WO2024086673A2 - Controlled reprogramming of a cell - Google Patents

Abstract

A method of identifying one or more suitable epigenetic editing target sites in a target cell is described herein. The method may include providing a first epigenetic map of a target cell in an initial cellular state. The first epigenetic map may provide an epigenetic state of each genomic site of a plurality of genomic sites in the target cell. The method may include providing a second epigenetic map of a desired cell in a desired cellular state. The second epigenetic map may provide an epigenetic state of each genomic site of the plurality of genomic sites in the desired cell. The method may include comparing the first epigenetic map and the second epigenetic map, thereby detecting a first differential. The method may include identifying a target genomic site in the plurality of genomic sites using the first differential. The target genomic site may be in an initial epigenetic state in the target cell and in a desired epigenetic state in the desired cell, wherein the initial epigenetic state and the desired epigenetic state are different epigenetic states.

Description

CONTROLLED REPROGRAMMING OF A CELL

RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63/379,967, filed on October 18, 2022, entitled “CONTROLLED PARTIAL REPROGRAMMING OF A CELL”, which is incorporated by reference in its entirety herein.

BACKGROUND

[0002] Since the discovery of Yamanaka factors (e.g., OCT4, SOX2, KLF4, and c-MYC), multiple studies have demonstrated the possibility to reverse aging and age-associated diseases through epigenetic reprogramming The current approaches rely on a limited set of transcription factors that induce widespread changes in cellular gene expression leading to uncontrolled, and undesirable, changes in cellular states such as loss of cell identity .

[0003] Attempts to directly control cellular state through epigenomic editing is limited, for example by relying on few simultaneous targets (e.g., 1-2 CpG sites) and effector functions (methylation and/or demethylation).

SEQUENCE LISTING

[0004] The instant application con tains a Sequence Listing which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. Said XML copy, created on October 12, 202.3, is named 65120-711 601 SL.xml and is 136,814 bytes in size.

SUMMARY OF THE DISCLOSURE

[0005] In one aspect, the present disclosure provides a method of identifying a target genomic site for epigenetic editing, comprising: (a) providing a first epigenetic map of a target cell in an initial cellular state, wherein the first epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the target cell; (b) providing a second epigenetic map of a desired cell in a desired cellular state, wherein the second epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the desired cell; (c) comparing the first epigenetic map and the second epigenetic map, thereby detecting a first differential; and (d) identifying a target genomic site in the plurality' of genomic sites using the first differential, wherein (i) the target genomic site is m an initial epigenetic state in the target cell, and (ii) the target genomic site is in a desired epigenetic state in the desired cell, wherein tire initial epigenetic state and the desired epigenetic state are different epigenetic states.

[0006] In some embodiments, the first epigenetic map and the second epigenetic map provide a methylation state. In some embodiments, the first epigenetic map and the second epigenetic map provide a 5' hydroxymethylation state, a chromatin accessibility state, or a histone modification state. In some embodiments, the initial epigenetic state is an unmethylated state and the desired epigenetic state is a methylated state. In some embodiments, the initial epigenetic state is a methylated state, and the desired epigenetic state is an unmethylated state. In some embodiments, the initial epigenetic state is an acetylated state, and the desired epigenetic state is an unacetylated state. In some embodiments, the initial epigenetic state is an unacetylated state and the desired epigenetic state is an acetylated state.

[0007] In some embodiments, the initial cellular state is a diseased state, and the desired cellular state is a healthier state relative to the initial cellular state. In some embodiments, the initial cellular state is an exhausted state, and the desired cellular state is a rejuvenated state relative to the initial cellular state. In some embodiments, tlie desired cellular state is a younger state relative to the initial cellular state. In some embodiments, the desired cellular state is a less differentiated state relative to the initial cellular state,, In some embodiments, the desired cellular state comprises a higher level of sternness relative to the desired cellular state. In some embodiments, the desired cell in the desired cellular state comprises a desired cellular functional state. In some embodiments, a cell in the desired cellular state comprises a desired phenotype. In some embodiments, the plurality of genomic sites comprises a whole genome of the target cell. In some embodiments, die method further comprises generating die first epigenetic map. In some embodiments, the method further comprises generating the second epigenetic map.

[0008] In some embodiments, the mediod further comprises: providing a third epigenetic map of an off-target cell, wherein the third epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the off-target cell; and wherein (d) further comprises detecting an epigenetic state of the target genomic site in the off-target ceil, wherein the epigenetic state of the target genomic site in the off-target cell and the desired epigenetic state are the same epigenetic state. In some embodiments, the method further comprises comparing the third epigenetic map with a fourth epigenetic map of a cell in the initial cellular state, thereby detecting a second differential and using tire second differential to identify the target genomic site in the plurality of genomic sites. In some embodiments, the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the first cell type and the second cell type are of different cell types. In some embodiments, the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the off-target cell is produced by modifying an initial cell of the first cell type using a drug. In some embodiments, the drug is capable of epigenetic editing. In some embodiments, the drug is a small molecule inhibitor. In some embodiments, the small molecule inhibitor is selected from rapamycin, a GSK-3 beta inhibitor, or a hypomethylation agent. In some embodiments, the drug is fusion polypeptide or a nucleic acid encoding the fusion polypeptide. In some embodiments, the fusion polypeptide comprises a nucleic acid binding moiety. In some embodiments, the nucleic acid binding moiety comprises a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a zinc finger domain, a TAL domain, atetR domain, a meganuclease, or an oligonucleotide. In some embodiments, the fusion polypeptide comprises an effector moiety. In some embodiments, the effector moiety comprises a DNMT1, DMMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DMMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1,MET1, DRM2, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e„ G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e., LSD1), KDM1B (i.e., LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1, KAT2A, KAT3A, KAT3B, or KAT13C, or a functional equivalent.

[0009] In some embodiments, the target cell is from a target tissue and the off-target cell is from an off-target tissue, wherein the target tissue and the off-target tissue are different tissues. In some embodiments, the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an olfactory cell, an auditory cell, or a kidney cell. In some embodiments, the target cell is a liver hepatocyte. In some embodiments, the off-target cell is a pancreatic acinar cell or a gastric epithelial cell. In some embodiments, the method further comprises generating the third epigenetic map. In some embodiments, the method further comprises generating the fourth epigenetic map.

[0010] In some embodiments, the method further comprises; providing an initial epigenetic map of a target cell in the initial cellular state, wherein the initial epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the target cell; providing a plurality of epigenetic maps of a plurality of off-target cells, wherein the plurality of epigenetic maps provides an epigenetic state of each genomic site of the plurality of genomic sites in each off-target cell in the plurality of off-target cells; and comparing the initial epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells, thereby detecting a third differential between the initial epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells; wherein (d) further comprises using the third differential to identify the target genomic site in the plurality of genomic sites, wherein the target genomic site is in the desired epigenetic state in each off-target cell in the plurality of off-target cells. In some embodiments, the first epigenetic map and the initial epigenetic map are the same epigenetic map. In some embodiments, the target cell is of a first cell type, and each off-target cell of the plurality of off-target cells is of a cell type that is different from the first cell type. In some embodiments, the plurality of off-target cells comprises at least two off-target cells of different cell types. In some embodiments, tire target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and the off-target tissues are different tissues. In some embodiments, the target cell is a liver hepatocyte. In some embodiments, the plurality of off-target cells comprises a pancreatic acinar cell or a gastric epithelial ceil. In some embodiments, the plurality of off-target cells comprises a pancreatic acinar cell and a gastric epithelial cell. In some embodiments, the method further comprises generating the plurality of epigenetic maps of the plurality of off-target cells.

[0011] In some embodiments, the present disclosure provides a method of modifying a target cell, comprising: (a) identifying a target genomic site for epigenetic editing according to die method of one or more embodiments described herein, (b) providing a target cell in the initial cellular state, wherein the provided target cell comprises the target genomic site in the initial epigenetic state; and (c) contacting the provided target cell with an epigenetic effector, wherein the epigenetic effector modifies the target genomic site from the initial epigenetic state to the desired epigenetic state, thereby producing a modified cell, wherein the modified ceil is in a modified cellular state. In some embodiments, the modified cellular state is functionally more similar to the desired cellular state than the initial cellular state is to the desired cellular state. In some embodiments, the method further comprises profiling a function of the modified cell. In some embodiments, the modified cell exhibits a modified phenotype that is different from an initial phenotype of the target cell. In some embodiments, the modified phenotype is more similar to a desired phenotype of the desired cell in the desired cellular state than the initial phenotype is to the desired phenotype. In some embodiments, the method further comprises profiling a phenotype of the modified cell. In some embodiments, modifying the target genomic site from the initial epigenetic state to the desired epigenetic state turns on expression of a gene. In some embodiments, modifying the target genomic site from tire initial epigenetic state to the desired epigenetic state turns off expression of a gene. In some embodiments, the epigenetic effector comprises: (i) an effector moiety; (ii) a first CRISPR/Cas domain; and (ii) a guide RNA complexed with the first CRISPR/Cas domain, wherein the guide RNA targets the epigenetic effector to the target genomic site.

[0012] In some embodiments, the present disclosure provides a method of screening a guide RNA for epigenetic editing, comprising: (a) modifying an initial target cell according to the method of one or more embodiments described herein, thereby producing a modified cell; (b) generating a fifth epigenetic map of the modified cell, wherein the fifth epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the modified cell; (c) comparing the fifth epigenetic map with a sixth epigenetic map, wherein the sixth epigenetic map is generated from a cell that is not treated with the epigenetic effector, thereby generating a fourth differential; (d) using the fourth differential to detect an off-target modification, wherein the off-target modification comprises a changed epigenetic state at an off-target genomic site in the modified cell, wherein the changed epigenetic state is different from an initial epigenetic state of the off-target genomic site in the initial target cell. In some embodiments, the first epigenetic map and the sixth epigenetic map are the same epigenetic map.

[0013] In another aspect, the present disclosure provides a method of screening a guide RNA for epigenetic editing, comprising: (a) introducing a CRISPR/Cas epigenetic effector and a first guide RNA to a first cell in an initial cellular state, wherein the first guide RNA is configured to bind to a first CRISPR/Cas domain in the CRISPR/Cas epigenetic effector and comprises a nucleic acid sequence complementary to a target genomic site, and wherein the CRISPR/Cas epigenetic effector introduces an on-target epigenetic editto the target genomic site and an off- target epigenetic edit to an off-target genomic site and produces a modified cell; (b) profiling the modified cell using epigenetic profiling to generate a first epigenetic map of the modified cell; and (c) comparing the first epigenetic map and a second epigenetic map of a second cell that has not been modified by introduction of the first guide RNA to generate a differential; and (d) using the differential to identify the off-target genomic site.

[0014] In some embodiments, the method further comprises: (i) introducing a second guide RNA and a second CRISPR/Cas domain to an additional cell in the initial cellular state, wherein the second CRISPR/Cas domain forms a complex with the second guide RNA and binds to tire off-target genomic site, thereby blocking the off-target genomic site from epigenetic editing; and

(ii) introducing the CRISPR/Cas epigenetic effector to the additional cell, wherein the CRISPR/Cas epigenetic effector introduces an on-target epigenetic edit to the target genomic site; wherein the first CRISPR/Cas domain and the second CRISPR/Cas domain do not crossreact.

[0G15] In another aspect, the present disclosure provides a method of identifying a target genomic site for epigenetic editing, comprising: (a) providing a target cellular epigenetic map of a target cell, wherein the target cellular epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the target cell; (b) providing an off-target cellular epigenetic map of an off-target cell, wherein the off-target cellular epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the off-target cell; (c) comparing the target cellular epigenetic map and the off-target cellular epigenetic map, thereby detecting a differential; and (d) using the differential to identify a target genomic site in the plurality of genomic sites, wherein (i) the target genomic site is a first epigenetic state in the target cell, and (ii) the target genomic site is in a second epigenetic state in the off-target cell, wherein the first epigenetic state and the second epigenetic state are different epigenetic states. In some embodiments, the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the first cell type and the second cell type are different cell types. In some embodiments, the target cell is from a target tissue and the off-target cell is from an off-target tissue, wherein the target tissue and the off-target tissue are different tissues. In some embodiments, the target cell is a liver hepatocyte. In some embodiments, the off-target cell is a pancreatic acinar cell or a gastric epithelial ceil. In some embodiments, the method further comprises generating the target cellular epigenetic map. In some embodiments, the method further comprises generating the off-target cellular epigenetic map.

[0016] In some embodiments, the method further comprises (i) providing a plurality of off- target cellular epigenetic maps, wherein each off-target cellular epigenetic map of the plurality of off-target cellular epigenetic maps provides an epigenetic state of each genomic site of the plurality of genomic sites in a distinct off-target cell in a plurality of off-target cells; (ii) comparing the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps, thereby detecting a differential between the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps; and (iii) using the differential to identify the target genomi c site in the plurality of genomic sites, wherein the target genomic site is in the second epigenetic state in each off-target cell in the plurality of off-target cells. In some embodiments, the target cell is of a first cell type, and each off-target cell of the plurality of off- target cells is of a cell type that is different from the fi rst cell type In some embodiments, the plurality of off-target cells comprises at least two off-target cells of different cell types. In some embodiments, the target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and the off-target tissues are different tissues. In some embodiments, the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an olfactory cell, an auditory cell, or a kidney cell In some embodiments, the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell, or a brain cell. In some embodiments, the target cell is a liver hepatocyte. In some embodiments, the plurality of off-target cells comprises a pancreatic acinar cell or a gastric epithelial cell. In some embodiments, the plurality of off- target cells comprises a pancreatic acinar cell and agastric epithelial cell. In some embodiments, the method further comprises generating the plurality of off-target cellular epigenetic maps.

BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Various aspects of the disclosed methods, devices, and systems are set forth with particularity in the appended claims. A better understanding of the features and advantages of the disclosed methods, devices, and systems will be obtained by reference to the following detailed description of illustrative embodiments and the accompanying drawings.

[0018] FIG. 1 shows an exemplary method for iteratively selecting a modification for one or more epigenetic markers.

[0019] FIG. 2 shows an exemplary’ method for iteratively’ selecting a modification for one or more epigenetic markers.

[0020] FIG. 3 shows an exemplar}⁷ method modifying epigenetic markers in a ceil according to a target list to generate a modified cell, according to some embodiments.

[0021] FIG. 4 shows a diagram depicting an epigenetic effector as described herein and a method of targeted methylation of a promoter region to silence gene expression as described herein.

[0022] FIG. 5 depicts an exemplary device, in accordance with some embodiments. [0023] FIG. 6 depicts an exemplary system, in accordance with some embodiments.

[0024] FIG. 7 illustrates a schematic representation of different constructs for OFF, ON, and

ON with transactivation system, and corresponding sgRNA designs (dCas = nuclease-deficient

Cas; AD - Activation Domain; crRNA = CRISPR RNA; tracRNA = trans-activatmg CRISPR

RNA; Rta = Epstein-Barr virus R transactivator).

[0025] FIG. 8 shows flow analysis for BFP reporter expression in cells transfected with ExpOFF plasmid and CD151 targeting sgRNA, CD81 targeting sgRNA, or non-targeting sgRNA control.

[0026] FIGs. 9A-9C illustrate flow analysis for CD81 and CD 151 expression in cells transfected with ExpOFF plasmid and CD151 or CD81 targeting sgRNA. FIG. 9A show's flow analysis for CD81 or CD151 expression in cells after 12 days post transfection. FIG. 9B shows flow analysis for CDS 1 or CD 151 expression in cells after 24 days post transfection. FIG. 9C show's flow analysis for CD81 or CD151 expression in cells after 35 days post transfection.

[0027] FIGs. 10A-10C illustrate plasmid constructs of ExpON, ExpOFF, and MCP-VPR. FIG. 10A show plasmid constructs of ExpOFF. FIG. 10B show plasmid constructs of ExpON. FIG. 10C show plasmid constructs of MCP-VPR.

[0028] FIG. 11 show s comparison of actual and reference null data sets for TCF7. Columns are CpGs in TCF7, rows are individual fragments spanning TCF7. Dark gray indicates methylated state. Light gray indicates unmethylated state.

[0029] FIG. 12 shows a plot of the Gap Statistic versus cluster number for TCF7. Dotted line indicates optimal number of clusters as given by: min(k) s.t. Gap(k) >= Gap(k+l)-3*SE(k+l), wherein min(k): minimum cluster number, k; Gap(k): Gap statistic at cluster number, k;

Gap(k+1): Gap statistic at cluster number, k+1; SE(k+l): Standard error of the null distribution at cluster number, k+1.

[0030] FIG. 13 shows a heatmap of TCF7 showing optimal number of clusters based on the Gap Statistic. Row annotation (gray) are CpG annotations showing various transcripts from the UCSC database (increasing gray bar height corresponds to introns, promoters, and exons, respectively). Dark gray indicates methylated state. Light gray indicates unmethylated state.

[0031] FIGs. 14A-14Z and FIGs. 14AA-14HH illustrate heatmaps of various T cell related genes showing optimal number of clusters based on the Gap Statistic. Row annotation (gray) are CpG annotations showing various transcripts from the UCSC database (increasing gray bar height corresponds to introns, promoters, and exons, respectively). FIG. 14A shows a heatmap of CD8A. FIG. 14B shows a heatmap of CD4. FIG. 14C shows a heatmap of TIGIT. FIG. 14D shows a heatmap of LAG3. FIG. 14E shows a heatmap of CCR7. FIG. 14F shows a heatmap of SELL. FIG. 14G shows a heatmap of TNFRSF9. FIG. 14H shows a heatmap of CTLA4. FIG. 141 show's a heatmap of CXCR3. FIG. 14 J show's a heatmap of SLAMF8. FIG. 14K show's a heatmap of CD69. FIG. 14L show's a heatmap of FOXP3. FIG. 14M shows a heatmap of EOMES. FIG. 14N shows a heatmap ofTBXZl. FIG. 140 shows a heatmap of GZMB. FIG. 14P shows a heatmap of CD19. FIG. 14Q shows a heatmap ofKLF4. FIG. 14R shows a heatmap ofMYC. FIG. 14S shows a heatmap of S0X2. FIG. 14T show's a heatmap of IL2.

FIG. 14U shows a heatmap ofIFNG. FIG. 14V shows a heatmap ofIL2RG. FIG. 14W show's a heatmap of MKI67, FIG. 14X shows a heatmap of CD 101. FIG. 14Y shows a heatmap ofIL7R. FIG. 14Z shows a heatmap of CD30. FIG. 14AA shows a heatmap of CD3E. FIG. 14BB show's a heatmap of CD27. FIG. 14CC shows a heatmap of CD28. FIG. 14DD show's a heatmap of IL7R. FIG. 14EE shows a heatmap of IL2.RB. FIG. 14FF shows a heatmap of CXCR.1. FIG. 14GG shows a heatmap of CDCR4. FIG. 14IIII shows a heatmap of BCL6. Dark gray indicates methylated state. Light gray indicates immethylated state.

[0032] FIG. 15 show's a histogram of the optimal number of clusters based on the Gap Statistic for >14,000 Hg38 genes.

[0033] FIGs. 16A-16E shows histograms of the optimal number ofclusters per chromosome based on the Gap Statistic for >14,0000 Hg38 genes. FIG. 16A shows from top to bottom histograms for chromosome 1, chromosome 14, chromosome 19, chromosome 3, and chromosome 8. FIG. 16B shows from top to bottom histograms for chromosome 10, chromosome 15, chromosome 2, chromosome 4, and chromosome 9. FIG. 16C shows from top to bottom histograms for chromosome 11, chromosome 16, chromosome 20, chromosome 5, and chromosome X. FIG. 16D shows from top to botom histograms for chromosome 12, chromosome 17, chromosome 21, and chromosome 6. FIG. 16E shows from top to bottom histograms for chromosome 13, chromosome 18, chromosome 22, and chromosome 7.

[0034] FIGs. 17A-17Z and FIGs. 17AA-17II illustrate heatmaps of various genes located on tire X chromosome showing optimal number of clusters based on the Gap Statistic. Row' annotation (gray) are CpG annotations showing various transcripts from the UCSC database (increasing gray bar height corresponds to introns, promoters, and exons, respectively). FIG. 17A shows a heatmap of EOLA2. FIG. 17B shows a heatmap of EMD. FIG. 17C shows a heatmap ofPGRMCl . FIG. 17D shows a heatmap ofRPLIO. FIG. 17E shows a beatmap of EOLA1. FIG. 17F shows a heatmap of HTATSF1. FIG. 17G shows a heatmap ofNDLFBll . FIG. 17H shows a heatmap of CCNQ gene. FIG. 171 shows a heatmap of IKBKG. FIG. 17J shows a heatmap of SLC25A5. FIG. 17K shows a heatmap of TMEM185A. FIG. 17L shows a heatmap ofZBTB33. FIG. 17M shows a heatmap of AMER1. FIG. 17N shows a heatmap of DYNLT3. FIG. 170 shows a heatmap of PRPSI. FIG. 17P shows a heatmap of ZNF449. FIG. 17Q shows a heatmap of BCAP31. FIG. 17R shows a heatmap of ZNF711. FIG. 17S shows a heatmap ofNALF2. FIG. 17T shows a heatmap of MORF4L2. FIG. 17U shows a heatmap of UBL4A. FIG. 17V shows a heatmap of ZNF41 . FIG. 17W shows a heatmap of ARX. FIG. 17X shows aheatmap of FAM199X. FIG. 17Y shows a heatmap of RAP2C. FIG. 17Z shows a heatmap of F8A2. FIG. 17AA shows a heatmap ofMCTSl . FIG. 17BB shows a heatmap of MED12. FIG. 17CC shows a heatmap of PRDX4. FIG. 17DD shows aheatmap ofPRPS2. FIG. 17EE shows a heatmap of ERCC6L. FIG. 17FF shows aheatmap of LONRF3. FIG. 17GG shows a heatmap of SOWAHD. FIG. 17HH shows a heatmap of SYP. FIG. 1711 shows a heatmap of TCEAL3. Dark gray indicates methylated state. Light gray indicates unmethylated state.

[0035] FIG. 18 shows a heatmap and plot of calculated information gain for the LAG3 gene.

Higher values of information gain indicate those CpGs are more important in defining the clusters. Dark gray indicates methylated state. Light gray indicates unmethylated state.

[0036] FIG. 19 shows a heatmap and plot of calculated information gam for the MYC gene.

Higher values of information gain indicate those CpGs are more important m defining the clusters. Dark gray indicates methylated state. Light gray indicates unmethylated state.

[0037] FIG. 20 depicts an example of sorting CD8+ T cells into naive, central memory (CM), effector (Eff), and effector memory' (EM) populations.

[0038] FIGs. 21 A-21D depict example epigenetic heatmaps generated of the GZMK gene in accordance with some embodiment. FIG. 21A depicts an example epigenetic heatmap of the GZMK gene constructed from methylome sequencing of naive CD8+ T-cells. FIG. 21 B depicts an example epigenetic map of the GZMK gene constructed from methylome sequencing of central memory CD8+ T-cells. FIG. 21C depicts an example epigenetic heatmap of the GZMK gene constructed from methylome sequencing of effector CD8+ T-cells. FIG. 21D depicts an example epigenetic heatmap of the GZMK gene constructed from methylome sequencing of effector memory CD8+ T-cells. Dark gray indicates unmethylated state. Light gray indicates methylated state. [0039] FIGs. 22A-22D depict, example epigenetic heatmaps generated of the SELL gene in accordance with some embodiment. FIG. 22A depicts an example epigenetic heatmap of the SELL gene constructed from methylome sequencing of naive CD8+ T-celis. FIG. 22B depicts an example epigenetic map of the SELL gene constructed from methylome sequencing of central memory CD8+ T-cells. FIG. 22C depicts an example epigenetic heatmap of the SELL gene constructed from methylome sequencing of effector CD8-I- T-cells. FIG. 22D depicts an example epigenetic heatmap of the SELL gene constructed from methylome sequencing of effector memory' CD8+ T-cells. Dark gray indicates unmethylated state. Light, gray indicates methylated state.

[0040] FIGs. 23A-23D depict example epigenetic heatmaps generated of the CD27 gene in accordance with some embodiment. FIG. 23A depicts an example epigenetic map of the CD27 gene constructed from methylome sequencing of naive CD8+ T-cells. FIG. 23B depicts an example epigenetic heatmap of the CD27 gene constructed from methylome sequencing of central memory CD8+ T-cells. FIG. 23C depicts an example epigenetic heatmap of the CD27 gene constructed from methylome sequencing of effector CD8+ T-cells. FIG. 23D depicts an example epigenetic heatmap of the CD27 gene constructed from methylome sequencing of effector memory CD8+ T-cells. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0041] FIG. 24 shows epigenetic maps of chromosome 11 (posi tions 831,698-834,439), depicting the methylation patterns in the CD151 gene of edited cells and of control cells. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0042] FIG. 25 shows epigenetic heatmaps of chromosome 11 (positions 831,698-834,439) generated for edited cells and control cells. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0043] FIG. 26 shows epigenetic maps of chromosome 1 (positions 55,037,760-55,066,456), depicting the methylation patterns in the PCSK9 gene for different cell types.

[0044] FIG. 27 shows an epigenetic map depicting the methylation paterns of a region of chromosome 19 for edited cells and control cells. Dark gray indicates unmethylated state. Light gray indicates methylated state. [0045] FIG. 28 shows an epigenetic map depicting the methylation patterns of a region of chromosome 12 for edited cells and control cells. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0046] FIG. 29 shows comparison of epigenetic maps of RUNXl gene in naive cells versus effector cells and where the footprint of RUNXl is enriched in each cell type. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0047] FIGs. 30A-30C illustrate transcription factors with distinct epigenetic states. FIG. 30A shows comparison of epigenetic maps of FOXN3 gene in naive cells versus effector cells. FIG.

30B shows comparison of epigenetic maps of ELK 1 gene in naive cells versus effector cells.

FIG. 30C shows comparison of epigenetic maps of BACH2 gene in naive cells versus effector cells. Dark gray indicates unmethylated state, high; gray indicates methylated state.

[0048] FIGs. 31A-31H illustrate differentially methylated regions of genes that are downstream or upstream of the GSK3 beta pathway. FIG. 31A shows a schematic diagram of GSK3 beta pathway. FIG. 31 B shows differentially methylated regions ofGSK3. FIG. 31C shows differentially methylated regions of AXIN1. FIG. 31D shows differentially methylated regions of AXIN2. FIG. 31E shows differentially methylated regions of LEF1, which is downstream of GSK3. FIG. 31F show's differentially methylated regions of TCF7, which is downstream of GSK3. FIG. 31G show's differentially methylated regions of BCL1 IB, which is downstream of GSK3. FIG. 31H shows differentially methylated regions of TLE, which is downstream of GSK3. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0049] FIGs. 32A-32C illustrate differentially methylated regions of genes related to AP-1 and RUNX (e.g., NFATC2, RUNXl) in naive cells versus effector cells. FIG. 32A and FIG. 32B show differentially methylated regions of NFATC2. FIG. 32C show s differentially methylated regions of RUNXl. Dark gray indicates unmethylated state. Light gray indicates methylated state.

[0050] FIG. 33 illustrates an exemplary' method for generating a personalized differential cellular state profile.

[0051] FIG. 34A and 34B show exemplary methods for partially reprogramming a cell. DETAILED DESCRIPTION

[0052] Directly editing the epigenome (e.g., by methylating, demethylating, acetylating, or deacetylating chromosomal target sites) provides a direct means of controlling cellular state. Methylatson and demethylation techniques can be used to modify both DNA targets and histone targets, while acetylation and deacetylation techniques can be used to modify histone targets. The disclosure provides methods of analyzing empirical data and/or other available (e.g., publicly available) data sets to select target epigenetic sites and/or epigenetic modifications. The selection may be iterative, for example by modifying a cell according to the selected target and/or modification, identifying effects of the modification (e.g., multi-omic and/or functional effects), and selecting anew target and/or effectors based on the identified effects.

[0053] The disclosure provides a method of selecting a modification for one or more epigenetic markers. "Hie method may include obtaining a target list comprising epigenetic markers (e.g., one or more CpG sites and/or one or more histones) and an associated modification (e.g., methylation, demethylation, acetylation, and/or deacetylation) for each epigenetic marker. The target list may include targets associated with a desired cellular state (for example, a biological age and/or a disease state). The method may include modifying at least a portion of the epigenetic markers in a cell according to the target list to generate a modified cell . The method may include profiling the modified cell to determine a cellular state profile for the modified cell. The method may include selecting, based on the cellular state profile for the modified ceil, an updated target list comprising updated epigenetic markers and an associated modification for each updated epigenetic marker The method may further include determining a differential between the cellular state profile and a desired cellular state profile. The updated target list maybe based on this differential. A cell may be reprogrammed by editing the cell based on tire updated target list.

[0054] The method may be performed iteratively. For example, the method may further include modifying at least a portion of the epigenetic markers from the updated target list in a second cell to generate a second modified cell. The second modified cell can then be profiled to determine a cellular state profile for the second modified cell. Based on the cellular state profile for the second modified cell, a second updated target list, comprising second updated epigenetic markers and an associated modification for each second updated epigenetic marker, may be selected. This process may be repeated any number of desired iterations (e.g , at least 2, at least 3, at least 4, or at least 5 iterations). [0055] The method may be used to select and/or evaluate a plurality of epigenetic markers. For example, the target list may include 2 or more, 10 or more, 25 or more, 50 or more, 100 or more.

500 or more, or 1000 or more epigenetic markers. The method may also be used to simultaneously modify a plurality of epigenetic markers in the cell according to the target list.

For example, 2 or more, 10 or more, 25 or more, 50 or more, 100 or more, 500 or more, or 1000 or more epigenetic markers may be simultaneously modified in the cell.

[0056] The method may include, for example, predicting one or more (e.g., a plurality of) epigenetic modifications (e.g., a target site and/or target-site associated effectors). The method may include modifying a cell according to the one or more predicted epigenetic modifications, Tire method may further include profiling the cellular state of the cell to generate a cellular profile. The generated cellular profile may then be used as an input to predict one or more new epigenetic modifications. FIG. I, FIG. 2, and FIG. 3 illustrate exemplary flowcharts for conducting the method.

Terminology

[0057] Unless defined otherwise, all technical and scientific terms used have the meaning commonly understood by one of ordinary skill in the art. Tire following terms have the meanings given:

[0058] Singular forms “a,” ‘an,” “the,” and “said” include the plural forms as well, unless tire context clearly indicates otherwise.

[0059] The terminology, “and/or,” used in a phrase such as “X and/or Y” includes both X and Y; X or Y; X (alone); and Y (alone),

[0060] The words “comprising,” “comprise,” “comprises,” “having,” “have,” “has,” “including,” “includes,” “include,” “containing,” “contains” and “contain” are inclusive or open- ended and do not exclude additional, unrecited elements or method steps. Aspects and embodiments of the invention described include “comprising,” “consisting of,” and “consisting essentially of’ (and variants thereof) aspects and embodiments,

[0061] Use of terminology like “some embodiments,” “an embodiment,” “one embodiment,” “other embodiments,” “various embodiments,” “another embodiment,” “some cases” and the like with reference to a particular feature or characteristic described in connection with the embodiment or case, means that the feature is included in one or more embodiments, but not necessarily all embodiments. Similarly, reference to “a method,” “the method,” “one method” and the like with reference to a particular feature or characteristic described in connection with the method, means that the feature is included in one or more methods, but not necessarily all methods

[0062] “About” and “approximately” refer to the usual error range for the respective value readily known to the skilled person in this technical field. Exemplary degrees of error are within

20 percent (%), typically, within 10%, and more typically, within 5% of a given value or range of values. Reference to “about” or “approximately” a value or parameter includes (and describes) embodiments directed to that value or parameter per se.

[0063] “Determining,” “measuring,” “evaluating,” “assessing,” “assaying,” and “analyzing” refer to forms of measurement, include determining whether an element is present or not (for example, detection), can include quantitative, qualitative, or quantitative and qualitative determinations. Assessing can be relative or absolute. “Detecting the presence of’ can include determining the amount of something present in addition to determining whether it is present or absent depending on the context.

[0064] “Cancer” and “tumor” are used interchangeably herein. These terms refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in tire form of a tumor, but such cells can exist alone within an animal, or can be a non-tumorigenic cancer cell, such as a leukemia cell. These terms include a solid tumor, a soft tissue tumor, or a metastatic lesion, “cancer” includes premalignant, as well as malignant cancers.

[0065] “Cell” refers to a biological cell. A cell can be the basic structural, functional and/or biological unit of a living organism. A cell can originate from any organism having one or more cells. Some non-limiting examples include: a prokaryotic cell, eukaryotic cell, a bacterial cell, an archaeal cell, a cell of a single-cell eukaryotic organism, a protozoa cell, a cell from a plant, an algal cell, a fungal cell an animal cell, a cell from an invertebrate animal (e.g. fruit fly, cnidarian, echinoderm, nematode, etc.), a cell from a vertebrate animal (e.g., fish, amphibian, reptile, bird, mammal), a cell from a mammal (e.g., a pig, a cow, a goat, a sheep, a horse, a rodent, a rat, a mouse, a non-human primate, a human, etc.). A cell can be a somatic cell, for example, a skin cell, a nerve cell, a muscle cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an ol factory cell, an auditory' cell, or a kidney cell, or a germ cell, e.g., an oocyte, a sperm. In some embodiments, the cell may be an adult cell, e.g., adult somatic cell, a sperm, an oocyte . In some embodiments the somatic cell is an “adult somatic cell,” which refers to a cell that is present in or obtained from an organism other than an embryo or a fetus or results from proliferation of such a cell in vitro. Unless otherwise indicated, the compositions and methods for rejuvenating a somatic cell can be performed both in vivo and in vitro, where in vivo is practiced when a somatic cell is present within a subject, and wdrere in vitro is practiced using an isolated somatic cell maintained in culture. In some embodiments, the ceil may be a stem cell, e.g , an embryonic stem cell, an adult stem cell, an induce pluripotent stem cell (iPSC). Induced pluripotent stem cells can be derived, for example, from adult somatic cells such as skin or blood cells. In some embodiments, the stem cell may be a totipotent stem cell, a pluripotent stem cell, a multipotent stem cell, or a unipotent stem cell. Certain other cell- related terminology is defined as follows:

(A) “Allogeneic cell” refers to a ceil obtained from an individual who is not the intended recipient of the cell as a therapy (the cell is allogeneic to the subject). Allogeneic cells of the disclosure may be selected from immunologically compatible donors with respect to the subject of the methods of the disclosure. Allogeneic cells of the disclosure may be modified to produce “universal” allogeneic cells, suitable for administration to any subject without unintended immunogenicity. Allogeneic cells of the disclosure include, but are not limited to. hematopoietic cells and stem cells, such as hematopoietic stem cells. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of an allogeneic cell.

(B) “Autologous cell” refers to a cell obtained from tire same individual to whom it may be administered as a therapy (the cell is autologous to the subject). Autologous cells of the disclosure include, but are not limited to, hematopoietic cells and stem cells, such as hematopoietic stem cells. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of an autologous cell.

(C) “Cell therapy” refers to the delivers' of a cell or cells into a recipient for therapeutic purposes. Cells described herein may be used in compositions and methods of cell therapy.

(D) “Hematopoietic cell’’ refers to a cell that arises from a hematopoietic stem cell. This includes, but is not limited to, myeloid progenitor cells, lymphoid progenitor cells, megakaryocytes, erythrocytes, mast cells, myeloblasts, basophils, neutrophils, eosinophils, macrophages, thrombocytes, monocytes, natural killer cells, T lymphocytes, B lymphocytes and plasma cells. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of a hematopoietic cell,

(E) “Induced pluripotent stem cell'’ (iPS or iPSC) refers to a pluripotent stem cell that can be generated directly from a somatic cell. This includes, but is not limited to, specialized cells such as skin or blood cells derived from an adult. In in certain embodiments, the methods of tire disclosure may be used to modify a cellular state of an iPSC.

(F) “Mesenchymal cell” refers to a cell that is derived from a mesenchymal tissue. In some cases, cells of the disclosure may be mesenchymal cells. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of a mesenchymal cell.

(G) “Mesenchymal stromal cell” (MSC) refers to a spindle shaped plastic-adherent cell isolated from bone marrow, adipose, and other tissue sources, with multi potent differentiation capacity in vitro. For example, a mesenchymal stromal cell can differentiate into osteoblasts (bone cells), chondrocytes (cartilage cells), myocytes (muscle cells), and adipocytes (fat cells which give rise to marrow' adipose tissue). The term mesenchymal stromal cell is suggested in the scientific literature to replace the term “mesenchymal stem cell”. In some cases, cells of the disclosure may be mesenchymal stromal cells. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of a mesenchymal stromal cell or to produce a mesenchymal stromal cell.

(H) “Mesenchyme” and “mesenchymal” refer to a type of animal tissue including loose cells embedded in a mesh off proteins and fluid, i.e., the extracellular matrix. Mesenchyme directly gives rise to most of the body's connective tissues including bones, cartilage, lymphatic system, and circulatory system.

(I) “Multipotent” refers to a cell that can develop into more than one cell type but is more limited than a pluripotent cell. For example, adult stem cells and cord blood stem cells may be considered multipotent. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of a multipotent cell or to produce a multipotent cell. (J) “Pluripotent stem cell” ( PSC) refers to a cell that can maintain an undifferentiated state indefinitely and can differentiate into most, if not all cells of the body. In in certain embodiments, the methods of the disclosure may be used to modify’ a cellular state of a PSC or to produce a PSC cell ,

(K) ‘"Stem ceil” refers to an undifferentiated or partially differentiated celi that can differentiate into various types of cells and proliferate indefinitely to produce more of the same stem cell. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of a stem cell or to produce a stem cell.

(L) “T-lymphocyte” or T-cell” refers to a hematopoietic cell that normally develops in the thymus. T-lymphocytes or T-cells include, but are not limited to, natural killer T cells, regulatory T cells, helper T cells, cytotoxic T cells, memory' T cells, gamma delta T cells, and mucosal invariant T cells. In in certain embodiments, the methods of the disclosure may be used to modify a cellular state of a stem cell or to produce a stem cell.

(M) “Transfect,” “transform” and “transduce” refer to a process by which exogenous nucleic acid is transferred or introduced into a cell or a host cell. A “transfected” or “transformed” or “transduced” cell is one which has been transfected, transformed, or transduced with exogenous nucleic acid or progeny of the cell. Cells of the disclosure may be modified according to methods of the disclosure, which may make use of transfection, transformation and/or transduction to deliver components usefill for epigenetic modifications of the cells.

[0066] “Complementary” and “complementarity” refer to the association of double-stranded nucleic acids by base pairing through specific hydrogen bonds. The base paring may be standard

Watson-Crick base pairing (e.g., 5'-A G T C-3' pairs with the complementary sequence 3’-T C A

G-5') or other non-traditional type. Complementarity is typically measured with respect to a duplex region and thus excludes overhangs, for example. Complementarity between two strands of the duplex region may be partial and expressed as a percentage (e.g., 80%), if only some (e.g..

80%) of the bases are complementary.

[0067] “CpG Island” refers to a region with a high frequency of CpG sites. The region is at least 200 bp, with a GC percentage greater than 50%, and an observed -to-expected CpG ratio greater than 60% [0068] “Domain’'' refers to a section or portion of a polypeptide or a nucleic acid sequence encoding the section or the portion of the polypeptide that contributes to a specified function to the polypeptide. A domain may comprise a contiguous region or more than one distinct noncontiguous regions of a polypeptide.

[0069] “Edit” and “editing” with reference to a nucleic acid refers to any change in nucleic acid, including insertion, deletion, and correction. “Editing” can also refer to any epigenetic changes or epigenetic editing. In some cases, “epigenetic editing” refers to the selective and reversible modification of DNA (e.g., methylation, demethylation) and histones (methylation, demethylation, acetylation, deacetylation). The changes can be in a genome of a cell.

“Insertion,” “deletion,” and “correction” have the following meanings:

(A) “Insertion” refers to an addition of one or more nucleotides in a DNA sequence. Insertions can range from small insertions of a few nucleotides to insertions of large segments such as a cDNA or a gene.

(B) “Deletion” refers to a loss or removal of one or more nucleotides in a DNA sequence or a loss or removal of the function of a gene. In some cases, a deletion can include, for example, a loss of a nucleotide, a few nucleotides, an exon, an intron, a gene segment, or the entire sequence of a gene. Deletion of a gene may’ include any’ deletion sufficient result in the elimination or reduction of the function or expression of the gene or its gene product.

(C) “Correction” refers to a change of one or more nucleotides of a genome in a cell, whether by insertion, deletion, or substitution.

[0070] Editing may also result in a gene knock-in, knock-out or knock-down, each defined as follows:

(A) “Knock-in” refers to an addition of a DN A sequence, or fragment thereof into a genome.

(B) “Knockout” refers to the elimination of a gene or the expression of a gene.

(C) “Knock-down” refers to reduction in tire expression of a gene or its gene product(s).

[0071] “Effector,” “epigenetic effector” and “effector polypeptide” refer to a polypeptide engineered to bind a specific target sequence in chromosomal DNA and modify the DNA or protein(s) associated with DNA at or near the target, sequence and modify the target, sequence. An epigenetic effector may, in some cases, include a nucleic acid binding moiety and one or more effector moietics. “Effector moiety” refers to a domain that can alter the expression of a target gene when localized to an appropriate site in the nucleus of a cell, e.g., in a target nucleotide sequence.

[0072} “Epigenetic map” as used herein refers to any modes of representation of epigenetic states across a plurality of different regions, e.g., coding sequences, intergenic spacers, regulatory regions, e.g., promoters, etc., of the entire genome, a portion of the genome or near or around or within a particular gene or genes.

[0073] “Gene” refers to a combination of polynucleotide elements, that when operatively linked in either a native or recombinant manner, provide some product or function. “Gene” is to be interpreted broadly and can encompass mRNA, cDNA, cRNA and genomic DNA forms of a gene. In some uses, “gene” encompasses the transcribed sequences, including 5' and 3' untranslated regions (5'-UTR and 3'-UTR), exons and introns. In some genes, the transcribed region will contain “open reading frames” that encode polypeptides. In some cases, a “’gene” comprises only the coding sequences (e.g., an “open readme frame” or “coding region”) necessary' for encoding a polypeptide. In some cases, a “gene” may not encode a polypeptide, for example, ribosomal RNA genes (rRNA) and transfer RNA (tRNA) genes. In some cases, a “gene” may include not only the transcribed sequences, but in addition, also includes nontranscribed regions including upstream and downstream regulatory regions, enhancers, and promoters.

[0074] “Guide RNA,” “gRNA,” “single guide RNA,” and “sgRNA” refer to any RNA molecule (or a group of RN A molecules collectively) that facilitates binding of a polypeptide, such as a Cas protein, to a specific location of a target nucleic acid. A single guide RNA (sgRNA) can comprise a crRNA and tracrRNA that are fused together. A guide RNA (gRNA) can comprise a crRNA segment and/or a tracrRNA segment. Exemplary guide RNAs include, but are not limited to, crRNAs, pre-crRNAs (e.g., DR-spacer-DR), and mature crRNAs (e.g., mature JDR- spacer, mature DR-spacer-mature JDR). “Guide RNA” also encompasses an RNA molecule or suitable group of molecular segments that binds a Cas protein other than Cas9 (e.g., Cpfl protein) and that possesses a guide sequence within the single or segmented strand of RNA comprising the functions of a guide RNA which include Cas protein binding to form a gRNA: Cas protein complex capable of binding, nicking and/or cleaving a complementary target sequence in a target polynucleotide.

[0075] “Homolog” refers to a gene or a protein that is related to another gene or protein by a common ancestral DNA sequence and is functionally similar. Homologous proteins may but need not be structurally related or are only partially structurally related. “Ortholog” refers to a gene or protein that is related to another gene or protein by a speciation event. Orthologous proteins may in some cases be structurally related or only partially structurally related. In some cases, an ortholog may retain the same function as the gene or protein to which they are orthologous. Non-limiting examples of Cas9 orthologs include: Akkermansia muciniphila Cas9 (AmCas9), Bifidobacterium longum Cas9 (BlC-as9), Campylobacter jejuni Cas9 (CjCas9), Francisella novicida Cas9 (FnCas9), Geobacillus stearothermophilus Cas9 (GeoCas9), Legionella pneumophila Cas9 (LpCas9), Neisseria lactamica Cas9 (NlCas9), Neisseria meningitidis Cas9 (NmCas9), Oscillospira luneus Cas9 (OlCas9), Staphylococcus aureus Cas9 (SaCas9), Streptococcus pyogenes Cas9 (SpCas9), Streptococcus thermophilus CRISPR1 Cas9 (St !Cas9), Streptococcus thermophilus CR1SPR3 Cas9 (St3Cas9). Homologs and orthologs may be identified by homology modeling (e g., see Filipek, S. (2023). Homology modeling: Methods and protocols . Humana Press.).

[0076] “Individual.” “patient,” and “subject” refer to any single subject, e.g., a mammal (including such non-human animals as, for example, dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non-human primates) for which treatment is desired. In particular embodiments, the patient is a human.

[0077] “Methylate” and “methylating” refer to (i) the addition one or more methyl groups to one or more cysteine residues, or (li) the replacement of one or more unmethylated cysteine residues with one or more methylated cysteine residues, or (fii) the addition of one or more methyl to one or more sites to one or more histones. “Demethylate” and “demethylating” refer to (i) the removal of one or more methyl groups from one or more cysteine residues, or (ii) the replacement of one or more methylated cysteine residues with one or more unmethylated cy steine residues, or (iii) the removal of one or more methyl residues from one or more sites on one or more histones.

[0078] “Modifying,” “modification,” “modulate” and “modulating” refer to a change in the structure, expression levels or activity of a gene or polypeptide as detected by standard art known methods such as those described herein, a modification (e.g., increase or decrease) includes a 10% change in expression levels, a 25% change, a 40% change, and a 50% or greater change in expression levels.

[0079] “Polynucleotide,” “oligonucleotide,” “nucleic acid,” and “nucleic acid sequence” are used interchangeably to refer to a polymeric form of nucleotides, such as deoxyribonucleotides, ribonucleotides, NS analogs thereof. Polynucleotides may be provided in single-, double-, or multi-stranded form in a linear, branched, or circular conformation. A polynucleotide can be exogenous (e.g., a sequence that is not native to the cell, or a chromosomal sequence whose native location in the genome of the cell is in a different chromosomal location) or endogenous (e g,, a chromosomal sequence that is native to the cell) to a cell A polynucleotide can exist in a cell-free environment A polynucleotide can be a gene or fragment thereof. A polynucleotide can be DNA. A polynucleotide can be RNA, e.g., an mRNA. A polynucleotide can comprise one or more analogs (e.g., altered backbone, sugar, or nucleobase). Non-limiting examples of modifications include addition (or removal) of acetyl groups, amino groups, carboxyl groups, carboxymethyl groups, hydroxyl groups, methyl groups, phosphoryl groups, and thiol groups, as well as the substitution of the carbon and nitrogen atoms of the bases with oilier atoms (e.g., 7- deaza purines). Nucleotide analogs also include dideoxy nucleotides, 2'-0-methyl nucleotides, locked nucleic acids (LNA), peptide nucleic acids (PNA), and morpholines. If present, modifications to the nucleotide structure can be imparted before or after assembly of the polymer.

[0080] “Profile” refers to a set of one or more biological features determined from a sample. Exemplary features that may be included in a profile include, but are not limited to, epigenetic features (e.g., methylation and/or acetylation status of a CpG site or histone), nucleic acid sequence data, expression data, proteomics data, metabolomics data, results from a functional assay, cellular morphological characteristics, etc, “Cellular profile,” “epigenetic profile,” and “personalized differential cellular state profile” have the following meanings:

(A) “Cellular profile” refers to the epigenetic characteristics of a cell’s genome. Non-limiting examples of epigenetic characteristics include DNA methylation, DNA demethylation, histone methylation, histone demethylation, histone acetylation, histone deacetylation and combinations thereof.

(B) “Epigenetic profile” and “epigenome profile” refer to epigenetic characteristics of genomic sequences in cells or tissues. Non-limiting examples of epigenetic characteristics include DNA methylation, DNA demethylation, histone methylation, histone demethylation, histone acetylation, histone deacetylation and combinations thereof.

(C) “Personalized differential cellular state profile” refers to the cellular profile of a cell compared to a healthy and/or young cell of similar type. [0081 ] “Reprogram,” “transdifferentiate” and the like refer to a process that alters or reverses the differentiation state of a differentiated cell (e.g., a somatic cell). Reprogramming can encompass complete reversion of the differentiation state of a differentiated cell (e.g., a somatic cell) to a pluripotent state or a multipotent state. Reprogramming can encompass complete or partial reversion of the differentiation state of a differentiated cell (e.g., a somatic cell) to an undifferentiated cell (e.g., an embryonic-like cell). Reprogramming can result in expression of particular genes by the cells, the expression of which further contributes to reprogramming. Programming of a differentiated cell (e.g., a somatic cell) according to the methods of the disclosure can cause a differentiated cell to assume a less differentiated state, or an undifferentiated state (e.g., an undifferentiated cell).

[0082] “Sample,” refers to a composition that is obtained or derived from a subject and/or individual of interest that contains or may contain a cellular and/or other molecular entity that is to be characterized and/or identified, for example, based on physical, biochemical, chemical, and/or physiological characteristics. Samples include, but are not limited to, tissue samples, primary or cultured cells or cell lines, cell supernatants, cell lysates, platelets, serum, plasma, vitreous fluid, lymph fluid, synovial fluid, follicular fluid, seminal fluid, amniotic fluid, milk, whole blood, plasma, serum, blood-derived cells, urine, cerebro-spinal fluid, saliva, sputum, tears, perspiration, mucus, tumor lysates, and tissue culture medium, tissue extracts such as homogenized tissue, tumor tissue, cellular extracts, and combinations thereof.

[0083] "‘Sequence homology” and “sequence identity” refer to sequence similarity between two peptides or between two nucleic acid molecules. Homology can be determined by comparing a position in each sequence which can be aligned for purposes of comparison. When a position in the compared sequence can be occupied by the same base or ammo acid, then the molecules can be homologous at that position. A degree of homology between sequences can be a function of the number of matching or homologous positions shared by the sequences. As a practical matter, whether any particular sequence can be at least 50%, 60%, 70%, 80%, 85%, 90%, 92%, 95%, 96%, 97%, 98% or 99% identical to any sequence described he(which can correspond with a particular nucleic acid sequence described herein), such particular polypeptide sequence can be determined conventionally using known computer programs such as the Bestfit program (Wisconsin Sequence Analysis Package, Version 8 tor Unix, Genetics Computer Group, University Research Park, 575 Science Drive, Madison, Wis 53711) When using Bestfit or any other sequence alignment program to determine whether a particular sequence is, for instance, 95% identical to a reference sequence, the parameters can be set such that the percentage of identity can be calculated over the full length of the reference sequence and that gaps in sequence homology of up to 5% of the total reference sequence can be allowed. For an amino acid sequence, in some cases, the sequence identity between a reference sequence (query' sequence, i.e., a sequence of the disclosure) and a subject sequence, also referred to as a global sequence alignment, can be determined using the FASTDB computer program based on the algorithm of Brutlag et al. (Comp App. Biosci. 6:237-245 (1990)). In some embodiments, parameters for a particular embodiment in which identity can be narrowly construed, used in a FASTDB ammo acid alignment, can include: Scoring Scheme=PAM (Percent Accepted Mutations) 0, k-tuple=2, Mismatch Penalty=l , Joining Penaity=20, Randomization Group Length=0, Cutoff Score=l, Window Size=sequence length, Gap Penalty=5, Gap Size Penalty =0.05, Window Size=500 or the length of the subject sequence, whichever can be shorter. According to this embodiment, if the subject sequence can be shorter than the query sequence due to N- or C-terminal deletions, not because of internal deletions, a manual correction can be made to the results to take into consideration the fact tiiat die FASTDB program does not account for N- and C-terminal truncations of tire subject sequence when calculating global percent identity. For subject sequences truncated at the N- and C-termini, relative to the query sequence, the percent identity can be corrected by calculating the number of residues of the query sequence that can be lateral to the N- and C-terminal of the subject sequence, which can be not matched/aligned with a corresponding subject residue, as a percent of the total bases of the query sequence. A determination of whether a residue can be matched/aligned can be determined by results of the FASTDB sequence alignment. This percentage can be then subtracted from the percent identity, calculated by the FASTDB program using the specified parameters, to arrive at a final percent identity score. This final percent identity score can be used for the purposes of this embodiment. In some cases, only residues to the N- and C-termini of the subject sequence, which can be not matched/aligned with the query sequence, can be considered for the purposes of manually adjusting tire percent identity score. That is, only query' residue positions outside the farthest N- and C-terminal residues of the subject sequence can be considered for this manual correction. For example, a 90-residue subject sequence can be aligned with a 100-residue query sequence to determine percent identity. The deletion occurs at the N-termmus of the subject sequence, and therefore, the FASTDB alignment does not show a matching/alignment of the first ten residues at the N-terminus. The ten unpaired residues represent 10% of the sequence (number of residues at the N- and C-termini not matched/total number of residues in the query sequence) so 10% can be subtracted from the percent identity' score calculated by the FASTDB program. If the remaining ninety residues were perfectly matched, the final percent identity can be 90%. In another example, a 90-residue subject sequence can be compared with a 100-residue query sequence. This time the deletions can be internal deletions, so there can be no residues at the N- or C -termini of the subject sequence which can be not matched/aligned with the query. In this case, the percent identity- calculated by FASTDB cannot be manually corrected. Once again, only residue positions outside the N- and C-terminal ends of the subject sequence, as displayed m the FASTDB alignment, which can be not matched/aligned with the query' sequence can be manually corrected for.

[0084] “Subject,” “host,” and “individual,” are used interchangeably to refer to animals, typically mammalian animals. Any suitable mammal can be treated by a method or composition described herein. A mammal can be administered a primer editor and/or a PEgRNA as described herein. Non-limiting examples of mammals include humans, non -hum an primates (e.g., apes, gibbons, chimpanzees, orangutans, monkeys, macaques, and the like), domestic animals (e.g., dogs and cats), farm animals (e.g., horses, cows, goats, sheep, pigs) and experimental animals (e.g., mouse, rat, rabbit, guinea pig). In some cases, a mammal is a human. A mammal may be any age or at any stage of development (e.g., an adult, teen, child, infant, or a mammal in utero). A mammal may be male or female. A mammal can be a pregnant female. In some case, a subject may be a human. In some cases, a human may be more than about: I day to about 10 months old, from about 9 months to about 2.4 months old, from about 1 year to about 8 years old, from about 5 years to about 25 years old, from about 20 years to about 50 years old, from about 1 year old to about 130 years old or from about 30 years to about 100 years old. Humans can be more than about: 1, 2, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, or 120 years of age. Humans can be less than about: 1 , 2, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120 or 130 years of age.

Incorporation by Reference

[0085] All publications, patents, and patent applications mentioned in this specification are incorporated by reference in their entirety to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference in its entirety. In the event of a conflict between a term and a term in an incorporated reference, control. Methods of Guided Epigenetic Editing

Identification sf target sites for modifying a cellular state

[0086] Hie present disclosure provides methods for guided epigenetic editing using epigenetic maps. The methods described herein use epigenetic maps to identify' epigenetic editing target sites for modifying a target cell for a desired purpose or application. In some cases, the desired purpose or application is to modify a cellular state, such as a differentiation state or a state of disease. For example, it may be desired to modify a highly differentiated cell (e.g., an effector T- cell) to a less differentiated state (e.g., a naive T-cell, stem cell memory T cell, central memory T ceil or effector memory T cell). As another example, it may be desired to modify an aged or diseased cell to a younger, healthier cell. In some cases, editing specific sites of the epigenome of a cell can help achieve these desired modifications A particular cellular state or a particular cell type can have unique methylation markers or patterns associated with the cellular state or cell type. In some cases, a specific methylation marker can be a major contributor to a desired cellular state. Introducing the specific methylation marker to a cell in an undesired cellular state can change the cell into the desired cellular state. For example, a healthy liver hepatocyte may have a specific methylation marker or pattern that is different from a diseased liver hepatocyte. By editing a diseased liver hepatocyte to have the specific methylation pattern of a healthy liver hepatocyte, one can change the diseased liver hepatocyte into a healthy state liver hepatocyte.

Epigenetic Maps

[0087]

[0088] The methods described herein utilize epigenetic maps of cells of different cellular states and cell types to identify unique methylation markers and patterns that may be contributors to a desired cellular state.

[0089] In some embodiments, an epigenetic map may be represented by coordinates compared to a reference genome. In some embodiments, an epigenetic map may be represented graphically. An epigenetic map may be physically displayed, e.g., on a computer monitor.

[0090] The mapping information can be obtained from the sequence reads to the region. In some embodiments, sequence read abundance, i.e., the number of times a particular sequence or nucleotide is observed in a collection of sequence reads may be calculated. In some embodiments, the epigenetic map depicting peak signals of sequence reads, e.g., as determined using peak-calling tools, can be generated. The resultant epigenetic map can provide an analysis of the chromatin in the region of interest. In some embodiments, the sequence reads are analyzed computationally to produce a number of numerical outputs that are mapped to a representation

(e g,, a graphical representation) of a region of interest.

[0091] In some instances, an epigenetic map may depict one or more of the following: chromatin accessibility' along the region; DMA binding protein (e.g., transcription factor) occupancy for a site in the region, and/or chromatin states along the region. An epigenetic map may further represent tire global occupancy of a binding site for the DNA binding protein by, e.g , aggregating data for one DNA binding protein over a plurality of sites to which that protein binds. In some instances, the map can be annotated with sequence information, and information about the sequence (e.g., the positions of introns, exons, transcriptional start sites, promoters, enhancers, etc.) so that the epigenetic information can be viewed m context with the annotation.

[0092] In some embodiments, an epigenetic map represents global changes in the methylation of across tire entire genome of an organism, e.g., a human as well as changes in methylation of a plurality of different regions, e.g., coding sequences, mtergenic spacers, regulatory' regions, e.g., promoters, etc., of the entire genome, a portion of the genome or near or around or within a particular gene or genes. In some embodiments, an epigenetic map can represent the methylation level values of all CpG positions within entire genome of an organism, e.g,, a human. In some embodiments, an epigenetic map can represent the methylation level values of all CpG positions within a plurality of different regions, e.g., coding sequences, intergenic spacers, regulatory regions, e.g., promoters, etc., of the entire genome, a portion of tire genome or near or around or within a particular gene or genes.

[0093] In some embodiments, computationally implemented scripts or tools can be used to generate epigenetic/epigenomic maps. Exemplary scripts or tools that can be utilized include make homer _ucsc file, which can create a .bedGraph file which allows for genome-wide pileups of fragment counts; and homer bedgraph jo bigwig which can convert the bedGraph file to a bmary-compressed bigWig file, used by most genome browsera to visualize fragment coverage across the genome. The analysis can include generating a metric associated with particular elements of a gene. For example, such metrics can include accessibility over a promoter of an annotated gene, or over the coding region of an annotated gene. In some embodiments, annotation and generation of metric can be used for further downstream analysis, e.g., comparing epigenetic profiles, clustering and/or biological pathway analysis to produce a differential epigenetic map. [0094] In some embodiments, an epigenetic map may be a differential epigenetic map. In some embodiments, a differential epigenetics map provides a representation of epigenetic modifications that have been made to across a plurality of different regions, e.g., coding sequences, intergenic spacers, regulatory regions, e.g., promoters, etc., of the entire genome, a portion of the genome or near or around or within a particular gene or genes compared to a reference. In some embodiments a differential epigenetics map provides a comparative representation of a first epigenetic map taken at a point in time and a second epigenetic map generated at another point of time to determine what changes have taken place in a specific time period. In some embodiments a differential epigenetics map provides a comparative representation of a first epigenetic map taken obtained before epigenetic modifications that have been made to across a plurality of different regions, e.g., coding sequences, intergenic spacers, regulators' regions, e.g., promoters, etc., of the entire genome, a portion of the genome or near or around or within a particular gene or genes and a second epigenetic map obtained after epigenetic modifications that have been made to across a plurality of different regions, e.g., coding sequences, intergenic spacers, regulatory regions, e g., promoters, etc., of the entire genome, a portion of the genome or near or around or within a particular gene or genes. In some embodiments, a differential epigenetics map provides a representation of epigenetic differences between a plurality of different regions, e.g., coding sequences, intergenic spacers, regulatory regions, e.g., promoters, etc., of the entire genome, a portion of the genome or near or around or within a particular gene or genes located within a first cell and a plurality of different regions, e.g., coding sequences, intergenic spacers, regulatory regions, e.g., promoters, etc., of tire entire genome, a portion of the genome or near or around or within a particular gene or genes located within a second cell. In some embodiments, the first cell and the second cell are of same type. In some embodiments, the first cell and the second cell are of different type. In some embodiments, the first cell and the second cell are of same age . In some embodiments, tire first cell and the second cell are of different age, e.g., the first cell is an old cell, and the second cell is a young cell of the same type or vice versa. In some embodiments, the first cell and the second cell are in same cellular state. In some embodiments, the first cell and the second cell are m the different cellular state, e.g., the first cell is in a healthy state and the second cell is in a diseased state or vice versa.

[0095] In some embodiments, the epigenetic map can provide information regarding active regulators' regions and/or the transcription factors that are bound to the regulatory regions. Methods using epigenetic maps

[0096] In some cases, the present disclosure provides methods of using epigenetic maps for identifying a target genomic site for epigenetic editing. In some cases, tire method includes preparing a differential epigenetic map. The differential epigenetic map may be used to identify a target genomic site.

[0097] In one aspect, the present disclosure provides a method of identifying a target genomic site for epigenetic editing. The method may include providing a first epigenetic map of a target ceil in an initial cellular state. The first epigenetic map may provide a methylation state of each genomic site of a plurality of genomic sites in the target cell. The method may include providing a second epigenetic map of a desired cell in a desired cellular state. The second epigenetic map may provide a methylation state of each genomic site of the plurality of genomic sites in the desired cell. For example, the epigenetic map can be a heatmap, as described elsewhere herein.

[0098] In some cases, the initial cellular state is a diseased state, and the desired cellular state is a healthier state relative to the initial cellular state. In some cases, the initial cellular state is an exhausted state, and the desired cellular state is a rejuvenated state relative to the initial cellular state. In some cases, the desired cellular state is a younger state relative to the initial cellular state. In some cases, initial cellular state is differentiated state, and the desired cellular state is less differentiated state relative to the initial cellular state. In some cases, the initial cellular state is differentiated state, and the desired cellular state is a substantially undifferentiated cellular state. In some cases, the initial cellular state is differentiated state, and the desired cellular state is differently differentiated cellular state (e.g., a different branch of differentiation relative to the initial cellular state).

[0099] In some cases, the desired cellular state is a less differentiated state relative to the initial cellular state. In some cases, the desired cellular state comprises a higher level of sternness relative to the desired cellular state. The desired cell in the desired cellular state may comprise a desired cell function or a desired phenotype. In some cases, the target cell and the desired cell are of the same cell type. In some cases, the target cell and the desired cell are of different cell types. In some cases, the target cell and the desired cell are from the same individual. In some cases, the target cell and the desired cell are from different individuals. In some cases, the plurality of genomic sites comprises a whole genome of the target cell or the desired cell. [0100] In some embodiments, the method includes comparing the first epigenetic map and the second epigenetic map. In some cases, comparing the first epigenetic map and the second epigenetic map detects a first differential. For example, the differential can be a genomic site or region that is unmethylated in the first epigenetic map and methylated in the second epigenetic map. In some cases, the method further comprises (d) identifying a target genomic site in the plurality of genomic sites using the first differential. In some cases, the target genomic site is in an initial methylation state in tire target cell, and the target genomic site is in a desired methylation state in the desired cell, wherein the initial methylation state and the desired methylation state are different methylation states. In some cases, the initial methylation state is an unmethylated state and the desired methylation state is a methylated state. In other cases, die initial methylation state is a methylated state, and the desired methylation state is an unmethylated state. In some cases, the initial methylation state of the target genomic site is a contributor to the initial cellular state of the target cell. In some cases, the desired methylation state of tire target genomic site is a contributor to the desired cellular state of the desired ceil. For example, an unmethylated state of a specific site in a gene promoter can result in expression of a specific gene in a diseased cell, and a methylated state of the same site in the gene promoter can silence expression of that gene in a healthy cell. By comparing epigenetic maps of the diseased cell and the healthy cell, one can identify the specific site in the gene promoter as one that is differentially methylated in the two epigenetic maps and select it as a target genomic site for epigenetic editing.

[0101] In some cases, the method further comprises cross-referencing with an additional epigenetic map to identify the target genomic site. For example, when selecting a target genomic site for epigenetic editing, such as for the purpose of modifying a cellular state, it may be desirable to control the effects of epigenetic editing to specific target cell types and minimize modifications to off-target cell types/tissues. In some cases, the method further comprises crossreferencing with an epigenetic map of an off-target cell, which can provide information about how to minimize the risk or level of modifications to the off-target cell. For example, specific genomic sites may be unmethylated in the target cell (where an edit is desired) and methylated in an off-target cell (where an edit is undesired). Targeting this specific genomic site for methylation may be favorable by methylating the genomic site in the target cell and producing no change to the genomic site in the off-target cell, since it is already methylated.

[0102] In some cases, the method for identifying the target genomic site further comprises providing a third epigenetic map of an off-target cell, wherein the third epigenetic map provides a methylation state of each genomic site of the plurality of genomic sites in the off-target cell. In some cases, the target cell and the off-target cell are of different ceil types. In some cases, the target cell and the off-target cell are from different tissues. For example, in one application, a liver hepatocyte may be selected as a target cell. A pancreatic acinar cell or a gastric epithelial cell may be considered an off-target cell.

[0103] In some cases, (d) identifying the target genomic site in the plurality of genomic sites further comprises detecting a methylation state of the target genomic site in the off-target cell, wherein the methylation state of the target genomic site in the off-target cell and the desired methylation state are the same methylation state. For example, a first differential between a first epigenetic map of a target diseased liver hepatocyte and a second epigenetic map of a healthy liver hepatocyte may identify a specific site in a gene promoter that is in an unmethylated state in the diseased state and in a desired methylated state in the healthy state. Cross-referencing with a third epigenetic map of an off-target pancreatic acinar cell may identify that this promoter site is also in the desired methylated state in the off-target pancreatic acinar cell. This promoter site may be selected as a favorable target site for methylation, which since methylation would modify the diseased liver hepatocyte but would produce no change to this promoter site in the off-target pancreatic acinar cell.

[0104] In some cases, the method further comprises comparing the third epigenetic map with a fourth epigenetic map of a cell m the initial cellular state, thereby detecting a second differential and using the second differential to identity' the target genomic site in the plurality of genomic sites. The fourth epigenetic map may be the same map as the first epigenetic map. For example, the third epigenetic map of the off-target pancreatic acinar cell can be compared with a fourth epigenetic map of the target diseased liver hepatocyte and the differential between the two maps may guide the identification or selection of the target genomic site for epigenetic editing. In some cases, the first differential between the first epigenetic map and the second epigenetic map first identifies a target region that is differentially methylated in the initial cellular state and the desired cellular state. In some cases, the second differential between the third epigenetic map and the fourth epigenetic map identifies the target site within the target region that is favorable for epigenetic editing. In some cases, the first differential between the first epigenetic map and the second epigenetic map first identifies a plurality’ of target sites that is differentially methylated in the initial cellular state and the desired cellular state.

[0105] In some cases, the second differential between the third epigenetic map and the fourth epigenetic map identifies a target site within the plurality of target sites that is favorable for epigenetic editing. In some cases, the target site identified from the second differential is favorable given that the target site is already’ in the desired methylation state in the off-target cell and targeting this site produces a lower risk or level of undesired modifications to the off-target. cell. Utilizing both the first differential and the second differential can narrow the search/selection space for target sites for epigenetic editing.

[0106] In some cases, the method further comprises generating the first, second, third, or fourth epigenetic map, or a combination thereof.

[0107] In some cases, the method for identifying the target genomic site farther comprises providing a plurality of epigenetic maps of a plurality of off-target, cells, wherein the plurality of epigenetic maps provides a methylation state of each genomic site of the plurality of genomic sites m each off-target cell in the plurality of off-target cells. In some cases, the plurality of epigenetic maps comprises 2, 3, 4, 5, 6, 7, 8, 9, or 10 epigenetic maps In some cases, the plurality of epigenetic maps comprises at least 2, at. least. 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 epigenetic maps. In some cases, the method further comprises providing an initial epigenetic map of a target cell in the initial cellular state, wherein the initial epigenetic map provides a methylation state of each genomic site of the plurality of genomic sites in the target cell. In some cases, the method further comprises comparing the initial epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells, thereby detecting a third differential between the third epigenetic map and the plurality’ of epigenetic maps of the plurality of off-target cells. In some cases, (d) identifying the target genomic site further comprises using the third differential to identify the target genomic site in the plurality of genomic sites, wherein the target genomic site is in the desired methylation state in each off-target cell in the plurality’ of off-target cells. In some cases, the first epigenetic map and the initial epigenetic map is the same epigenetic map.

[0108] In some cases, the target cell is of a first cell type, and each off-target cell of the plurality of off-target cells is of a cell type that is different from the first cell type. In some cases, the plurality of off-target cells comprises at least two off-target cells of different cell types. The target ceil can be from a target tissue. The plurality of off-target cells can be from an off-target tissues. In some cases, the target tissue and the off-target tissues are different tissues. For example, in one application, a liver hepatocyte may be selected as a target cell. The plurality of off-target cells can comprise a pancreatic acinar cell and/or a gastric epithelial cell ,

[0109] In some cases, the method further comprises generating the initial epigenetic map, any one of the plurality’ of epigenetic maps, or a combination thereof. Genomic editing and modification

[Oil 0] In some cases, the method further comprises modifying one or more target genomic sites. In some cases, the method comprises providing a target cell in an initial cellular state, wherein the provided target cell comprises one or more target genomic sites in the initial methylation state. In some cases, the method further comprises contacting the provided target cell with an epigenetic effector, as described elsewhere herein. In some cases, the epigenetic effector modifies the target genomic site from the initial methylation state to the desired methylation state, thereby producing a modified ceil, wherein the modified cell is in a modified cellular state. For example, the target genomic site or sites can be unmethylated in provided target cell and the epigenetic effector can methylate the target genomic site to produce the modified cell. In another example, the target genomic site or sites can be methylated in provided target cell and the epigenetic effector can demethylate the target genomic site to produce the modified cell.

[0111] As discussed in more detail below, the epigenetic effector may be specific for a target genomic site or can selectively modify a target genomic site, as described elsewhere herein. The epigenetic effector may, for example, comprise a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a Zinc finger domain, or a TAL domain, as described elsewhere herein For example, the epigenetic effector can comprise an effector moiety, a CRISPR/Cas domain, and a guide RNA complexed with the CRISPR/Cas domain, where in the guide RhJA selectively targets the target genomic site.

Modified or edited cells

[0112] In some cases, the method produces a modified cellular state that is functionally more similar to the desired cellular state than the initial cellular state is to the desired cellular state. For example, introducing an epigenetic edit in an initial diseased cell can change the diseased cell to be functionally more similar to a desired healthy state. As another example, introducing an epigenetic edit in an initial highly differentiated cell can change the differentiation state of the cell to a less differentiated state. In some cases, the method further comprises profiling a function of the modified cell, for example, using a functional assay.

[0113] In some cases, the method produces a modified cell that exhibits a modified phenotype that is different from an initial phenotype of the target cell. A phenotype of the cell can be expression of a cell marker, a cell size, or cellular morphology. In some cases, the modified phenotype is more similar to a desired phenotype of the desired cell in the desired cellular state than the initial phenotype is to the desired phenotype. For example, if a naive T-cell is the desired cellular state, introducing an epigenetic edit in an effector T-cell cell can result in the cell exhibiting a desired cell marker characteristic of naive T-cells. In some cases, the method further comprises profiling a phenotype of the modified cell. For example, expression of a cellular marker can be profiled using antibodies against the cellular marker and flow cytometry analysis. The size or morphology of modified cells can be profiled by imaging.

[0114] In some cases, modifying the target genomic site from the initial methylation state to the desired methylation state turns on expression of a gene. In some cases, modifying the target genomic site from the initial methylation state to the desired methylation state turns off' expression of a gene. For example, methylating a promoter site can turn off expression of a gene. On the other hand, demethylating a promoter site can turn on expression of a gene. In some cases, methylating an internal region of a gene can turn on or turn off expression of a gene. In some cases, demethylating an internal region of a gene can turn on or turn off expression of a gene. In some cases, methylating an activator or repressor gene can turn on or turn off expression of a second gene. In some cases, demethylating an activator or repressor gene can turn on or turn off' expression of a second gene.

[0115] In some cases, the method further comprises epigenetic profiling the modified cell to examine the effects of the epigenetic effector. Epigenetic profiling of the cell after modification can be used to further refine the epigenetic editing system. For example, for a CRISPR based epigenetic editing system, one or more guide RNAs can be screened for efficacy of epigenetic editing of fire target site. The one or more guide RNAs can also be screened for off-target edits at off-target genomic sites.

[0116] In some cases, the method further comprises providing a fifth epigenetic map of the modified cell, wherein the fifth epigenetic map provides a methylation state of each genomic site of a plurality of genomic sites in the modified cell. In some cases, the method further comprises comparing the fifth epigenetic map with a sixth epigenetic map, wherein the sixth epigenetic map is generated from a cell that is not treated with the epigenetic effector, thereby generating a fourth differential. In some cases, the method further comprises using the fourth differential to detect an off-target modification. The off-target modification can comprise a changed methylation state at an off-target genomic site in the modified cell. In some cases, the changed methylation state is different from an initial methylation state of the off-target genomic site in the initial target cell. In some cases, the first epigenetic map and the fifth epigenetic map are the same epigenetic map. Parallel, multiple epigenetic editing and modification

[0117] The methods described herein allow for parallel, multiple epigenetic editing of targets (e.g., CpG sites and/or histones) and associated modifications (e.g., methylation, demethylation, acetylation and/or deacetylation) for the epigenetic markers. In some embodiments, the editing of targets (e.g., gene targets, CpG sites, histones) can comprise orthogonal Cas constructs. In some embodiments, the editing of targets (e.g., gene targets, CpG sites, histones) can be bidirectional epigenetic editing (e.g., gene activation and repression). In some embodiments, the editing of targets (e.g., gene targets, CpG sites, histones) can be unidirectional epigenetic editing. In some embodiments, the method described herein allow of one, two, three, four, five, six, seven, eight, nine, ten, 11, 12, 13, 14, 15, or more epigenetic editing of targets (e.g., gene targets, CpG sites, histones) and associated modifications (e.g., methylation, demethylation, acetylation, and/or deacetylation) for the epigenetic markers. The desired edits may be selected computationally by leveraging previous experimental data and/or other available datasets (e.g., publicly available data sets). After editing, the modified cells may be profiled to evaluate multi- omic and functional effects of the epigenetic modifications. The resulting profiling data can be fed back into the computational approach to classify the results and inform prediction for the next round of edits. A method of selecting a modification for one or more epigenetic markers can include obtaining a target list comprising epigenetic markers and an associated modification for each epigenetic marker, wherein the target list is associated with a desired cellular state; modifying at least a portion of the epigenetic markers in a cell according to the target list to generate a modified cell; profiling the modified cell to determine a cellular state profile for the modified cell; and selecting, based on the cellular state profile for the modified cell, an updated target list comprising updated epigenetic markers and an associated modification for each updated epigenetic marker. The cellular state may be, for example, a biological age or a disease state. The target list may be based at least in part on epigenetic biomarkers associated with aging or a disease state.

[0118] The cellular state profile for the modified cell may also be compared to a desired cellular state profile to determine a differential between the cellular state profile and the desired state profile. The target list may be updated, for example, based on this differential.

[0119] The modified cell may be profiled to obtain a cellular profile of the modified cell

Exemplary profiling techniques may include, for example, epigenetic profiling, transcriptomic profiling, proteomic profiling, cell imaging, determining a cellular state, a functional assay, multi-onrics profiling, metabolic profiling, flow cytometry', whole genome bisulfite sequencing, single-cell sequencing, ATAC sequencing, single-cell ATAC sequencing, a methylation microarray profiling, methylation sequencing, single-cell methylation sequencing, single-cell RNA sequencing, or nucleic acid sequencing. In some implementations, the modified cell is profiled using single-cell sequencing, methylation sequencing, or single-cell methylation sequencing.

[0120] Epigenetic markers that may be modified include one or more CpG sites and/or one or more histones Modifications can include, for example, methylation or demethylation (e.g., for

CpG sites and/or histones), or acetylation or deacetylation (e.g., for histones).

Exemplary processes for selecting a modification

[0121 J FIGS. 2 and 3 show exemplary processes for selecting a modification for one or more epigenetic markers, any one of which may be performed iteratively. For example, the method may further include modifying at least a portion of the epigenetic markers from the updated target list in a second cell to generate a second modified cell. The second modified cell may be profiled to determine a cellular state profile for the second modified cell. Based on the cellular state profile for the second modified cell, a second updated target list, comprising second updated epigenetic markers and an associated modification for each second updated epigenetic marker, may be selected.

[0122] FIG. 2 depicts an exemplary' method of parallel multi-site epigenetic editing and profiling that may be performed iteratively. The process includes identifying a target list that may comprise CpG, histone, methylation, demethylation, acetylation and deacetylation sites across a plurality of genomic sites, followed by constructing a vector comprising an inducible multi-target effector molecule. The vector may then be parallelly delivered to the targets located across the plurality of genomic sites. The time course may be multiplexed to generation a multi- omic IHC functional profile.

[0123] FIG. 3 depicts an exemplary method for modifying one or more epigenetic markers, any one of which may be performed iteratively. The process includes using Data/ Al core to identify a list of CpG targets and effector types, vectors comprising the selected effector and specific sgRNAs were designed and viral inducible Sa/pdCas9-fusion molecules are constructed and are delivered to selected samples via different delivery methods such as transduction (with chemical and fluorophore selection), induction with helper vector, electroporation ( with fluoropbore selection) for modifying samples. Modified samples are contacted with barcoded oligos to enable pooled sequencing by cohort and profiling is generated by various methods such as scRNA-seq, scATAC-seq, WGBS, and/or flow cytometry. Blocking modifications at off-target genomic sites

[0124] In another aspect, the present disclosure provides a method of blocking a modification at an off-target genomic site. An off-target genomic site can be a genomic site that is unintentionally targeted or a site where a modification is undesired. In some cases, an off-target genomic site comprises an epigenetic cellular identity marker. An epigenetic cellular identity marker can be correlated with the identity (i.e., cellular differentiation state) of cell, as described elsewhere herein. In some cases, loss of the epigenetic cellular identity markers causes the cell to lose its cellular identity. Cell identity can be dictated by the specific set of genes expressed and proteins produced in the cell that are activated by the epigenetic state of the cell to enable its unique function. Altering the epigenetic state of the epigenetic cellular identity' markers can cause a loss of cellular state identity. To preserve the identity of the cell, die methods described herein can preserve the epigenetic state of the one or more epigenetic cellular identity markers, e.g., through blocking a modification at an off-target genomic site comprising a cellular identity marker

[0125] To limit off target epigenetic modification, and more particularly to preserve selected epigenetic cellular identity markers, the cell can be contacted with a blocking reagent that specifically binds to one or more selected epigenetic cellular identity markers. By specifically binding a selected epigenetic marker, the modification enzymes are sterically prevented from modifying the protected marker. Thus, the cellular identity of the cell may be preserved when epigenetic cellular identity markers are protected by the blocking reagent.

[0126] Hie blocking reagent can include a nucleic acid binding moiety that specifically binds to an off-target genomic site, e g., an epigenetic cellular identity marker. The nucleic acid binding moiety may specifically bind based on the nucleic acid sequence at the epigenetic locus (that is, the nucleic acid binding moiety can bind to the locus irrespective of the status of the epigenetic marker). Tire nucleic acid binding moiety can be a nuclease-deficient targeted nucleic acid binding moiety. The blocking reagent may include a CRISPR-based editing platform, which can include a dead endonuclease domain (e.g., a dead Cas9) domain. Hie CRISPR-based editing platform of the blocking reagent may further include one or more single guide RNA (sgRNA) molecules that targets one or more epigenetic cellular identity markers, e.g., a blocking guide RNA. A blocking guide RNA can comprise a nucleic acid sequence that is complementary' to the off-target genomic site identified by any of the methods described herein. In some cases, the blocking guide RNA is configured to bind to a CRISPR/Cas domain, wherein the CRISPR/Cas domain - blocking guide RNA complex binds to the off-target genomic site, lire CRISPR/Cas domain can be catalytically inactive. In another example, the nuclease-deficient targeted DN A binding domain comprises a transcription activator-like effector (TALE) nucleic acid binding moiety or a zinc finger nucleic acid binding moiety that specifically bind the off-target genomic site, e.g., an epigenetic cellular identity marker. In some cases, the CRISPR/Cas domain - blocking guide RNA complex, the T ALE nucleic acid binding moiety, or the zinc finger nucleic acid binding moiety prevents a modification, e.g., methylation, demethylation, acetylation, or deacetylation, from occurring at the off-target genomic site, hi some cases, the nucleic acid binding moiety used with the blocking reagent is not fused or bound to an epigenetic effector.

Analysis of modifications io off-target genomic sites

[0127] In another aspect, the present disclosure provides a method of analyzing modifications to off-target genomic sites and/or screening an epigenetic effector or epigenetic editing system for off-target modifications. In some cases, the method comprises introducing an epigenetic effector or epigenetic editing system to a first cell, wherein the epigenetic effector or epigenetic editing system modifies the first cell, producing a modified cell. In some cases, the method further comprises profiling the modified cell using epigenetic profiling to generate a first epigenetic map of the modified cell. In some cases, the method further comprises comparing the first epigenetic map and a second epigenetic map of a second cell that has not been modified by the epigenetic effector or epigenetic editing system. For example, the second cell can be a control ceil that is in the same cellular state and/or of the same cell tope as the first ceil. In some cases, the control cell may lack one component of the epigenetic effector or epigenetic editing system. For example, the first cell may comprise a CRISPR/Cas epigenetic effector and a specific guide RNA, while the control ceil may comprise the CRISPR/Cas epigenetic effector but not the specific guide RNA. The method may comprise screening a guide RNA based on the number and/or location of off-target modifications associated with the guide RN A. In some cases, comparing the first epigenetic map and the second epigenetic map generates a differential, and the method further comprises using the differential to identify an off-target edited site. The off- target edited site can be a site that is unintentionally targeted or a site where an edit is undesired.

[0128] In some cases, the epigenetic effector or epigenetic editing system comprises a CRISPR/Cas epigenetic effector and a first guide RNA to a first cell, wherein the first guide RNA is configured to bind to a first CRISPR/Cas domain in the CRISPR/Cas epigenetic effector and comprises a nucleic acid sequence complementary to a target genomic site. In some cases, the CRISPR/Cas epigenetic effector introduces an on-target epigenetic editto the target genomic site and an off-target epigenetic edit to an off-target genomic site, and the differential between the first epigenetic map and the second epigenetic map identifies the off-target genomic site. Reprogramming a cell

[0129] In another aspect, the present disclosure provides a method of reprogramming a cell, which may in some cases be a partial reprogramming. A cell can be reprogrammed, e.g., partially reprogrammed, by contacting the cell with a blocking reagent that specifically binds to an off-target genomic site, e.g., a site that comprises an epigenetic cellular identity marker or a site where it is unde sired to introduce a modification; and contacting the cell with an epigenetic effector described elsewhere herein that modifies a target site. In some cases, the blocking reagent inhibits modification of the off-target genomic site. In some cases, the cell is simultaneously contacted with the blocking reagent and the epigenetic effector such that the blocking reagent inhibits the epigenetic effector from modifying the off-target site. In other cases, the cell is contacted with the blocking reagent, wherein the blocking reagents binds to an off-target genomic site, and then subsequently contacted with an epigenetic effector, wherein the epigenetic effector introduces a modification at a target site. The method may further include culturing the cell after contacting the cell with the blocking reagent and the epigenetic effector.

[0130] For example, the blocking reagent can comprise a first CRISPR/Cas domain that is deficient in nuclease activity and a first guide RNA, e.g , a blocking guide RNA, that binds to the off-target genomic site. The first guide RNA can hybridize to a sequence at the off-target genomic site and recruit the first CRISPR/Cas domain to the off-target genomic site, thereby blocking the off-target genomic site from epigenetic editing. In some cases, the blocking reagent comprises a TALE domain or a zinc finger domain that specifically binds to the off- target genomic site. Tire epigenetic effector can comprise a second CRISPR/Cas domain and a second guide RNA, a TALE domain, or a zinc finger domain that specifically binds to the target site, lire epigenetic effector can comprise an effector moiety as described elsewhere herein that introduces an epigenetic modification to the target site In some cases, the blocking reagent comprises a first CRISPR/Cas domain, and the epigenetic effector comprises a second CRISPR/Cas domain, wherein the first CRISPR/Cas domain and the second CRISPR/Cas domain do not cross-react. Examples of orthogonal CRISPR/Cas domains that do not crossreact are described elsewhere herein.

[0131] The method may further include identifying and/or selecting the off-target genomic site and/or selecting the target site for guide epigenetic editing using one or more methods described elsewhere herein. Identification and/selection of the off-target genomic site or the target site may be, for example, based a known association between the epigenetic marker and a cellular identity, disease state, and/or biological age. As further described herein. identification and/selection may be based on the epigenetic markers of a desired cellular state profile, an undesired cellular state profile, and/or a differential profile. In some embodiments, identification and/selection may be based on a differential detected between two or more epigenetic maps, as described elsewhere herein.

[0132] In some embodiments, the method further includes selecting one or more off-target genomic sites; selecting one or more target sites for guided epigenetic editing, wherein the one or more selected target sites excludes the one or more off-target genomic sites; and contacting the cell with one or more epigenetic effectors targeted to the one or more selected target sites. The method may further include contacting the cell with a blocking reagent that specifically binds to the one or more selected off-target genomic sites, wherein the blocking reagent inhibits modification of the selected one or more off-target genomic sites.

[0133] The methods described herein allow for parallel, multiple epigenetic editing of targets (e.g., CpG sites and/or histones) and associated modifications (e.g., methylation, demethylation, acetylation and/or deacetylation) for the epigenetic markers, and/or the preservation of multiple epigenetic makers (e.g., cellular identity markers) at off-target genomic sites. The desired edits and/or targeted preservations may be selected computationally by leveraging previous experimental data and/or other available datasets (e.g , publicly available data sets). The selection process may be iterative. For example, after initial reprogramming, the modified cells may be profiled to evaluate nmlti-omic and functional effects of the epigenetic modifications. The resulting profiling data be fed back into the computational approach to classify the results and inform prediction for the next round of edits.

[0134] Methods of partially reprograming a cell may be performed in vivo (e.g., in a subject), ex vivo (e.g., outside of a subject), or in vitro (e.g , using a cell line). For example, the one or more epigenetic effectors and/or blocking reagents may be administered to an individual. The epigenetic effectors and/or blocking reagents may be administered, for example, using a vector (such as a viral vector), which allows for expression of the epigenetic effectors and/or blocking reagents in the cell, which causes the partial reprogramming. In some implementations, the vector may be targeted to a particular cell type. In some embodiments, the method may be performed ex vivo, for example by obtaining a cell (or population of cells) from a subject. In some embodiments, the reprogrammed cell taking from the subject may then be readministered to the subject.

[0135] In some embodiments, the method may be used to reprogram an immune cell. In some embodiments, the method may be used to reprogram an immune cell ex vivo. In some embodiments, the method may be used to reprogram an immune cell into immunosenescence, which can, for example, be applied in cases of autoimmunity or organ rejection. In some embodiments, the method may be used to reprogram an immune cell out of immunosenescence, which can, for example, be applied in cases for oncology or infection. In some embodiments, the method may be used to reprogram an immune cell for adoptive cell therapy. After reprogramming the cell, the reprogrammed ceil may be, in some embodiments, administered to a subject, which may be the same subject or a different subject from which the original cell was obtained.

[0136] In some embodiments, the method may’ be used to reprogram a ceil in vivo. Such partial reprogramming may be used to treat, for example, fibrosis in lung, liver, kidney, heart, or neurodegenerative disease, or type 2 diabetes. In some embodiments, the method may be used in reprogramming a pancreatic beta cell in vivo

[0137] FIG, 34 A shows an exemplary' method for reprogramming a cell. Although the figure is shown representing steps in a particular order, the illustrated steps may be performed in any suitable order. As shown in FIG. 34A, at 102, one or more epigenetic cellular identity' markers are selected. The one or more epigenetic cellular identity markers may be associated (i.e., con-elated) with the identity of the cell subject to the partial reprogramming method. At 104, one or more target epigenetic markers are selected. The one or more target epigenetic markers are those epigenetic markers intended to be modified, for example an epigenetic marker associated with biological aging or a disease state. At 106, a blocking reagent that specifically binds to the one or more selected epigenetic cellular identity markers is contacted with the cell. In some embodiments, the blocking reagent is added to a cellular medium containing the cell. In some embodiments, the blocking reagent is expressed in the cell, for example using a heterologous vector controlled by an inducible promoter. Exemplary forms of the blocking agent may include mRNA, integrative DNA, non-integrative DNA, and/or proteins. Exemplary methods of introducing the blocking reagent into the cell include (1) passive uptake through the media, (2) transfection, (3) transduction (e.g., using various viruses, lentivirus, AAV, etc.), (4) activation of endogenous genes, and (5) lipid nanoparticles. For example, dCAS9 with guide RNAs may be used for specific cell identity markers that may be introduced into the cell through transduction using AAV2. In another example, dCAS9 protein and guide RNAs are introduced into the cell directly through electroporation. At 108, tire cell is contacted with one or more targeted cellular reprogramming factors to modify the target epigenetic markers. The one or more cellular reprogramming factors may be introduced in the same manner or different manner as the blocking agent. For example, in some embodiments, the one or more cellular reprogramming factors are added to a cellular medium containing the cell. In some embodiments, the one or more cellular reprogramming factors are expressed in the cell, for example using a heterologous vector controlled an inducible promoter. Exemplary methods of introducing the cellular reprogramming factors into the cell include (1) passive uptake through the media, (2) transfection, (3) transduction (e.g., using various viruses, lentivirus, AAV, etc.), (4) activation of endogenous genes, and (5) lipid nanoparticles. Although FIG. LA shows step 106 occurring prior to step 108, these steps may occur in either order or simultaneously. At optional step 110, the ceil is cultured in the presence of the blocking reagent and the one or more modification enzymes, which allows the modification enzymes to modify the targeted epigenetic marker while the blocking regent protects the one or more selected epigenetic cellular identity markers. In some embodiments, in an alternative to step 110, the method may occur in vivo. [0057] FIG. 34B shows an exemplary' method for reprogramming a cell, which includes at least rejuvenating the cell. Although the figure is shown representing steps in a particular order, the illustrated steps may be performed in any suitable order. As shown in FIG. 34B, at 112, one or more epigenetic cellular identity markers are selected. The one or more epigenetic cellular identity markers may be associated (i.e., correlated) with the identity of die cell subject to the partial reprogramming method. At 114, one or more target epigenetic markers are selected. The one or more target epigenetic markers are those epigenetic markers intended to be modified, for example an epigenetic marker associated with biological aging or a disease state. At 1 16 the cell is at least rejuvenated, for example by contacting the cell with one or more non-targeted cellular reprogramming factors (e.g., one or more transcription factors, such as one or more Yamanaka factors). Contacting the cell with the one or more non-targeted cellular reprogramming factors can include, for example, adding the one or more non-targeted cellular reprogramming factors to the cell medium containing the cell. In another example, contacting the cell with the one or more non-targeted cellular reprogramming factors can include expressing the one or more transcription factors in the cell, for example using a heterologous vector controlled an inducible promoter. Exemplary methods of introducing the non-targeted cellular reprogramming factors into the cell include (1 ) passive uptake through the media, (2) transfection, (3) transduction (e.g., using various viruses, lentivirus, AAV, etc.), (4) activation of endogenous genes, and (5) lipid nanoparticles. At 118, a blocking reagent that specifically binds to the one or more selected epigenetic cellular identity markers is contacted with the cell In some embodiments, the blocking reagent is added to a cellular medium containing the cell. In some embodiments, the blocking reagent is expressed in the cell, for example using a heterologous vector controlled by an inducible promoter. Exemplary forms of the blocking agent may include mRNA, integrative DNA, non-integrative DNA, and/or proteins. Exemplary methods of introducing the blocking reagent into the cell include (1) passive uptake through the media, (2) transfection, (3) transduction (e.g., using various viruses, lentivirus, A AV, etc.), (4) activation of endogenous genes, and (5) lipid nanoparticles. For example, dCAS9 with guide RNAs may be used for specific cell identity markers that may be introduced into the cell through transduction using AAV2. In another example, dCAS9 protein and guide RNAs are introduced into the cell directly through electroporation. At 120, the cell is contacted with one or more targeted cellular reprogramming factors to modify the target epigenetic markers. In some embodiments, the one or more modification enzymes or fragments are added to a cellular medium containing tire cell. In some embodiments, the one or more modification enzymes or fragments are expressed in the cell, for example using a heterologous vector controlled by an inducible promoter. Exemplary methods of introducing the targeted cellular reprogramming factors into the cell include (1) passive uptake through the media, (2) transfection, (3) transduction (e.g., using various viruses, lentivirus, AAV, etc.), (4) activation of endogenous genes, and (5) lipid nanoparticles. Although FIG. 34B shows step 116 occurring prior to step 118, and step 118 occurring prior to step 120, these steps may occur in either order or simultaneously. At optional 122, the cell is cultured in the presence of the blocking reagent and the one or more modification enzymes, which allows the modification enzymes to modify the targeted epigenetic marker while the blocking regent protects the one or more selected epigenetic cellular identity markers. In some embodiments, in an alternative to step 122, the method may occur in vivo.

Minimizing modifications to an off-target cell/tissue

[0138] When selecting a target genomic site for epigenetic editing, such as for the purpose of modifying a cellular state, it may be desirable to control the effects of epigenetic editing to specific target cell types and minimize modifications to off-target cell types/tissues. The present disclosure provides methods of using epigenetic maps to identify target genomic sites for epigenetic editing a target cell that can minimize the risk or level of modifications in an off- target cell or tissue. For example, specific genomic sites may be unmethylated in the target cell and methylated in an off-target cell. Targeting this specific genomic site tor methylation would produce no change to the genomic site in the off-target cell, since it is already methylated. The methods described herein may be useful to narrow' or remove the search space for target epigenetic sites for selective editing.

[0139] In an aspect, the present disclosure provides a identifying a target genomic site for epigenetic editing, comprising: (a) providing a target cellular epigenetic map of a target cell, wherein the target cellular epigenetic map provides a methylation state of each genomic site of a plurality of genomic sites in the target cell. In some cases, the method further comprises (b) providing an off-target cellular epigenetic map of an off-target cell, wherein the off-target cellular epigenetic map provides a methylation state of each genomic site of a plurality of genomic sites in tlie off-target ceil. In some cases, the target cell is of a first cell type, and tlie off-target cell is of a second cell type, wherein the first cell type and the second cell type are different cell types. In some cases, the target cell is from a target tissue and the off-target cell is from an off-target tissue, wherein the target tissue and tlie off-target tissue are different tissues. For example, in one application, a liver hepatocyte may be selected as a target cell. A pancreatic acinar cell or agastric epithelial cell may be considered an off-target cell.

[0140] In some cases, the method farther comprises (c) comparing the target cellular epigenetic map and the off-target cellular epigenetic map, thereby detecting a differential. In some cases, tlie method further comprises (d) using the differential to identify a target genomic site in the plurality of genomic sites, wherein (i) the target genomic site is a first methylation state m the target cell, and (ii) the target genomic site is in a second methylation state in the off-target cell, wherein the first methylation state and the second methylation state are different methylation states. For example, a target cellular epigenetic map of a target diseased liver hepatocyte may be compared with an off-target cellular epigenetic map of a healthy pancreatic acinar cell. This comparison may reveal a promoter site that is unmethylated in the target diseased liver hepatocyte and that is methylated in the off-target healthy pancreatic acinar cell. In this example, tlie promoter site may be identified as a favorable epigenetic editing site for methylation, since a targeted epigenetic effector comprising a methylase would modify this site in the target diseased liver hepatocyte but would produce no change to this site in the off-target healthy pancreatic acinar cell, since it is already methylated.

[0141] In some cases, the method further comprises generating tlie target cellular epigenetic map. In some cases, the method farther comprises generating the off-target cellular epigenetic map.

[0142] In some cases, the method comprises providing a plurality of off-target cellular epigenetic maps of a plurality of off-target cells, wherein the plurality of off-target cellular epigenetic maps provides a methylation state of each genomic site of the plurality of genomic sites in each off-target cell in tlie plurality of off-target cells. In some cases, the target cell is of a first cell type, and each off-target cell of the plurality⁷ of off-target cells is of a cell type that is different from the first cell type. In some cases, the plurality of off-target cells comprises at least two off-target cells of different cell types. In some cases, the target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and tlie off-target tissues are different tissues. For example, the target cell may be a liver hepatocyte and the plurality of off-target cells may comprise a pancreatic acinar cell or a gastric epithelial cell. In some cases, the plurality of off-target ceils comprises a pancreatic acinar cell and a gastric epithelial cell.

[0143] In some cases, the method comprises comparing the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps. In some cases, comparing the epigenetic maps detects a differential between the target cellular epigenetic map and the plurality of off- target cellular epigenetic maps. In some cases, the method comprises using the differential to identify the target genomic site in the plurality of genomi c sites, wherein the target genomic site is in the second methylation state in each off-target cell in the plurality of off-target cells. For example, the target cellular epigenetic map may be a diseased liver hepatocyte epigenetic map, and the plurality of off-target cellular epigenetic maps may be a healthy pancreatic acinar epigenetic map and a healthy gastric epithelial cell epigenetic map. Comparing the diseased liver hepatocyte epigenetic map with the healthy pancreatic acinar epigenetic map and the healthy gastric epithelial cell epigenetic map may reveal a target site that is unmethylated in the diseased liver hepatocyte and methylated in both the healthy pancreatic acinar and the healthy gastric epithelial cell. This target site may be identified as a favorable target site for methylation given that this target site is already methylated in the healthy pancreatic acinar and the healthy gastric epithel tai cell and introducing a targeted methylating agent to tins site would have no effect on this site in the healthy pancreatic acinar and the healthy gastric epithelial cell.

[0144] In some cases, the method further comprises generating the plurality of off-target cellular epigenetic maps.

Method of treatment

[0145] The method can further comprise contacting a cell in the initial epigenetic state with an epigenetic effector, blocking reagent, or epigenetic modifying system, thereby producing a treated cell. The method can further comprise generating an epigenetic profile of the treated cell according to any of the methods described elsewhere herein The method can further comprise screening the epigenetic intervention based on a differential cellular state profile. For example, the epigenetic profile of the treated cell can be compared with the initial epigenetic state and the desired epigenetic state. The screening can comprise assessing the difference between the treated epigenetic state and the initial epigenetic state, and/or assessing the difference between the treated epigenetic state and the desired epigenetic state. In some cases, the epigenetic intervention can be selected based on how close the treated epigenetic state is to the target epigenetic state.

[0146] In some embodiments, the present disclosure provides a method of selecting a combination of epigenetic interventions for cellular treatment based on a differential cellular state profile generated according to any of the embodiments described herein. In some embodiments, a method or composition described herein is used to treat disease selected from a neurological disease, a cancer, a hormonal disease, an imprinting disease, an inflammatory disease, or an infection. In some embodiments, the infection may be a chronic infection. In some embodiments, the chronic infection may be a viral or bacterial chronic infection. In some embodiments, the modified, transformed or modulated cells, e.g., the modified, transformed or modulated cell disclosed herein and/or their progeny may be used as input into processes for further modifying such ceils to produce therapeutic cells. In some embodiments, the ceil may be obtained from a subject having a disease.

Compositions for Use in Guided Epigenetic Editing

Epigenetic profile

[0147] In some aspects, the methods described herein comprise identifying an epigenetic target site from an epigenetic profile of a ceil in a specific cellular state. Hie epigenetic profile can be represented by an epigenetic map. The epigenetic map can present the epigenetic state (a methylation state, a 5’ hydroxymethylation state, a chromatin accessibility state, or ahistone modification state) of a genomic site at a single-nucleotide resolution. A cellular state can be a state of differentiation, a state of rejuvenation, a state of exhaustion, a state of memory, a biological age, a state of health, a state of disease, or a state of dysfunction. For example, a cellular state can comprise a level of sternness, a stem-like characteristic, or a memory characteristic. In another example, a cellular state can comprise a level of exhaustion, a level of differentiation, a disease-associated characteristic, a dysfunction-associated characteristic, or an age-associated characteristic .

[0148] In some embodiments, the methods described herein comprise using an epigenetic profile of a cell in a diseased state, an exhausted state or a dysfunctional state. In some embodiments, the methods described herein comprise using an epigenetic profile of a cell in a healthy state, a rejuvenated state, or high-functioning state. In some embodiments, the methods described herein comprise using an epigenetic profile of a cell in a young, more stemlike, or less differentiated cellular state. In some embodiments, the methods described herein comprise using an epigenetic profile of a cell in aged or more differentiated cellular state. For example, a cellular state may be an exhausted effector tumor infiltrating lymphocyte, a stemlike tumor infiltrating lymphocyte, a fibrotic state, a resident cell state, an induced pluripotent stem cell state, a target differentiated cell state, an alpha cell state, or a beta cell state.

[0149] In some aspects, the methods described herein describe using an epigenetic profile of a cellular state of a cell or tissue type. A cell or tissue type may be defined by one or more characteristics, such as phenotypic properties (e.g., cell surface markers) or certain functional characteristics (e.g., ability to release cytokines). A cell type can also be classified by its tissue of origin (e.g., liver hepatocyte or blood granulocyte). For example, a cell may be a red blood cell, a white blood cell (e.g., a granulocyte or a lymphocyte), a liver hepatocyte, a cardiomyocyte, a pancreatic acinar cell, or an oligodendrocyte. In some embodiments, the methods described herein comprise profiling a cellular state of a lymphocyte (e.g., a natural killer cell, a T-cell, or a B-cell). In some cases, the lymphocyte is a T-cell. The T-cell may be a CD8+ T-cell, a CD4+ T-cell, or a regulatory T-cell.

[0150] In some aspects, the methods described herein describe methods of analyzing a cell’s epigenetic profile or generating an epigenetic map of a cell’s epigenetic profile. Analyzing a. cell’s epigenetic profile or generating an epigenetic map of a cell’s epigenetic profile may comprise methylome sequencing. Methylome sequencing may' provide information about methylation states (e.g., methylated or unmethylated) of different sites in a gene or multiple genes. The methylome sequencing may be whole methylome sequencing and provide information about methylation states across the whole genome. Methylome sequencing may provide information about the methylation state at specific CpG sites or DNA metliylations regions that regulate gene expression through transcriptional silencing of the corresponding gene. DNA methylation states may differ in different cell types or tissue types. DNA methylation states may differ based on state of differentiation, a state of rejuvenation, a state of exhaustion, a state of memory, a biological age, a state of health, a state of disease, or a state of dysfunction.

[0151] One or more epigenetic profiles described herein can be compared to identify a unique epigenetic marker or a unique epigenetic pattern (e .g., a unique methylation marker or a unique methylation pattern). In some cases, one or more epigenetic profiles described herein can be compared to identify a unique acetylation marker or a unique acetylation patern. An epigenetic profile described herein can be used to identify a desired methylation or acetylation state at a specific genomic site. A differential between two or more epigenetic profiles described herein can identify a target site for modifying a cellular state to achieve a desired cellular state or to be closer to a desired cellular state. In some cases, detecting a differential in the two or more epigenetic profiles comprises comparing two or more epigenetic maps of the two or more epigenetic profiles. For example, a genomic site may be methylated in a first epigenetic profile and unmethyiated in a second epigenetic profile. The differential at this genomic site can be detected by comparing the two epigenetic profiles In some cases, a differential between two or more epigenetic profiles can be a differential in epigenetic state (e.g., methylation state) of a single nucleotide. In some cases, a differential between two or more epigenetic profiles can be a differential in epigenetic state (e.g., a methylation pattern) of a genomic region comprising at least 2, at least 4, at least 6, at least 8, at least 10, at least 20, at least 30, at least 40, at least 50, at least 60, at least 80, at least 100, at least 150, at least 200, at least 250, at least 300, at least 350, at least 400, at least 450, or at least 500 nucleotides. A list of one or more epigenetic target sites and associated modifications for each epigenetic target site may be selected computationally. For example, a machine-learning model trained to associate one or more modifications of an epigenetic marker to a desired cellular state (e.g., a desired biological age state or a desired disease state). Data used to train the model can include epigenetic profiling data from a database (e.g., a publicly available database). Training data may additionally’ or alternatively include differential cellular state profiling data.

[0152] In some embodiments, the differential cellular state profiling can be epigenetic profiling. In some embodiments, the epigenetic profiling can comprise unsupervised clustering scheme In some embodiments, the unsupervised clustering scheme can identify epigenetic states on a whole genome. In some embodiments, the unsupervised clustering scheme can identify epigenetic states on a gene-level basis. In some embodiments, the unsupervised clustering scheme can identify epigenetic states on a whole genome and gene-level basis. In some embodiments, clustering scheme can further comprise calculating the information gain for CpGs. In some cases, the information gained from a given classification (e.g., cluster) can provide information on the relative importance of a CpG methylation status on the underlying state classification (e.g., cluster).

Cellular identity marker

[0153] As described herein, the present disclosure in part provides a cellular identity marker.

The epigenetic cellular identity marker can be correlated with the identity (i.e., cellular differentiation state) of cell. Loss of the epigenetic cellular identity¹ markers may cause the ceil to lose its cellular identity. See, for example, Basu et al Epi gene tic reprogramming of cell identity: lessons from development for regenerative medicine. Clinical Epigenetics, vol 13, no. 144 (2021). The cellular identity of a cell can be the cellular differentiation state, for example, an immune cell (or particular type of immune cell), neural cell, epithelial cell, etc. In some cases, cell identity is dictated by the specific set of genes expressed and proteins produced in tire cell that are activated by the epigenetic state of the cell to enable its unique function. In some cases, altering the epigenetic state of the epigenetic cellular identity markers causes a loss of cellular state identity.

[0154] In some embodiments, the epigenetic cellular identity marker is selected from a database. Such a database may be generated, for example, by comparing epigenetic profiles of different types of cells. The specific epigenetic sites across the genome of the different types of cells are compared and sites that are highly specific to a given tissue and cell are selected. For example, this could be in the form of a specific set of CpG sites in particular location in the genome that are unmethylated for cardiomyocytes but are methylated in all other tissues. Exemplary’ cellular identity markers are described in Moss et al., Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease, Nat. Commun., vol. 9, no.

5068 (2018): Loyfer et al., A human DNA methylation atlas reveals principles of cell typespecific methylation and identifies thousands of cell type-specific regulatory elements, Biorxiv 2022.01.24.477547 (2022); and Cui et al., A human tissue map of 5-hydroxymethylcytosines exhibits tissue specificity through gene and enhancer modulation, Nat. Commun., vol. 11, no. 6161 (2020).

Epigenetic effector

[0155] As described herein, the present disclosure in part provides an epigenetic effector comprising a nucleic acid binding moiety and an effector moiety. In some embodiments, the effector moiety of the epigenetic effector may be or may comprise a moiety capable of modifying a nucleic acid. In some embodiments, the nucleic acid is a DNA, e.g., genomic DNA. In some embodiments, the nucleic acid is a RNA, e.g., niRNA. In some embodiments, the effector moiety is capable of altering methylation profile of a genome of a cell. In some cases, effector moiety can modify a nucleic acid by increasing or decreasing methylation in a target nucleic acid. In other cases, the effector moiety modifies the chromatin structure of a cell through histone modifications, e.g., via modulating histone methylation and/or acetylation profile. In some embodiments, the epigenetic effector comprises a nucleic acid binding moiety and multiple effector moieties (e.g., 1 , 2, 3, 4, 5, 6. 7. 8. 9, or 10 effector moieties). In some embodiments, the nucleic acid binding moiety and die effector moiety are covalently linked, e.g., via a peptide bond. In some embodiments, the nucleic acid binding moiety and the effector moiety are not covalently linked. [0156] In some embodiments, the nucleic acid binding moiety of the epigenetic effector determines the site of nucleic acid modification through specific binding with a target nucleic acid. In some embodiments, the nucleic acid binding moiety may be or comprise a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a zinc finger domain, or a TAL domain, as described elsewhere herein. In some embodiments, the nucleic acid binding moiety of the epigenetic effector may be or may comprise a Cas9 protein or a functional equivalent. In some embodiments, the nucleic acid binding moiety of the epigenetic effector may be or may comprise a Casl2 protein or a functional equivalent. In some embodiments, the epigenetic effector may be capable of binding to a transcription regulatory element (e.g., a promoter, an enhancer, or a transcription start site operably linked to a gene) and facilitating an epigenetic modification at the desired target site. In some embodiments, the epigenetic effector may be capable of binding to a site in a CpG island of a target nucleic acid and introducing an epigenetic modification at a desired target site. In some embodiments, the epigenetic effector may be capable of methylating or demethylating at least one CpG site of a target nucleic acid.

[0157] In some embodiments, the epigenetic effector is capable of binding to a transcription regulatory element. In some embodiments, the epigenetic effector is capable of binding to a transcription regulatory element selected from a promoter, an enhancer, a silencer, an insulator, a locus control region, or a transcription start site operably linked to a gene. In some embodiments, the epigenetic effector is capable of binding to a promoter element. In some embodiments, the epigenetic effector is capable of binding to a promoter element selected from a TATA box, a CAAT box, a GC box, an INR, a DPE, an MTE, a DCE, or a BRE. In some embodiments, the epigenetic effector is capable of binding to a TATA box. In some embodiments, the epigenetic effector is capable of binding to a CAAT box. In some embodiments, the epigenetic effector is capable of binding to a GC box. In some embodiments, the epigenetic effector is capable of binding to an INR. In some embodiments, the epigenetic effector is capable of binding to a DPE, In some embodiments, the epigenetic effector is capable of binding to an MTE. In some embodiments, the epigenetic effector is capable of binding to a DCE. In some embodiments, the epigenetic effector is capable of binding to a BRE. Hie consensus sequences of exemplary promoter elements are provided in Table 13 below. In some embodiments, the promoter may be constitutively active. Alternatively, in some embodiments, the promoter may be conditionally active (e.g., where transcription is initiated only under certain physiological conditions). In some embodiments, the epigenetic effector is capable of binding to an enhancer. In some embodiments, the epigenetic effector is capable of binding to a silencer. In some embodiments, the epigenetic effector is capable of binding to an insulator. In some embodiments, the epigenetic effector is capable of binding to a locus control region. In some embodiments, the epigenetic effector is capable of binding to a transcription start site.

[0158] In some embodiments, a nucleic acid binding moiety binds to its target sequence with a KD of less than or equal to 500, 450, 400, 350, 300, 250, 200, 150, 100, 50, 40, 30, 20, 10, 9, 8, 7, 6, 5, 4, 3, 2, I, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.09, 0.08, 0 07, 0 06, 0.05, 0.04, 0 03, 0.02, 0.01, 0.005, 0.003, 0 002, or 0.001M. In some embodiments, , anucleic acid binding moiety does not bind, e.g., does not delectably bind to a non-target sequence. In some embodiments, the nucleic acid binding moiety comprises a sequence complimentary, e.g., at least 5%, at least 10%, at least 15%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 99%, or 100% complimentary to the target sequence.

[0159] In some cases, an epigenetic effector may comprise a fission protein comprising a nucleic acid binding domain and an effector domain. In some instances, the nucleic acid binding domain of an epigenetic effector may be located at tire N-terminus or C-terminus of the effector domain. In some cases, the nucleic acid binding domain is located at the N-terminus of the effector domain. In other cases, the nucleic acid binding domain is located at the C-terminus of the effector domain. In some cases, the nucleic acid binding domain is located within the effector domain. In other cases, the effector domain is located within the nucleic acid binding domain. In some embodiments, the epigenetic effector comprises more than one effector domain. For an epigenetic effector comprising more than one effector domain, in some cases, the first effector domain may be located at the N-tenninus or C-terminus of the second effector domain. Tn other cases, first effector domain may be located at the N-terminus of the nucleic acid binding domains, and the second effector domain may be located at the C-terminus of the nucleic acid binding domain. The epigenetic effector may comprise any combination of arrangements of the nucleic acid binding moiety and the effector moiety described in this disclosure.

[0160] In some embodiments, the epigenetic effector, e.g, an epigenetic effector described herein may be capable of methylation, demethylation, acetylation, and/or deacetylation. In some embodiments, the epigenetic effector is capable of adding or removing a methyl group in a nucleic acid. In some embodiments, the epigenetic effector is capable of adding or removing a methyl group in a histone. In some embodiments, the epigenetic effector is capable of adding or removing an acetyl group in a histone. In some embodiments, the epigenetic effector comprises an effector moiety selected from DNMT3AL DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMTI, MQ1, MET1, DRAG, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e., ESDI), KDM1B (i.e, LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1 , KAT2A, KAT3A, KAT3B, KAT13C, HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6, HDAC7, HDAC8, HDAC9, HDAC10, HDAC11, SIRT1, SIRT2, SIRT3, SIRT4, SIRT5, SIRT6, SIRT7, SIRT8, SIRT9, KRAB, MeCP2, HP1, RBBP4, REST, FOG1, SUZ12, or a functional equivalent thereof.

[0161] In some embodiments, tire epigenetic effector, e.g, an epigenetic effector described herein may comprise multiple effector moieties, e.g, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 effector moieties.

[0162] In some embodiments, the 2nd, 3rd, 4th, 5th, 6th, 7th, 8th, 9th, or 10th effector moiety is selected from one or more ofDNMT3Al, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DAMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMTI, MQ1, MET1, DRM2, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e, G9A), EHMT1 (i.e, GLP), SUV39H1 , EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e, ESDI), KDM1B (i.e, LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1, KAT2A, KAT3A, KAT3B, KAT13C, HDAC1, HDAC2, HDAC3, HDAC4, I-IDAC5, HDAC6, HDAC7, HDAC8, HDAC9, HDAC10, HDAC11, SIRT1, SIRT2, SIRT3, SIRT4, SIRT5, SIRT6, SIRT7, SIRT8, SIRT9, KRAB, MeCP2, HP1, RBBP4, REST, FOG1, SUZ12, or a functional equivalent thereof. [0163] In some embodiments, the epigenetic effector, an epigenetic effector described herein may simultaneously methylate and transcriptionally repress a target site. In some embodiments, the epigenetic effector, an epigenetic effector described herein may simultaneously methylate and transcriptionally activate a target site. In some embodiments, the epigenetic effector, an epigenetic effector described herein may simultaneously demethylate and transcriptionally repress a target site. In some embodiments, the epigenetic effector, an epigenetic effector described herein may simultaneously demethylate and transcriptionally activate a target site. In some embodiments, the epigenetic effector, an epigenetic effector described herein may simultaneously acetylate and transcriptionally repress a target site. In some embodiments, the epigenetic effector, an epigenetic effector described herein may simultaneously deacetylate and transcriptionally activate a target site.

[0164] In some embodiments, a fusion construct comprises a protein having a sequence as recited in Uniprot ref: Q8NFU7 or a protein encoded by a nucleotide sequence as recited in NCBI Accession: Accession: NM_030625.3,

GI: 1519311914: or Accession: NM 001406365.1 , GI: 2238345226; or Accession: NM ,001406367.1, GI: 2238345083; or Accession: NM 001406368.1, GI: 2238345245; or Accession: NMJ001406369. 1, GI: 2238345201; or Accession: NM_001406370.1, GI: 2238345031 ; or Accession: NM 001406371.1, GI: 2238345008; or Accession: NM _001406372.1,

GI: 2.238345087; or Accession: NM_001406373.1, GI: 2238345233; or Accession: NM_001406374, 1, GI: 2238885731 ; or Accession: NM_001406375.1,

GI: 2238345043; or Accession: NM 001406376 1, GI: 2238345085. In some embodiments, a fusion construct comprises a functional fragment or variant of any thereof, or a polypeptide with a sequence that has at least 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identity-' to any of the above-referenced sequences. In some embodiments, the fusion construct further comprises a Cas9 protein. In some embodiments, the fusion construct demethylates the target sequence. In some embodiments, the fusion construct activates the target gene.

[0165] In some embodiments, a fusion construct comprises a protein having a sequence as recited in Uniprot ref: Q9Y6K1 or a protein encoded by a nucleotide sequence as recited in NCBI Accession: NM__001320892 2, GI: 1677500358; or Accession: NM_001320893.1, GI: 1003701584; or Accession: NM 001375819.1, GI: 1034612234; or

Accession: NM_022552.5, GI: 1812533218; or Accession: NM_153759.3, GI: 371940994; or Accession: NM_175629.2, GI: 371940990; or Accession: NM_175630.1,GI: 28559070. In some embodiments, a fusion construct comprises a functional fragment or variant of any thereof, or a polypeptide with a sequence that has at least 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identity to any of the above-referenced sequences. In some embodiments, the fusion construct further comprises a Cas9 protein. In some embodiments, the fusion construct methylates the target sequence. In some embodiments, the fusion construct deactivates the target gene.

[0166] In some embodiments, a fusion construct comprises a protein having a sequence as recited in Uniprot ref: Q9UJW3 or a protein encoded by a nucleotide sequence as recited in NCBI Accession: NM_ 013369.4, GI: 1676318741: or Accession: NM_, 175867.3,

GI: 1732746326. In some embodiments, a fusion construct comprises a functional fragment or variant of any thereof, or a polypeptide with a sequence that has at least 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identity to any of the above-referenced sequences. In some embodiments, the fusion construct further comprises a Cas9 protein. In some embodiments, the fusion construct methylates the target sequence. In some embodiments, the fusion construct deactivates the target gene.

[0167] In some embodiments, a fusion construct comprises a protein having a sequence as recited in Uniprot ref: P21506 or a protein encoded by a nucleotide sequence as recited in NCBI Accession: NM_ 015394.5, GI: 1519244023. In some embodiments, a fusion construct comprises a functional fragment or variant of any thereof, or a polypeptide with a sequence that has at least 80, 85, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identity to any of the abovereferenced sequences. In some embodiments, the fusion construct further comprises a Cas9 protein. In some embodiments, the fusion construct methylates the target sequence. In some embodiments, the fusion construct deactivates the target gene.

Effector moieties

[0168] As described herein, the present disclosure in part provides an effector moiety of the epigenetic effector. In some embodiments, the effector moiety may be or may comprise a moiety capable of modifying a nucleic acid (e.g., DNA, e.g., genomic DNA). In some embodiments, the effector moiety may be or may comprise a moiety capable of modifying a nucleic acid (e.g., RNA, e.g , mRNA). In some embodiments, the effector moiety may be or may comprise a moiety capable of modifying a histone. In some embodiments, the effector moiety may be capable of altering methylation profile of a genome of a cell.

[0169] In some embodiments, the epigenetic effector comprises an effector moiety comprising a DNA methylation, DNA demethylation, histone methylation, or histone acetylation activity. In some embodiments, the epigenetic effector may be or comprise a methylase or a demethylase. In some embodiments, the effector moiety may be selected from a DNA methyltransferase, DNA demethylase, a histone methyltransferase, a histone demethylase, a histone acetyltransferase, or a histone deacetylase. In some embodiments, the effector moiety may be or comprise a transcriptional activator or a transcriptional repressor. In some embodiments, the effector moiety is selected from DNMTL DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1, MET1, DRM2, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i e, GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1 , SUV420H2, KDM1A (i.e, ESDI), KDM1B (i.e, LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1 , KAT2A, KAT3A, KAT3B, KAT13C, HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6, HDAC7, HDAC8, HDAC9, HDAC10, HDAC11 , SIRT1 , SIRT2, SIRT3, SIRT4, SIRT5, SIRT6, SIRT7, SIRT8, SIRT9, KRAB, MeCP2, 1 IPL RBBP4, REST. FOG 1, SUZ12, MBD2, MBD3, TDG, ROS1, DME, DML2, DML3, TRDMT1 (DNMT2), m.Mpel, M.Sssl, M. Hpall, VI Aral. M.HacIII, M.Hhal, M.Mspl, Ml J L Dim-2, dDnmt2, or Pmtl or a functional equivalent thereof. In some cases, the effector moiety comprises M TaqI, M.EcoDam, M.CcrMI, or CamA.

[0170] In some embodiments, the effector moiety of the epigenetic effector may enhance or repress methylation in a target nucleic acid. The effector moiety of the epigenetic effector may be or comprise a DNA methyltransferase or a functional equivalent thereof The DNA methyltransferase may be selected from a m6A methyltransferase, an m4C me thyltransferase, and an m5C methyltransferase. The DNA methyltransferase may be selected from DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1, METL DRM2, CMT2, CMT3, or a functional equivalent thereof.

[0171] In some embodiments, the effector moiety may be or may comprise a moiety capable of effecting DNA demethylation. The effector moiety may be or comprise a DNA demethylase. The effector moiety may comprise a member of the TET family. The effector moiety may be selected from TET1, TET2, and TET3, or a functional equivalent thereof. The effector moiety may be or comprise TDG.

[0172] In other embodiments, the effector moiety of the epigenetic effector may increase or decrease methylation or acetylation in a histone. Increasing or decreasing methylation or acetylation in a histone can modify chromatin structure . In some embodiments, the effector moiety may be or comprise a histone methyltransferase or a functional equivalent thereof The histone methyltransferase may be selected from SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, a viral lysine methyltransferase (vSET), a histone methyltransferase (SET2), a protein-lysine N- methyl transferase (SMYD2), or a functional equivalent thereof. In some cases, the effector moiety comprises D0T1L, PRDM9, PRMTI, PRMT2, PRMT3, PRMT4, PRMT5, NSD1, NSD2, NSD3, R0M2, AtHD3A, HDAC11, HDAC8, SIRT3, S1RT6, HST2, a SETDB1 domain, a NuRD domain, or a TET family protein domain.

[0173] The effector moiety of the epigenetic effector may be or comprise a histone demethylase or a functional equivalent thereof. Hie histone demethylase may be selected from KDM1 A (i.e., LSD1), KDM1B (i.e., LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, or a functional equivalent thereof.

[0174] In some embodiments, the effector moiety of the epigenetic effector may be capable of adding or removing an acetyl group m a histone. In some embodiments, the effector moiety of the epigenetic effector may be or comprise a histone acetyltransferase or a functional equivalent thereof. Hie histone acetyltransferase may be selected from KAT1, KAT2A, KAT3A, KAT3B, KAT13C, or a functional equivalent thereof. The effector moiety of the epigenetic effector may be or comprise a histone deacetylase. The histone deacetylase may be selected from HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6, HDAC7, HDAC8, HDAC9, HDAC10,

HDAC11, SIRT1, SIRT2, SIRT3, SIRT4, SIRT5, SIRT6, SIRT7, SIRT8, SIRT9, or a functional equivalent of any thereof.

[0175] In some embodiments, the effector moiety of the epigenetic effector may be or comprise a transcriptional activator moiety' or a transcriptional regulator. In some embodiments, the transcriptional activator moiety may be selected from categories comprising a DNA demethylase, histone acetyltransferase, histone methyltransferase, and histone demethylase. In some embodiments, the transcriptional activator moiety or transcriptional regulator may be selected from a VP16 tetramer (e.g., VP64), a p65 activation domain, a VP 160, Rta, a p300 domain, VPR, VPH, HSF1, CBP, FOXO3, a KRAB domain, a lysine-specific histone demethylase 1 (ESDI), a euchromatic histone-lysine N -methyltransferase 2 (G9a), a histone - lysine N-methyltransferase, an enhancer of zeste homolog 2 (EZH2), a viral lysine methyltransferase (vSET), a histone methyltransferase (SET2), a protein-lysine N- methyltransferase (SMYD2), SUV39H1, NUE, DIMS, MES0L04, SETS, SET-TAF1B, an Epstein-Barr virus R transactivator (Rta) activation domain, an Rta activation domain, CACO1, DRM1, DRM2, CMT1, CMT2, CMT3, CBX8, CBX5, CBXI, CBX3, CBX4, CBX7, CDYL2,

CDY2, PCGF2, SCMH1 , SCML2, MPP8, SUMO3, SUMO1, SUMO5, HERC2, IRF2BPI, IRF2BP2, IRF2BPL, KMT2A, HAT1, HIE lalpha, SMARCA2, SIN3A, RYBP, SAVE HAP2, HAP3, or HAP4. In some cases, the effector moiety comprises VPH, VPR, mini VR, or micro VR. In some cases, the effector moiety comprises a gene expression regulatory domain. In some cases, the effector moiety comprises Mascl, Masc2, Rid, a domain encoded by the hsdM gene, or a domain encoded by the hsDSgene. In some embodiments, the effector moiety of the epigenetic effector may be or comprise a transcriptional regulation domain. 'The transcriptional regulation domain may be selected from Kruppel associated box, such as a KRAB domain, an ERF repressor domain, an MXI 1 repressor domain, a SID repressor domain, a SID4X repressor domain, or a Mad-SID repressor domain. In some cases, the KRAB domain is a KRAB domain ofKOXl or ZIM3.

[0176] In other embodiments, the effector moiety of the epigenetic effector may be or comprise a transcription repressor moiety. In some embodiments, the transcriptional repressor moiety may be selected from the categories comprising a DNA methyltransferase, histone deacetylase, histone methyltransferase, and histone demethylase. In some embodiments, the effector moiety may comprise a protein selected from KRAB, MeCP2, HP1, RBBP4, REST, FOG1 , SUZ12, or a functional equivalent.

[0177] In some embodiments, the effector moiety of the epigenetic effector may be or comprise a transcription factor regulator or DNA-binding domain. Hie transcription factor regulator or DMA-binding domain may be selected from a KRAB domain, KAP1 domain, MECP2 domain, VP16, P64, p65, FOXA 1, FOXA2, FOXO3, FOXO1, TOX, TOX3, 1'0X4. ID2, ID1 , CREM, SCX, TWST1, CREB1, TERF1, ID3, GSX1, ATF1, TWST2, ZMYM3, 12BP1, RHXF1, 12BL, TRI68, HXBI3, HEY1, PHC2, F1GLA, SAMI1, KMT2B, HEY2, JDP2, ASCL4, HHEX, GSX2, ASCL3, PHCI, OTP, I2.BP2, VGLL2, HXA1 1, PDLI4, ASCL2, CDX4, ZN860, NKX25, ISLE CDX2, PROP1, HXC11, HXC10, PRS6A, VSXL NKX23, MTG16, HMX3, E1MX1, KIF22, CSTF2, CEBPE, CLX2, PPARG, PRIC1, UNC4, BARX2, ALX3, TCF15, TERA, VSX2, HXDI2, CDX1, TCF23, ALX1, HXA10, RX, CXXC5, SCML1, NFIL3, DLX6, MTG8, CDX8, CEBPD, DLX5, NOTC1, TERF2, RGSI2, PAX7, NKX62, ASXL2, GATAI, ZMYM5, GATA2, GATA3, IRX4, ZBED6, LHX4, NKX61, R51A1, MB3LL NKX22, ATF1, SSX2, ZN680, HXA13, PHC3, TCF24, ETV7, LMBL4, PDIP3, CERBPB, SIN3B, SMBT1, SECI3, FIP1, ALX4, LHX3, PRIC2, MAGI3, NELLI, PRRXI, MTG8R, RX2, DLX3, DLX1, NKX26, NAB1, SAMD7, PITX3, WDR5, ME0X2, NAB2, DHX8, FOXA2, EMX2, CPSF6, HXC12, KDM2B, LMBL3, PHX2A, EMX1, NC2B, DLX4, SRY, NELLI, BSH, SF3B4, TEAD1, TEAD2, RGAP1, PHF1, RBBP7, SPI2B, LRP1, MIXL1, SGTI, LMCD1, CEBPA, SOX 14, ZTIP, PRP19, NKX11 , RBBP4, DMRT2, SMCA2, VP 16, VP64, VP 160, CITED2, Stat3, p65, p53, ZNF473, myb, CRTC1, Med9, EGR3, Dpy-30, NCOA3, HSF1, YAF2, MGA, BINI, RTA, AFP, ANM2, APBB1, EGR3, IKKA, ITCH, KIBRA, KPCI, KS6B2, MYB, MYB A, NCOA2, NOCA3, NOC2, STAT2, T2EB, CRTC2, CRTC3, CXXC1, DPF1, ENL, IMA5, MTA3, WWTR1, CREBBP, GCN4, GCN5, SAGA, or SALSA.

[0178] In some embodiments, the effector moiety of the epigenetic effector may comprise a tyrosine kinase, e.g, ABL1 or TK. In some cases, the effector moiety of the epigenetic effector may comprise a Homobox, e.g., HOXA 13, HOXB13, HOXC13, H0XA1 1, HOXC11, HOXC10, HOXA10, HOXB9, HOXA9.

[0179] In some embodiments, the effector moiety of the epigenetic effector may be or comprise an epigenetic or chromatin modifier. The epigenetic or chromatin modifier may be selected from a TET protein (e.g., TET1), an ERF protein (e.g.ERFl, ERF3), ESDI, PYGO1, KRAB, MeCP2, SIN3A, HDTL MBD2B, NIPP1, VP64, HP1A, Rb, SUVR4, COBB, NCOR, or HP1A.

[0180] In some embodiments, the effector moiety of the epigenetic effector may be capable of cartying out phosphorylation or dephosphorylation. In some cases, the effector moiety may be capable of carrying out phosphorylation of a histone. In some cases, the effector moiety may be capable of carrying out dephosphorylation of a histone. In some cases, the effector moiety may be capable of catalyzing the addition of a phosphate group. In some cases, the effector may be capable of catalyzing the removal of a phosphate group. The effector moiety may comprise a phosphorylase, a phosphatase, or a kinase.

[0181] In some embodiments, the effector moiety of the epigenetic effector may be capable of carrying out ubiquitination. In some embodiments, the effector moiety of the epigenetic effector may be capable of carry ing out ubiquitination of a histone. The effector moiety may comprise a ubiquitin-activating enzyme (El), a ubiquitin conjugating enzyme (E2), or aubiquitin-protein ligase (E3).

[0182] In some embodiments, the effector moiety of the epigenetic effector may be or comprise a protein complex or interactor. The protein complex or interactor may be selected from APC 16, DPY30, PRP19, PYGO1, PYGO2, SMCA2, SMRC2, U2AF4, WBP4, WWP1, WWP2, PCAF, RBAK, or HKRI, [0183] In some embodiments, the effector moiety of the epigenetic effector may be or comprise a protein domain (e.g, a PI6 domain) or a protein tag (e.g., a SunTag).

[0184] In some embodiments, the epigenetic effector may comprise multiple, e.g., at least 2, 3,

4, 5, 6, 7, 8, 9, or 10 effector moieties. In some embodiments, the epigenetic effector may comprise a first effector moiety and a second effector moiety. The second effector moiety may be selected from DNMT1 , DNMT3AL DNMT3A2, DNMT3BI, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1 , MQ1 , METl, DRM2, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i.e, GLP), SUV39H1 , EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e , ESDI), KDM1B (i.e, LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1, KAT2A, KAT3A, KAT3B, KAT13C, HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6, HDAC7, HDAC8, HD ACM, HDAC10, HDAC11, SIRT1, SIR’ I '2, SIRT3, SIRT4, SIRT5, SIRT6, SIRT7, SIRT8, SIRT9, KRAB, MeCP2, HP1, RBBP4, REST, FOG1, SUZ12, or a functional equivalent thereof.

[0185] In some embodiments, the effector moiety may be a durable effector moiety. In some embodiments, the effector may be a transient effector moiety. In some embodiments, the epigenetic effector may comprise at least two durable effector moieties. In some embodiments, the epigenetic effector may comprise at least two transient effector moieties. In some embodiments, the epigenetic effector may comprise at least one durable effector moiety and at least one transient effector moiety.

[0186] In some embodiments, the epigenetic effector is a transcriptional enhancer. A transcriptional enhancer can increase gene transcription. In some embodiments, the transcriptional enhancer is a transcriptional activator, a protein that acts via recruitment of transcription activator proteins, modifier of target gene, such as demethylation, recruitment of DMA modifier, modulator of histones associated with target DNA, recruitment of a histone modifier (e.g, acetylation and/or methylation of histones). In some embodiments, the epigenetic effector comprises multiple transcriptional enhancers, e.g, at least 2, at least 3, at least 4, at least

5, at least 6, at least 7, at least 8, at least 9, or at least 10 transcriptional enhancers. Examples of proteins (or fragments thereof) that can be used in increase transcription include but are not limited to: transcriptional activators such as VPR (e.g, VPR-p65-Rta), VP16, VP64, VP48, VP160, MyoDl, HSF1,RTA, SET7/9, ap65 subdomain (e.g, from NFkB), and activation domain of EDLL and/or TAL activation domain (e.g, for activity in plants); histone lysine methyltransferases such as SET1A, SET1B, MLL1 to 5, ASHI, SYMD2, NSD1, and the like; histone lysine demethylases such as JHDM2a/b, UTX, JMJD3, and the like; histone acetyltransferases such as GCN5, PCAF, CBP, p300, p300 core, TAF1, TIP60/PLIP, MOZ/MYST3, MORF/MYST4, SRC1, ACTR, Pl 60, CLOCK, and the like; and DNA demethylases such as Ten-Eleven Translocation (TET) dioxygenase 1 (TET1CD), TET1, DME, DMLI, DML2, ROSE BRIM, or a fragment or vanant thereof. In some embodiments, the transcriptional enhancer is a VP64. In some embodiments, the transcriptional enhancer is a p300 or a p300 core. In some embodiments, the transcriptional enhancer is p300. In some embodiments, the transcriptional enhancer comprises H3K27ac. In some embodiments, the transcriptional enhancer is a BRD4.

[0187] In some embodiments, the expression level of a target gene that is enhanced via the transcriptional enhancer disclosed herein is at least about 50%, at least about 60%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, at least about 100%, at least about 101%, at least about 102%, at least about 103%, at least about 104%, at least about 105%, at least about 106%, at least about 107%, at least about 108%, at least about 109%, at least about 110%, at least about 115%, at least about 120%, at least about 125%, at least about 130%, at least about 140%, at least about 150%, at least about 160%, at least about 170%, at least about 180%, at least about 190%, at least about 200%, or more, as compared to the expression level of the target gene in the control cel l without the transcriptional enh ancer disclosed herein. In some embodiments, the expression level of a target gene that is enhanced via die transcriptional enhancer disclosed herein is at least about 0. 1-fold, at least about 0 2-fokI, at least about 0.3-fold, at least about 0.4-fold, at least about 0.5-fold, at least about 0 6-fold, at least about 0.7-fold, at least about 0.8-fold, at least, about 0 9-fold, at least about 1-fold, at least about 1 .1 -fold, at least about 1.2-fold, at least about 1.3 -fold, at least about 1 .4-fold, at least about 1.5-fold, at least about 1.6-fold, at least about 1.7- fold, at least about 1.8-fold, at least about 1.9-fold, at least about 2-fold, at least about 2.5-fold, at least about 3-fold, at least about 3.5-fold, at least about 4-fold, at least about 4.5-fold, at least about 5-fold, at least about 6-fold, at least about 7-fold, at least about 8-fold, at least about 9-fold, at least about 10-fold, at least about 15-fold, at least about 20-fold, at least about 30-fold, at least about 40-fold, at least about 50- fold, or more greater than the expression level of the target gene in the control cell without the transcriptional enhancer disclosed herein.

[0188] In some embodiments, the transcriptional enhancer described herein can be part of a construct comprising any one or more of the nucleic acid binding domains described herein. In some embodiments, the tran scriptional enhancer can be part of a construct comprising any one or more of the nucleic acid binding domains described herein and any one or more of the epigenetic effectors described herein (e.g., Cas9-DNMT3A-VP64). In some embodiments, the construct can comprise a nucleic acid binding domain and an epigenetic effector, and further comprise another nucleic acid binding domain and a transcriptional enhancer (e.g., Cas9- DNMT3A+Cas9-VP64). In some embodiments, the transcriptional enhancer can be located at the N-terminus or C -terminus of the nucleic acid binding domain. In some embodiments, the transcriptional enhancer can be located at the N-terminus or C-terminus of the epigenetic effector. In some embodiments, the epigenetic effector can be located at the N-terminus or C- terminus of the nucleic acid binding domain. In some embodiments, the transcriptional enhancer can be placed in a spatial orientation which allows it to affect the transcription of the target. In some embodiments, a transcriptional enhancer can be advantageously positioned to affect the transcription of the target, and a nuclease can be advantageously positioned to cleave or partially cleave tlie target.

[0189] In some embodiments, a transcriptional repressor moiety described herein can be part of a construct comprising any one or more of tlie nucleic acid binding domains described herein. In some embodiments, the transcriptional repressor moiety can be part of a construct comprising any one or more of the nucleic acid binding domains described herein and any one or more of tire epigenetic effectors described herein (e.g., Cas9-DNMT3A-KRAB). In some embodiments, the construct can comprise a nucleic acid binding domain and an epigenetic effector, and further comprise another nucleic acid binding domain and a transcriptional repressor moiety (e.g., Cas9- DNMT3A+Cas9-KRAB). In some embodiments, the transcriptional repressor moiety can be located at the N -terminus or C -terminus of the nucleic acid binding domain. In some embodiments, the transcriptional repressor moiety can be located at the N-terminus or C- terminus of the epigenetic effector. In some embodiments, the epigenetic effector can be located at the N-terminus or C -terminus of the nucleic acid binding domain. In some embodiments, the transcriptional repressor moiety can be placed in a spatial orientation which allows it to affect the transcription of the target. In some embodiments, a transcriptional repressor moiety can be advantageously positioned to affect the transcription of the target, and a nuclease can be advantageously positioned to cleave or partially cleave the target. This may include positions other than the N-/C- terminus of the nucleic acid binding domain. Blocking reagent

[0190] In some aspects, the present disclosure provides a blocking reagent. The blocking reagent can be capable of blocking an off-target genomic site from an epigenetic modification. Tire blocking reagent can include a nucleic acid binding moiety that is capable of specifically binding to an off-target genomic site, e.g., an epigenetic cellular identity marker. Hie nucleic acid binding moiety may be configured to bind based on the nucleic acid sequence at the epigenetic locus (that is, the nucleic acid binding moiety’ can bind to the locus irrespective of the status of the epigenetic marker). The nucleic acid binding moiety can be a nuclease-deficient targeted nucleic acid binding moiety. The blocking reagent may include a CRISPR-based editing platform, which can include a dead endonuclease domain (e.g., a dead Cas9) domain. The CRISPR-based editing platform of the blocking reagent may further include one or more single guide RNA (sgRNA) molecules that targets one or more epigenetic cellular identity markers, e.g., a blocking guide RNA. A blocking guide RNA can comprise a nucleic acid sequence that is complementary to the off-target genomic site identified by any of the methods described herein. In some cases, the blocking guide RNA is configured to bind to a CRISPR/Cas domain, wherein the CRISPR/Cas domain - blocking guide RNA complex binds to the off-target genomic site. The CRISPR/Cas domain can be catalytically inactive. In some cases, CRISPR/Cas domain - blocking guide RNA complex prevents a modification, e.g., methylation, demethylation, acetylation, or acetylation, from occurring at the off-target genomic site. In another example, the nuclease-deficient targeted nucleic acid binding moiety comprises a transcription activator-like effector (TALE) domain or a zinc finger domain that specifically binds the off-target genomic site, e.g., an epigenetic cellular identity marker. In another example, the nuclease-deficient targeted nucleic acid binding moiety' comprises an OMEGA domain or a Fanzor domain that specifically binds the off-target genomic site, e.g., an epigenetic cellular identity marker. In some cases, the nucleic acid binding moiety' used with the blocking reagent is not fused or bound to an epigenetic effector moiety.

Nucleic acid binding ci moieties

[0191] As described herein, an epigenetic effector or blocking reagent disclosed herein can comprise a nucleic acid binding moiety. In some embodiments, the nucleic acid binding moiety may bind to a target nucleic acid, e.g., a DNA, e.g., a genomic RNA, e.g., an RNA, e.g., an mRNA. In some embodiments, the nucleic acid binding moiety may bind one or more genomic sequences in a cell. In some embodiments, the nucleic acid binding moiety may be or comprise a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a zinc finger domain, a TAL domain, a tetR domain, a meganuclea.se, or an oligonucleotide.

CRISPR/Cas domains

[0192} In some embodiments, a nucleic acid binding moiety may be or comprise a CRISPR domain. In some cases, a CRISPR domain is part of an epigenetic effector or a blocking reagent described elsewhere herein. A CRISPR domain can be the nucleic acid binding domain of an epigenetic effector. An CRISPR domain can be coupled to an effector moiety described elsewhere herein, for ..••••.am pie. as a fusion protein. Alternatively, an CRISPR domain can be the nucleic acid binding domain of a blocking reagent, described elsewhere herein.

[0193] In some cases, a CRISPR domain is part of an epigenetic effector described elsewhere herein The epigenetic markers in the cell may be modified using a CRISPR-based editing platform. An exemplary process for modifying a cell is shown in FIG. 3. Exemplary methods for using editing epigenomic markers using a CRISPR-based editing platform are described in Nakamura et al., CRISPR technologies for precise epigenome editing, Nature Cell Biology, vol. 23, pp. 1 1-22 (2021); Kang et ah, Regulation of gene expression, by altered promoter methylation using a CRISPR/Cas9~mediated epigenetic editing system, Scientific Repots, vol. 9, no. 11960 (2019); Nunez et al.. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing, Cell, vol. 184, p. 2503-2519 (2021); Policarpi et al.. Epigenetic editing: Dissecting chromatin function in context, Bioessays, vol. 43, no. 2000316 (2021). In an exemplary method, the CRISPR-based editing platform comprises one or more single guide RNA (sgRNA) molecules that targets an epigenetic marker. A dead Cas9 endonuclease (e g., Sa/pdCas9) or other suitable ortholog (e.g., dead Cpfl, dead Casl3, or dead CasRx) may be used for the CRISPR-based editing platform, which is optionally introduced using a viral inducible vector. The dead Cas9 endonuclease may be fused to an epigenetic modification enzyme (also referred to as an “effector protein”) or active fragment thereof.

Exemplary effector proteins include KRAB, VPR, p65 VP64, HSF1, p300, DNMT3A, TET1, EZH2, G9a SUV39H1, HDAC3, LSD1, PRDM9, DOT1L, FOG1, BAF, PYL1, ABI1, CIBN, ADAR2, METTL3, METTL14, ALKBH5, and FTO.

[0194] In some embodiments, the CRISPR-based editing platform comprises a CRISPR/Cas domain. In some embodiments, the CRISPR/Cas domain comprises one or more RNA molecules, which can be a crRNA and/or a tracrRNA and/or optionally, an engineered single guide RNA or sgRNA. In some embodiments, the CRISPR/Cas domain forms a complex with its partner RNA or RNAs. In some embodiments, the CRISPR/Cas domain and RN A complex utilizes RNA-DNA base pairing to determine the binding site to a target nucleic acid. In some embodiments, the CRISPR/Cas domain optionally complexed with its partner sgRNA or sgRNAs binds to a CpG site in a target nucleic acid. In some embodiments, the CRISPR/Cas domain optionally complexed with its partner sgRNA or sgRNAs binds to a protospacer adjacent motif (PAM) sequence in the target nucleic acid. In some embodiments, the PAM sequence is located within a CpG Island in a target nucleic acid.

[0195] In some embodiments, the CRISPR/Cas domain may comprise a CRISPR/Cas protein. In some embodiments, a CRISPR/Cas domain may be derived from a protein involved in a Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) system or have structural and/or functional similarities to a protein involved in the CRISPR system and optionally a guide RNA, e.g., a single guide RNA (sgRNA). Two classes of CRISPR systems have been identified, class 1 and class 2 CRISPR systems. The class 2 CRISPR systems use a single Cas endonuclease (rather than multiple Cas proteins). One class 2 CRISPR system includes a type II Cas endonuclease such as Cas9, a CRISPR RNA (“crRNA”), and a trans-activating crRNA (“tracrRNA”). The crRNA contains a '‘guide RN A”, typically about 20-nucleotide RNA sequence that corresponds to a target DNA sequence. crRNA also contains a region that binds to tlie tracrRNA to form a double-stranded structure which is cleaved by RNase III, resulting in a crRNA/tracrRNA hybrid. A crRNA/tracrRNA hybrid then directs Cas9 endonuclease to recognize and cleave a target DNA sequence. Another class II CRISPR system includes the type V endonuclease Cpfl, which is smaller than Cas9; examples include AsCpfl (from Acidaminococcus sp.) and LbCpfl (from Lachnospiraceae sp.). Cpfl -associated CRISPR arrays are processed into mature crRN As without the requirement of a tracrRNA; m other words, a Cpfl system requires only Cpfl nuclease and a crRNA to cleave a target DNA sequence. The CRISPR/Cas protein may be selected from a type I, type II, type III, type IV, type V Cas protein, and type VI Cas protein. The CRISPR/Cas protein may be selected from Casl, CaslB, Cas2, Cas3, Cas4, Cas5, Cas5d, Cas5t, Cas5h, Cas5a, Cas6, Cas7, Cas8, Cas8a, Cas8b, Cas8c, Cas9, CaslO, Casl Od, Casl 2a/Cpfl, Casi2b/C2cl, Casl2c/C2c3, Casl2d/CasY, Casl2e/CasX, Cas 12g, CasI2h, CasI2i, Casl2j (Cas-phi2), Csyl , Csy2, Csy3, Csy4, Csel, Cse2, Cse3, Cse4, Cse5e, Cscl, Csc2, Csa5, Csnl, Csn2, ( ism 1, Csm2, Csm3, Csm4, Csm5, Csm6, Cmrl, Cmr3, Cmr4, Cmr5, Cmr6, Csbl, Csb2, Csb3, Csxl7, Csx14, CsxlO, Csxl6, CsaX, Csx3, Csxl, CsxlS. Csxll, Csfl, Csf2, CsO, Csf4, Csdl, Csd2, Cstl, Cst2, Cshl , Csh2, Csal. Csa2, Csa.3, Csa4, Csa5, AsCasl2a, Cas 13a, Cas 13b, Cas 13c, Casl 3d, Casl3X, Casl3Y, LbCasl2a, HypaCas9, a Type I Cas effector protein, a Type II Cas effector protein, a Type III Cas effector protein, a Type IV Cas effector protein, a Type V Cas effector protein, a Type VI Cas effector protein, CARF, DinG, Cpfl, Casi2b/C2cl , Casl2c/C2c3, Casl2b/C2cl, and functional fragments and derivatives thereof. In some embodiments, the CRISPR/Cas protein may be or comprise a Cas9 ortholog The Cas9 protein may be selected from SpCas9, SaCas9, ScCas9, StCas9, NmCas9, VRERCas9, VERCas9, xCas9, espCas91 .0, espCasl.l, Cas9HFl , hypaCas9, evoCas9, HiFiCas9, and CjCas9. In some embodiments, the CRISPR/Cas protein may be or comprise a Cas 12 ortholog. The Cas 12 protein may be selected from Cpfl, FnCasl2a, LbCasl2a, AsCasl2a, LbCasl2a, TsCasl2a, SaCasl2a, Pb2Casl2a, PgCasl2a, MiCasl2a, Mb2Casl2a, Mb3Casl2a, Lb4Casl2a, Lb5Casl2a, FbCasl2a, CpbCasl2a, CrbCasl2a, CMaCasl2a, BsCasl2a, BfCasl2a, BoCasl2a. In some embodiments, the CRISPR/Cas protein may be derived from a bacteria or has one or more components derived from a bacteria, and wherein the one or more components may optionally be derived from different bacteria. The bacteria origin of the CRISPR/Cas protein of each of die epigenetic effectors may be selected from Streptococcus pyogenes, Streptococcus thermophilus, Streptococcus sp., Staphylococcus aureus, Nocardiopsis dassonvillei, Streptomyces pristinae spiralis, Streptomyces viridochromo genes, Streptomyces viridochromogenes, Streptosporangium roseum, Streptosporangium roseum, AlicyclobacHlus acidocaldarius, Bacillus pseudomycoides, Bacillus selenitireducens, Bacillus niameyeiisis, Bacillus okhensis, Capnocytophaga cams, Chryseobacterium gallinarum, Coriobacterium_glomerans_PW2, Dechloromonas denitrificans, Enterococcus cecorum, Enterococcus faecium, Enterococcus italicus, Eubacterium dolichum, Eubacterium sp., Eggerthelia sp. YY7918, Exiguobacterium sibincum, Flavobacterium frigidarium, Facklamia hominis, Fi»egoldia_magna_ATCC_29328, Kingella kingae, Lactobacillus_rhamnosus_LOCK900, Lactobacillus delbrueckii, Lactobacillus salivarius, Lactobacillus sp., Microscilia marina. Mycoplasma gailisepticum CA06, Neisseria meningitidis, Omithobactenum rhinotracheale, Burkholdenales bacterium, Polaromonas naphthalenivorans, Polaromonas sp., Pediococcus acidilactici, Prevotella histicola, Parabacteroides sp., Streptococcus_agalactiae_NEM316, Streptococcus dysgalactiae subsp. equisimilis AC-2713, Streptococcus equinus, Streptococcus gallolyticus, Streptococcus gordonii, Streptococcus mutans GS-5, Streptococcus macedonicus, Streptococcus ratti, Streptococcus_salivarius_JTM8777, Streptococcus sinensis. Streptococcus suis D9, Streptococcus thermophilus LMG 18311, Tissierellia bacterium KA00581, Treponema denticola ATCC 35405, Treponema putidum, Turicibacter sp., Veillonella parvula ATCC 17745, Weeksella virosa, Streptococcus equi, Streptococcus agalactiae, Lactobacillus animalis KCTC 3501, Listeria monocytogenes, Lachnospiraceae bacterium ND2006, Acidaminococcus sp. BV3L6, Helcococcus kunzii, Prevotella ihumii, Prevotella bryantii B14, Compost ..meta __GaOO79224_ _100045232_ - _CRISPR associated_protein,_Csn 1 _femily_CDSjranslation_Compost_meta, Geyser Hotspring.. Yellowstone. _Ga0078972 1022257 ■ CRISPR- associated_protein,_Csnl_family_CDS_traiislation_Coinmwrity_metagenome, Geyser- Hotspring_Yellowstone_Ga0078972_1010018 -_CRISPR- associaled protein, Csnl family ...CDS translation Community metagenome, Crocosphaera watsonii, Cyanothece sp., Microcystis aeruginosa, Pseudomonas aeruginosa, Synechococcus sp., Acetohaiobium arabaticum, Ammonifex degensii, Caldicelulosiruptor becscii, Candidates Desulforudis, Clostridium botulinum, Clostridium difficile, Clostridium Tyrobutyricum, Clostridium beijerinckii, Clostridium perfringens, Clostridium autoethanogenum, Finegoldia magna, Natranaerobius thermophilus, Methanococcus maripaludis, Pelotomaculum thermopropionicum, Acidithiobacillus caldus. Lactobacillus crispatus, Acidithiobacillus ferrooxidans, Acidaminococcus intestine RyC-MR95, Allochromatium vinosum, Marinobacter sp., Nitrosococcus halophilus, Nitrosococcus watsoni, Pseudoalteromonas haloplanktis, Ktedonobacter racemifer, Methanohalobium evestigatum, Streptococcus thermophilus. Lactococcus lactis, Staphylococcus epidermidis Anabaena variabilis, Nodularia spumigena, Nostoc sp., Arthrospira maxima, Arthrospira platensis, Arthrospira sp., Lyngbya sp , Microcoleus chthonoplastes, Oscillatoria sp.. Petrotoga mobilis, Thermosipho africanus, Clostridium acetobutylicum , Synechococcus elongates UTEX 2973, Actinoplanes sp., B. subtilis, Corynebacterium glutamicum, Streptomyces sp., Clostridium difficile, Clostridium saccharoperbutylacetonicum Nl-4, Acaryochloris marina, Leptotrichia shahii, and Francisella novicida.

[0196] The CRISPR/Cas protein may be derived from a virus, e.g , a phage vims, e.g., a bacteriophage, e.g., a Biggievirus or has one or more components derived from a vims, e.g., a phage virus, e.g., a bacteriophage, e.g., a Biggievirus and wherein the one or more components may optionally be derived from different virus.

[0197] In some embodiments, die CRISPR/Cas domain comprises a modified form of a wildtype Cas protein. The modified form of the w ild-type Cas protein can comprise one or more amino acid changes (e.g., deletion, insertion, or substitution). In some embodiments, the endonuclease domain may comprise one or more amino acid substitutions as compared to a wild-type endonuclease domain. In some embodiments, the CRISPR/Cas domain comprises an endonuclease domain that has modified or reduced nuclease activity as compared to a wild-type protein. For example, the endonuclease domain can have less than 90%, less than 80%, less than 70%, less than 60%, less than 50%, less than 40%, less than 30%, less than 20%, less than 10%, less than 5%, or less than 1% nuclease activity of the wild-type Cas protein. In some embodiments, the CRISPR/Cas domain comprises a catalytically inactive CRISPR/Cas protein (e.g., dCas9) or a CRISPR/Cas protein with substantially reduced nuclease activity⁷ compared to a wild-type CRISPR/Cas protein. Many catalytically inactive CRISPR/Cas proteins are known in the art. A catalytically inactive CRISPR/Cas protein or a CRISPR/Cas protein that has reduced DMA cleavage activity with respect to both strands of a double-stranded target DNA can result from deletion or mutation of all of the nuclease domains of a CRISPR/Cas protein (e.g., both RuvC and HNH nuclease domains in a Cas9 protein; RuvC nuclease domain in a Cpfl protein). For example, a catalytically inactive S. pyogenes Cas9 can result from a DI0A (aspartate to alanine at position 10) mutation in the RuvC domain and H939A (histidine to alanine at amino acid position 839) or H840A (histidine to alanine at amino acid position 840) in the HNH domain A catalytically inactive CRISPR/Cas protein (e.g., dCas, dCas9) can bind to a target polynucleotide but may not cleave the target polynucleotide. Examples of mutations in Cas9 include but are not limited to D10A, DI 1A, D16A, D17A, H557A, H558A, H588A, N61 1 A, N612A, H589A, H820A, H821A, D839A, H840A, N863A, N864A, D917A, D918A, H969A, H970A, E993A.E994A, N995A, N996A, El 006A, E1007A, D1255A, DI 256A, or any combination thereof. In some embodiments, a spCas9 mutation include e.g., D10A/H820A, DIOA, D10A/D839A/H840A, and D10A/D839A/H840A/N863A or any combination thereof.

[0198] In some embodiments, the CRISPR/Cas domain comprises a CRISPR/Cas domain that has single strand DNA cleavage activity when contacted with a double stranded DNA sequence. In some embodiments, the CRISPR/Cas domain comprises a CRISPR/Cas domain (i.e., a nickase) that can generate a single-strand break but not a double-strand break. Many CRISPR/Cas nickases are known in the art. A CRISPR/Cas nickase can result from deletion or mutation of one of the nuclease domains in a Cas protein comprising at least two nuclease domains (e.g., Cas9). For example, an S. pyogenes Cas9 nickase can result from a D10A (aspartate to alanine at position 10) mutation m the RuvC domain or a H839A (histidine to alanine at amino acid position 839) or H840A (histidine to alanine at amino acid position 840) mutation in the HNH domain.

[0199] In some embodiments, a Cas protein described herein is a mature Cas protein, e.g., lacking aN terminal methionine. A Cas protein can be a chimeric Cas protein that is fused to oilier proteins or polypeptides. A Cas protein can be a chimera of various Cas proteins, for example, composing domains of Cas proteins from different organisms. In some embodiments, a Cas9 is a chimeric Cas9, e g., modified Cas9, e.g., synthetic RNA-guided nucleases (sRGNs), eg., modified by DNA family shuffling, e.g., sRGN3.1, sRGN3.3. In some embodiments, the DNA family shuffling comprises, fragmentation and reassembly of parental Cas9 genes, e.g., one or more of Cas9s from Staphylococcus hyicus (Shy), Staphylococcus lugdunensis (Siu), Staphylococcus microti (Smi), and Staphylococcus pasteuri (Spa).

[0200] PAM sequences: A target DNA sequence must generally be adjacent to a “protospacer adjacent motif’ (“PAM”) that is specific for a given Cas endonuclease; however, PAM sequences appear throughout a given genome. In some embodiments, the PAM is required for target binding of the Cas protein. The specific PAM sequence required for Cas protein recognition may depend on the specific type of the Cas protein. A PAM can be 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more nucleotides in length. In some embodiments, a PAM is between 2-6 nucleotides in length. In some embodiments, the PAM can be a 5’ PAM (i.e., located upstream of the 5’ end of the protospacer). In some embodiments, the PAM can be a 3’ PAM (i.e., located downstream of the 5‘ end of the protospacer). In some embodiments, the Cas protein of a prime editor recognizes a canonical PAM, for example, a SpCas9 recognizes 5’-NGG-3’ PAM. In some embodiments, a Cas protein described herein has altered PAM specificity. In some embodiments, a Cas protein described herein may have one or mutations in a PAM recognition motif. Examples of specific PAM sequences are provided in Table 1 below. As used in PAM sequences in Table 1 and consensus sequences of exemplary’ promoter elements in Table 13, “N” refers to any one of nucleotides A, G, C, and T, “R” refers to nucleotide A or G, “Y” refers to nucleotide C or T, “W” refers to nucleotide A or T, “K” refers to nucleotide G or T, “M” refers to nucleotide A or C, “B” refers to nucleotide C or G or T, “D” refers to nucleotide A or G or T, “II” refers to nucleotide A or C or T, and “V” refers to nucleotide A or C or G.

Table 1 — Exemplary PAM Sequences of CRISPR/Cas Proteins

Streptococcus gordonii str. ; Sgo \ NNAAAG : A46

; Challis substr. CHI : :

OMEGA domains

[0201] In some embodiments, a nucleic acid binding moiety may be or comprise a domain from an obligate mobile element-guided activity (OMEGA) system or an engineered variant thereof. The OMEGA domain can comprise an RNA-programmable nuclease domain. In some cases, the OMEGA domain can comprise a distinct transposon-encoded protein domain, for example, an IscB domain, an IsrB domain, an IshB domain, or an I'npB domain. Idle OMEGA domain can be an ancestor or a variant of an ancestor of a CRISPR nuclease domain, for example, a Cas9 domain or a Casl2 domain. An IscB domain or an TnpB domain can be encoded in a family of IS200/IS605 transposons. The OMEGA domain can comprise a nuclease domain . In some cases, the OMEGA domain comprises a RuvC domain or an HNH domain. In some cases, the OMEGA domain comprises a RuvC domain and an HNH domain. In other cases, die OMEGA domain can comprise an HNH domain but no RuvC domain. The OMEGA domain can further comprise a PLMP domain. In some cases, the OMEGA domain is catalytically active. The OMEGA domain can, for example, comprise nickase activity. Hie OMEGA domain can be mutated to be deficient in nuclease activity. In some cases, the OMEGA domain is catalytically inactive.

[0202] In some cases, the OMEGA domain can comprise RNA-guided activity. In some cases, an OMEGA domain can comprise an RNA-guided nuclease. An OMEGA domain can be capable of specifically interacting with or binding to a specific noncoding RNA, for example, an ®RNA. The noncoding RNA can be configured to recruit the OMEGA domain to a specific target sequence, for example, by hybridization of a segment of the noncoding RNA to the target sequence. In some cases, hybridization of the segment of the nonRNA to the target sequence triggers the OMEGA domain to activate its nuclease domain and carry out double-stranded ONA cutting or a single-stranded DNA nick at the target sequence. In some cases, the noncoding RN A that interacts with the OMEGA domain comprises a CRISPR repeat sequence or a sequence from a CRISPR array. In some cases, the OMEGA domain is associated with a CRISPR array. In some cases, the OMEGA domain is capable of associating with a particular target adjacent motif (TAM). The OMEGA domain may require binding to the TAM in order to activate its RNA-guided activity.

[0203] In some embodiments, an OMEGA domain is a part of an epigenetic effector described elsewhere herein. In some embodiments, an OMEGA domain is a part of a blocking reagent described elsewhere herein. An OMEGA domain can be the nucleic acid binding domain of an epigenetic effector. An OMEGA domain can be coupled to an effector moiety described elsewhere herein, for example, as a fusion protein. Alternatively, an OMEGA domain can be the nucleic acid binding domain of a blocking reagent described elsewhere herein.

Fanzor domain

[0204] In some embodiments, a nucleic acid binding moiety may be or comprise a Fanzor domain. The Fanzor domain can comprise an RNA-programmable nuclease domain. In some cases, the Fanzor domain is derived from a eukaryotic cell or an engineered variant thereof. The Fanzor domain can be derived from a metazoan, fungus, choanoflagellate, algae, rhodophyta, a unicellular eukaryote, plant, or animal. In further cases, the Fanzor domain is derived from a virus or an engineered variant, thereof. For example, the Fanzor domain can be derived from Phycodnavindae, Ascoviridae, or Mimiviridae . In some cases, the Fanzor domain is derived from the Accmthamoeba polyphaga mimwims,Mercenaria tnercenaria, Dreissena polymorpha, Batillaria attramentaria^ Klebsormidium nitens, or Chlamydomonas reinhardtii. The Fanzor domain can comprise a homolog of a TnpB domain. A Fanzor domain can be capable of associating with a eukaryotic transposase. In some cases, a Fanzor domain is capable of associating with a LINE, CMC, Crypton, Mariner/Tcl, hAT, IS607, EnSpm, Sola, or Helitron transposon. The Fanzor domain can comprise a nuclease domain. In some cases, the Fanzor domain comprises a RuvC domain. The Fanzor domain can further comprise a WED domain. In some cases, the Fanzor domain is catalytically active. The Fanzor domain can, for example, comprise nickase activity. Tire Fanzor domain can be mutated to be deficient in nuclease activity. In some cases, the Fanzor domain is catalytically inactive.

[0205] In some cases, the Fanzor domain can comprise RNA-guided activity. In some cases, an Fanzor domain can comprise an RNA-guided nuclease. A Fanzor domain can be capable of specifically interacting with or binding to a specific noncoding RNA, for example, an coRNA. The noncoding RNA can be configured to recruit the Fanzor domain to a specific target sequence, for example, by hybridization of a segment of the noncoding RN A to the target sequence. In some cases, hybridization of the segment of the nonRNA to the target sequence triggers the Fanzor domain to activate its nuclease domain. In some cases, an activated Fanzor domain carries out double-stranded DNA cuting or a single-stranded DNA nick at the target sequence. In some cases, the Fanzor domain is capable of associating with a particular target adjacent motif (TAM). Tire Fanzor domain may require binding to the TAM in order to activate its RNA-guided activity. The Fanzor domain can be smaller in size compared to a CR ISPR Cas9 protein or a CRISPR Casl2 protein.

[0206] In some embodiments, a Fanzor domain is a part of an epigenetic effector described elsewhere herein. In some embodiments, a Fanzor domain is a part of a blocking reagent described elsewhere herein. A Fanzor domain can be the nucleic acid binding domain of an epigenetic effector. A Fanzor domain can be coupled to an effector moiety described elsewhere herein, for example, as a fusion protein. Alternatively, a Fanzor domain can be the nucleic acid binding domain of a blocking reagent described elsewhere herein. Zinc finger domains

[0207] In some embodiments, a nucleic acid binding moiety may be or comprises a Zn finger domain. Zn finger proteins and methods for design and construction of fusion proteins are know’ll to those of skill in the art. The Zn finger domain may comprise or consist essentially of or consist of 1-10, 1-9, 1-8, 1-7, 1-6, 1-5, 1-4, 1 -3, 1-2, 2-10, 2-9, 2-8, 2-7, 2-6, 2-5, 2-4, 2-3, 3- 10, 3-9, 3-8, 3-7, 3-6, 3-5, 3-4, 4-10, 4-9, 4-8, 4-7, 4-6, 4-5, 5-10, 5-9, 5-8, 5-7, 5-6, 6-10, 6-9, 6- 8, 6-7, 7-10, 7-9, 7-8, 8-10, 8-9, or 9-10 zinc fingers. Zn finger proteins and/or multi fingered Zn finger proteins may be linked together, e.g., as a fusion protein, using any suitable linker sequences. The Zn finger domain may include any combination of suitable linkers between the individual Zn finger proteins and/or multi -fingered Zn finger proteins of the Zn finger molecule.

[0208] Hie Zn finger domain of an epigenetic effector may comprise a Zn finger molecule comprising an engineered zinc finger protein that binds (in a sequence- specific manner) to a DNA sequence in a target nucleic acid. Engineering methods include, but are not limited to, rational design and various types of selection. Rational design includes, for example, using databases comprising triplet (or quadruplet) nucleotide sequences and individual Zn finger amino acid sequences, in which each triplet or quadruplet nucleotide sequence is associated with one or more amino acid sequences of zinc fingers which bind the particular triplet or quadruplet sequence. See, for example, U.S. Pat. Nos. 6,453,242 and 6,534,261, incorporated by reference herein in their entireties. Exemplary selection methods, including phage display and two-hybrid systems, are disclosed in U.S. Pat Nos. 5,789,538; 5,925,523; 6,007,988; 6,013,453; 6,410,248; 6,140,466; 6,200,759; and 6,242,568; as well as International Patent Publication Nos. WO 98/37186; WO 98/53057; WO 00/27878; and WO 01/88197 and GB 2,338,237. In addition, enhancement of binding specificity for zinc finger proteins has been described, for example, in International Patent Publication No. WO 02/077227.

[0209] In some cases, aZn finger molecule may comprise a two-handed Zn finger protein. Two handed Zn finger proteins are those proteins in which two clusters of zinc finger proteins are separated by intervening ammo acids so that tire two Zn finger domains bind to two di scontinuous target DNA sequences. An example of a two-handed type of zinc finger binding protein is SIP1, where a cluster of four zinc finger proteins is located at the amino terminus of the protein and a cluster of three Zn finger proteins is located at the carboxyl terminus (Remade et al 1999). Each duster of zinc fingers in these proteins is able to bind to a unique target sequence and the spacing between the two target sequences can comprise many nucleotides. [0210] In some embodiments, the Zn finger domain comprises a ZIM3, ZNF436, ZNF257, ZNF675, ZNF490, ZNF320, ZNF33L ZNF816, ZNF680, ZNF41, ZNF189, ZNF528, ZNF543, ZNF554, ZNF140, ZNF610, ZNF264, ZNF350, ZNF8, ZNF582, ZNF30, ZNF32.4, ZNF98, ZNF669, ZNF677, ZNF596, ZNF677, ZNF596, ZNF214, ZNF37A, ZNF34, ZNF250, ZNF547, ZNF273, ZNF354A, ZNF82, ZNF224, ZNF33A, ZNF45, ZNF175, ZNF595, ZNF184, ZNF419, ZNF28-1, ZNF28-2, ZNF18, ZNF213, ZNF394, ZNFT, ZNF14, ZNF416, ZNF557, ZNF566, ZNF729, ZIM2. ZNF254, ZNF764, ZNF785, ZNF10 (KOX1), ZFP28, ZN334, ZN568, ZN37A, ZN181, ZN510, ZN862, ZN140, ZN208, ZN248, ZN571, ZN699, ZN726, ZIK1, ZNFT, Z705F, ZNF14, ZN471, ZN624, ZNF84, ZNF7, ZN891, ZN337, Z705G, ZN529, ZN729, ZN419, Z705A, ZNF45, ZN302, ZN486, ZN621, ZN688, ZN33A, ZN554, ZN878, ZN772, ZN224, ZN184, ZN544, ZNF57, ZN283, ZN549, ZN211, ZN615, ZN253, ZN226, ZN730, Z585A, ZN732, ZN681, ZN667. ZN649, ZN470. ZN484, ZN431, ZN382, ZN254, ZN124, ZN607, ZN317, ZN620, ZN141, ZN582. ZN540, ZN75D, ZN555, ZN658, ZN684, ZN829, ZN582, ZN112, ZN716, ZN350, ZN480, ZN416. ZNF92, ZNIOO, ZN736, ZNF74, ZN443, ZN195, ZN530, ZN782, ZN791, ZN331, Z354C, ZN157, ZN727, ZN550, ZN793, ZN235, ZNF8, ZN724, ZN573, ZN577, ZN789, ZN718, ZN300, ZN383, ZN429, ZN677, ZN850, ZN454, ZN257, ZN264, ZFP82, ZFP14, ZN485, ZN737, ZNF44, ZN596, ZN565, ZN543, ZFP69 , ZNF12, ZN169, ZN433, ZNF98, ZN175, ZN347, ZNF25, ZN519, Z585B, ZIM3, ZN517, ZN846, ZN230, ZNF66, ZFP1, ZN713, ZN816, ZN426, ZN674, ZN627, ZNF20, Z587B, ZN316, ZN233, ZN611, ZN556, ZN234, ZN560, ZNF77, ZN682, ZN614, ZN785, ZN445, ZFP30, ZN225, ZN551, ZN610, ZN528, ZN284, ZN418, ZN490, ZN805, ZN80B, ZN763, ZN285, ZNF85, ZN223, ZNF90, ZN557, ZN425, ZN229, ZN606, ZN155, ZN222, ZN442, ZNF91, ZN135, ZN778, ZN534, ZN586, ZN567, ZN440, ZN583, ZN441, ZNF43, ZNF589, ZNF10, ZN563, ZN561, ZN136, ZN630, ZN527, ZN333, Z324B, ZN786, ZN709, ZN792, ZN599, ZN613, ZF69B, ZN799. ZN569, ZN564. ZN546, ZFP92, YAF2, ZN723, ZNF34, ZN439, ZFP57, ZNF19, ZN404, ZN274, CBX3, ZNF30, ZN250, ZN570, ZN675, ZN695, ZN548, ZNL32, ZN738, ZN420, ZN626, ZN559, ZN460, ZN268, ZN304, ZIM2, ZN605, ZN844, ZN101, ZN783, ZN417, ZNI82, ZN823, ZN177. ZN197, ZN717, ZN669, ZN256, ZN251, ZN562, ZN461, Z324A, ZN766, ZN473, ZN496, ZN597, ZN274, ZN783, ZN840, ZN777, ZN212, ZN214, ZN764, ZNF17, ZN282, ZNF8L or ZN298 domain.

TAL domains

[0211] In some embodiments, a nucleic acid binding moiety is or comprises a TAL domain, A TAL domain is derived from a TAL effector molecule that specifically binds a DNA sequence. TAL effectors typically comprise a plurality of TAL effector domains or fragments thereof, and optionally one or more additional portions of naturally occurring TAL effectors (e.g., N- and/or C -terminal of the plurality of TAL effector domains). More than 113 TAL effector sequences are known to date. Non-limiting examples of TAL effectors from Xanthomonas include Hax2, Hax3, Hax4, AvrXa7, AvrXalO and AvrBs3. Many TAL domains are known to those of skill in the art and are commercially available.

[0212] TAL effectors comprise a central repeat domain of tandemly arranged repeats (the repeat- variable di-residues, RVD domain) that determine the specific binding of TAL effectors. These repeats are typically 33 or 34 amino acids. Different TAL effectors may have a different number of repeats (typically ranging from 1 ,5 to 33.5 repeats) and a different order of their repeats. The C-terminal repeat is usually shorter in length (e.g., about 20 amino acids) and is generally referred to as a “half-repeal”. Each repeat of the TAL effector generally correlates to one base-pair in the target DNA sequence with different repeat types exhibiting different basepair specificity . A smaller number of repeats generally results in weaker protein-DNA interactions. A number of 6.5 repeats in a TAL effector has been shown to be sufficient to activate transcription of a reporter gene (Scholze et ah, 2.010).

[0213] Many variations between repeats occur at amino acid positions 12 and 13, which have been termed “hypervariable” and are responsible for the specificity of the interaction with the target DNA promoter sequence, as shown in Table 2 listing exemplary' repeat variable diresidues (RVD) and their corresponding nucleic acid base targets.

Table 2 — RVDs and Nucleic Acid Base Specificity

[0214] 1 lie RVD NK has also been shown to target G. Many target sites of TAL effectors also include a T flanking the 5' base targeted by the first repeat.

[0215] In some embodiments, the TAL domain described herein may be derived from a TAL effector from any bacterial species (e.g., Xanthomonas species such as the African strain of Xanthomonas oryzae pv. Oryzae (Yu et al. 2011), Xanthomonas campestris pv. raphani strain 756C and Xanthomonas oryzae pv. oryzzco /a strain BLS256 (Bogdanove et al. 2011). In som< embodiments, the TAL domain comprises an RVD domain as well as flanking sequence(s) (sequences on the N-terminal and/or C-terminal side of the RVD domain) also from the naturally occurring TAL effector. It may comprise more or fewer repeats than the RVD of the naturally occurring TAL effector. The TAL domain can be designed to target a given nucleic acid sequence based on Table 2 and other nucleic acid base specificities known in the art. The TAL domain of an epigenetic effector can comprise a number of TAL effector domains (e.g., repeats (monomers or modules)) selected based on the desired binding site to a target nucleic acid. TAL effector domains, e.g., repeats, may be removed or added m order to suit a specific binding target sequence In some cases, the TAL domain of an epigenetic effector may comprise between 6.5 and 33.5 TAL effector domains, e.g., repeats. In some cases, TAL domain of an epigenetic effector may comprise between 8 and 33.5 TAL effector domains, between 10 and 25 TAL effector domains, or between 10 and 14 TAL effector domains. In some cases, the TAL domain of an epigenetic effector may comprise TAL effector domains that correspond to a perfect match to the DNA target sequence. In some cases, the TAL domain of an epigenetic effector may comprise a mismatch between a repeat and a target base-pair in the target nucleic acid as along as it allows for the function of the epigenetic effector comprising the TAL effector molecule. In some cases, the TAL domain of an epigenetic effector comprises no more than 7 mismatches, 6 mismatches, 5 mismatches, 4 mismatches, 3 mismatches, 2 mismatches, or 1 mismatch, and optionally no mismatch, with the target DNA sequence. In general, TAL binding is inversely correlated with the number of mismatches. Without wishing to be bound by theory', in general the smaller the number of TAL effector domains in the TAL domain of the epigenetic effector, the smaller the number of mismatches will be tolerated and still allow for the function of the epigenetic effector comprising the TAL domain. The binding affinity' of the TAL domain to the target nucleic acid is thought to depend on the sum of matching repeat-DNA combinations. For example, TAL effector molecules having 25 TAL effector domains or more may be able to tolerate up to 7 mismatches.

[0216] In addition to the TAL effector domains, the TAL domain of an epigenetic effector may comprise additional sequences derived from a naturally occurring TAL, effector. 'The length of the C-terminal and/or N-terminal sequence(s) included on each side of the TAL effector domain portion of the TAL domain can vary and be selected by one skilled in the art. For example, a number of C-terminal and N-terminal truncation mutants in Hax3 derived TAL -effector based proteins have been characterized (Zhang et al, 201 1) and key elements have been identified that contribute to optimal binding to the target sequence and activation of transcription.

Transcriptional activity was generally found to inversely correlate with the length of N-termimis. On the C -terminus side, an important element for DNA binding residues was identified within the first 68 amino acids of the Hax 3 sequence. Accordingly, in some cases, the first 68 amino acids on the C-terminal side of the TAL effector domains of the naturally occurring TAL effector may be included m the TAL domain of the epigenetic effector. In some cases, a TAL domain in an epigenetic effector comprises 1) one or more TAL effector domains derived from a naturally occurring TAL effector; 2) at least 70, 80, 90, 100, 110, 120, 130, 140, 150, 170, 180, 190, 200, 220, 230, 240, 250, 260, 270, 280 or more ammo acids from the naturally occurring TAL effector on the N -terminal side of the TAL effector domains; and/or 3) at least 68, 80, 90, 100, 110, 120, 130, 140, 150, 170, 180, 190, 200, 220, 230, 240, 250, 260 or more amino acids from the naturally occurring TAL effector on the C-terminal side of the TAL effector domains.

[0217] It is possible to modify the repeats to target specific DNA sequences. In some embodiments, the TAL effector domain of an epigenetic effector can be engineered to carry the epigenetic effector to desired target sites.

Linkers

[0218] In some embodiments, tire epigenetic effector further comprises a linker, e.g., a linker connecting the domains of the epigenetic effector. . In some cases, a I inker may connect a polypeptide to another polypeptide. Tn some cases, a linker may connect a polypeptide to a nucleic acid. In some cases, a linker may connect a nucleic acid to another nucleic acid. In some cases, a linker connects the nucleic acid binding domain and the effector domain of an epigenetic effector. A linker may be a chemical bond. In some cases, a linker may be a covalent bond. In oilier cases, a linker may be a noncovalent bond. In some cases, a linker may be a peptide linker. In some cases, a peptide linker may be at least 2, 3, 4, 5, 6, 7, 8, 9, 10 or more amino acids in length. In some cases, a linker may be a rigid linker. As well known by one of skill in the art, rigid linkers may comprise an alpha helix structure or Pro-rich sequence. Rigid linkers maintain a substantially fixed spatial distance between domains. In other cases, a linker may be a flexible linker As well known by one of skill in the art, flexible linkers may comprise small amino acids (e.g., Gly, Ser, or Ala). Flexible linkers allow the domains they connect to have flexibility of movement relative to each other. In some cases, a linker may be a cleavable linker. Cleavable linkers may utilize the reversible nature of a disulfide bond. In some cases, a cleavable linker compri ses a cleavage site motif for a protease. In some cases, a cleavable linker may be a self-cleaving linker. In vivo cleavage of linkers in compositions described herein may be cleaved in specific conditions. Nuclear Localization Sequence (NLS)

[0219} some instances, an epigenetic effector described herein may comprise one or more nuclear localization sequences (NLS) (e.g., an SV40 NLS). In some cases, the one or more NLS facilitates the import of the epigenetic effector comprising an NLS into the cell nucleus. In some cases, the epigenetic effector may comprise 1 NLS. In some cases, the epigenetic effector may comprise 2 NLSs. In some cases, the polypeptide may comprise 3 NLSs. In other cases, the epigenetic effector may comprise more than 3, 4, 5, 6, 7, 8, 9, or 10 NLSs. In some cases, the NLS is located at the N-terminus, C-terminus, or in an internal region of the epigenetic effector. In some cases, an NLS is fused to the N-terminus of the nucleic acid binding domain of an epigenetic effector described herein. In some cases, an NLS is fused to the C-terminus of the nucleic acid binding domain of an epigenetic effector. In some cases, an NLS is fused to the N- terminus of the effector domain of an epigenetic effector. In some cases, an NLS is fused to the C-terminus of the effector domain of an epigenetic effector. In some cases, the nucleic acid binding domain of the epigenetic effector does not comprise an NLS. In some cases, the effector domain of the epigenetic effector does not comprise an NLS. In some cases, an NLS is fused to the N-terminus of a CRISPR/Cas effector protein. In some cases, an NLS is fused to the C- terminus of a CRISPR/Cas effector protein. Examples of NLS are provided in Table 24 below.

Table 24- Exemplary NLS Sequences

Epigenetic modifying systems

[0220] In some aspects, the present disclosure provides an epigenetic modifying system comprising one or more compositions described elsewhere herein. The epigenetic modifying system can comprise, for example, one or more epigenetic effectors, one or more blocking reagents, or combinations thereof. In some cases, the epigenetic modifying system comprises orthogonal epigenetic effectors or epigenetic effectors that do not cross-react.

Epigenetic modifying systems comprising an epigenetic effector and a blocking reagent

[0221] In some aspects, the present disclosure provides an epigenetic modifying system comprising an epigenetic effector configured to bind to a target site as described elsewhere herein and a blocking reagent configured to bind to an off-target genomic site as described elsewhere herein. Tire epigenetic modifying system can be used for a method of reprogramming a cell as described elsewhere herein. In some cases, the epigenetic modifying system can comprise a CRISPR-Cas-associated epigenetic effector and a CRISPR-Cas-associated blocking reagent In some cases, the CRISPR-Cas associated epigenetic effector and the CRISPR-Cas associated blocking reagent comprise orthogonal CRISPR systems. In other cases, the epigenetic modifying system can comprise a TALE-associated epigenetic effector and a TALE-associated blocking reagent. In further cases, the epigenetic modifying system can comprise a zinc finger- associated epigenetic effector and a zinc finger-associated blocking reagent. In some cases, the epigenetic modifying system can comprise a CRISPR-Cas-associated epigenetic effector and a TALE-associated blocking reagent. In some cases, the epigenetic modifying system can comprise a CRISPR-Cas-associated epigenetic effector and a zinc finger-associated blocking reagent In other cases, the epigenetic modifying system can comprise a TALE-associated epigenetic effector and a CRISPR-Cas-associated blocking reagent. In further cases, the epigenetic modifying system can comprise a TALE-associated epigenetic effector and a zinc finger-associated blocking reagent. In some cases, the epigenetic modifying system can comprise a zinc finger-associated epigenetic effector and a CRISPR-Cas-associated blocking reagent. In oilier cases, the epigenetic modifying system can comprise a zinc finger-associated epigenetic effector and a TALE-associated blocking reagent.

Epigenetic modifying systems with orthogonal CRISPR/Cas domains

[0222] Many potentially high impact therapeutic inventions and biotechnologies rely on efficacious methodologies for manipulating nucleic acids, including both epigenetic and genetic modifications. The use of orthogonal Cas systems in epigenetic editing can facilitate the implementation of multiplex and concurrent modification at different target sites. Such systems can carry out two-way epigenetic alterations targeting multiple sites or bidirectional epigenetic editing. For instance, multiple epigenetic sites can be targeted to turn on and/or turn off gene expression at multiple sites simultaneously. For example, a first epigenetic site can be targeted to turn on gene expression of a first gene while a second epigenetic site can be targeted to turn off gene expression of a second gene. In some cases, multiple epigenetic sites are targeted to turn on and/or turn off gene expression at multiple sites sequentially. Another application of orthogonal Cas systems is for simultaneous editing of one target site while blocking one or more off-target sites to reduce off-target impacts. This can be achieved through use of combinations of orthogonal Cas systems, wherein one or more orthogonal Cas systems can be used to selectively block one or more off-target sites (using guide RNAs that guide the respective Cas protein(s) to bind to the off-target sites, thereby blocking epigenetic editing), while another orthogonal Cas system introduces an epigenetic edit to a specific target site. In some cases, the Cas system used to selectively block one or more off-target sites comprises a catalytically inactive Cas domain (e g,, dCas9 or dCasl 2). In some cases, the Cas system introducing the epigenetic edit comprises an epigenetic effector.

[0223] In some embodiments, the composition comprises a set of epigenetic effectors, e.g., a first epigenetic effector and a second epigenetic effector comprising two CRISPR/Cas domains. In some embodiments, the set of epigenetic effectors comprise two or more orthogonal CRISPR/Cas proteins or two or more CRISPR/Cas proteins that do not cross-read substantially. In some embodiments, the set of epigenetic effectors comprises two CRISPR/Cas proteins selected such that a first tracrRNA sequence interacting with the first CRISPR/Cas protein and a second tracrRNA sequence interacting with the second CRISPR/Cas protein have a phylogenetic distance of exceeding 0.2. In some embodiments, the set of epigenetic effectors comprises a first tracrRNA sequence interacting with the first CRISPR/Cas protein and a second tracrRNA sequence interacting with the second CRISPR/Cas protein having a phylogenetic distance of exceeding 0.2. In some embodiments, predicted cross-reactivity negatively correlates with phylogenetic distance. Phylogenetic distance between protein sequences may be measured using the BLOSUM 62 matrix excluding indeis.

[0224] In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from ain, bni, bok, ccal, cga, cgl, cmel, cpe, dde, ece, edo, efa, eit espl, esp2, ffr, fho, fma, ghy2, ghy4, kki, ian, Imo, Irh, Ispl, lsp2, mga, nme2, sp, orh, pac, phi, psp, sagl, sag2, sdy, seql, seq2, sga, sgo, smu, sma2, spy,sra, ssa, ssi, ssu, sthla, tba, tte, tdu, tpu, tsp, vpa, wpi, cpfl, Ascpfl , hkcasl 2a, picas 12a, Fn3CasI2a, pb2Cas!2a, Casphi-2 and cas!2c-l , and the second CRISR/Cas protein in the set of epigenetic effectors may be selected from ain, bni, bok, ccal, cga, cgl, cmel, cpe, dde, ece, edo, efa, eit espl, esp2, ffr, fho, fina, ghy2, ghy4, kki, lan, Imo, Irh, Ispl, Isp2, mga, nme2, sp, orh, pac, phi, psp, sagl , sag2, sdy, seql, seq2, sga, sgo, smu, sma2, spy.sra, ssa, ssi, ssu, sthla, tba, tie, tdu, tpu, tsp, vpa, wpi, cpfl, Ascpfl, hkcasl 2a, picas 12a, Fn3Casl2a, pb2Casl2a, Casphi-2 and cas! 2c-l . In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from spy, lan, sagl, Imo, Ascapfl, hkcas!2a, picas 12a, Fn3Casl2a, pb2Cas!2a, Casphi-2 and cas!2c-l and the second CRISR/Cas protein in the set of epigenetic effectors may be selected from spy. lan, sagl, Imo, Ascpfl, hkcas!2a, picas!2a, Fn3CasI2a, pb2CasI2a, Casphi-2 and cas!2c-l . In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from spy, lan, sagl, and Imo, and the second CRISR/Cas protein in the set of epigenetic effectors may be selected from Ascpfl, hkcas!2a, picas 12a, Fn3Casl2a, and pb2Casl2a. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from spy, lan, sagl, and Imo, and the second CRISR/Cas protein in the set of epigenetic effectors may be selected from Casphi-2 and casl2c-I. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from Ascapfl, hkcas !2a, picas 12a, Fn3Casl2a, and pb2Cas!2a and die second CRISR/Cas protein in the set of epigenetic effectors may be selected from Casphi-2 and casl2c-l. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from Casphi-2 and pb2CasI2a and the second CRISR/Cas protein in the set of epigenetic effectors may be selected from Casphi-2. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors may be selected from Lan, Lmo and Sagl and the second CRISPR/Cas protein in the set of epigenetic effectors may be a SpyCas9.

[0225] In some embodim ents, the set of epigenetic effectors comprise two or more CRISPR/Cas proteins, wherein the first CRISPR/Cas protein comprises a PAM sequence selected from NRTAW, NNGTAMAY, NNHDAGGDNA, BRTTTTT, BRRTTTW, NCAARC, NARNCCN, NNNNCVGAA, NNNNGYAA, NNGHWAAA, NTGARGNANY, BTGGDATNN, NGGGAH1 NAN, NAAAG, N VARAACCN, NARA' TC, NNGAAAN , NNGAC, NAANARCN, YHHNGTH, NNNNCTAA , NTNTAAWA, NNGWAAYT, NCAAHYBY, NNGAD, NHDTCCA, NCNNTCCN, NNAAARG, NHTAAAA, NARGHWHAGNC, NRATTTT, NGGDAWT, NGGNG, NTAGANANN, NGGDAHT, NNAAAG, NGGDT, NHGYNANA,NGGDAGNN, NNNAGAAA, NHAAAAA, NHTAAAAA, NHGYRAA, NNNATTT, NAAAAY, NATAWNA, NNAAACN, NATARCH, HHAAATD, NGG, NRG, NBGG, TTTV, YYV, KKYV, YTV, NYTV, TBN, and TG and the second CRISR/Cas protein comprises a PAM sequence selected from NRTAW, NNGTAMAY, NNHDAGGDNA, BRTTTTT, BRRTTTW, NCAARC, NARNCCN, NNNNCVGAA, NNNNGYAA, NNGHWAAA, NTGARGNANY, BTGGDATNN, NGGGAHTNAN, NAAAG, NVARAACCN, NARATC, NNGAAAN , NNGAC, NAANARCN, YHHNGTH, NNNNCTAA , NTNTAAW A, NNGWAAYT, NCAAHYBY, NNGAD, NHDTCCA, NCNNTCCN, NNAAARG, NHTAAAA, NARGHWHAGNC, NRATTTT, NGGDAWT, NGGNG, NTAGANANN, NGGDAHT, NNAAAG, NGGDT, NHGYNANA/NGGDAGNN, NNNAGAA A, NHAAAAA, NHTAAAA A, NHGYRAA, NNNATTT, N AAAAY, NATAWNA, NNAAACN, NATARCH, HHAAATD, NGG, NRG, NBGG, TTTV, YYV, KKYV, YTV, NYTV, TBN, and TG. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from NGG, NRG, NBGG, TTTV, YYV, KKYV, YTV, NYTV, TBN, and TG and the second CRISR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from NGG, NRG, NBGG, TTTV, YYV, KKYV, YTV, NYTV, TBN, and TG. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from NGG, NRG, and NBGG , and the second CRISR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from TTTV, YYV, KKYV, YTV, and NYTV. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from NGG, NRG, and NBGG, and the second CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from TBN and TG. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from TTTV, YYV, KKYV, YTV, and NYTV and the second CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from TBN and TG. In some embodiments, the first CRISPR/Cas protein in the set of epigenetic effectors comprises a PAM sequence selected from TBN and NYTV and the second CRISPR/Cas protein in the set of epigenetic effectors comprises a PA M sequence TG.

[0226] In some embodiments, die set of epigenetic effectors comprise two or more CRISPR/Cas proteins, further comprising a first guide RNA and a second guide RNA. In some embodiments, first guide RNA and second guide RNA in the set of epigenetic effectors may be selected such that it does not cross react substantially with the other. In some embodiments, first sgRNA or second sgRNA in the set of epigenetic effectors may comprise a sequence selected from SEQ ID No. 1-4 at 3’ end (Table 4a). In some embodiments, first guide RNA or second guide RNA in the set of epigenetic effectors may comprise a sequence selected from SEQ ID No. 5-10 at 5" end (Table 4a).

Table 4a — guide RNA Sequences

[0227] In some embodiments, the set of epigene tic effectors comprises a first epigenetic effector comprising a first guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a first desired site of epigenetic modification and a second epigenetic effector comprising a second guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a second desired site of epigenetic modification. The first epigenetic effector may be any of the epigenetic effectors with guide RNAs described herein. The second epigenetic effector may be any of the epigenetic effectors with guide RNAs described herein. In some embodiments, the first epigenetic effector in the set of epigenetic effectors comprises a methyl ase and a first guide RNA comprising a sequence complementary' to a DNA sequence within 1 kb from a desired site of methylation, and the second epigenetic effector in the set of epigenetic effectors comprises a demethylase and a second guide RN A comprising a sequence complementary to a DNA sequence within 1 kb from a desired site of demethylation. In some embodiments, the first epigenetic effector in the set of epigenetic effectors comprises a transcriptional activator and a first guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a desired site of transcriptional activation, and the second epigenetic effector in the set of epigenetic effectors comprise a transcriptional repressor and a second guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a desired site of transcriptional repression.

[0228] In some embodiments, a composition comprises a set of epigenetic effectors, e.g., a first epigenetic effector and a second epigenetic effector, comprising: (a) a first guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a first desired site of epigenetic modification, and (b) a second guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a second desired site of epigenetic modification, wherein the first guide RNA interacts with the first epigenetic and the second guide RNA interacts with the second epigenetic effector. In some embodiments, the first effector and the second effector may act concurrently. In some embodiments, the first effector and the second effector may act substantially concurrently. In some embodiments, the first effector and the second effector may act sequentially. In some embodiments, the first effector and the second effector may act sequentially within a time period of about 15 minutes, 30 minutes, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 12 hours, 15 hours, 20 hours, 22 hours, 24 hours or less.

[0229] In some aspects, the disclosure provides in part, a composition for simultaneous nucleic acid modification. In some embodiments, the composition comprises a set of epigenetic effectors comprising a first, epigenetic effector and a second epigenetic effector for simultaneous epigenetic modification at one or more target sites. In some embodiments, the first epigenetic effector induces transcriptional activation at a first target site, and the second epigenetic effector induces transcriptional repression at a second target. In some embodiments, the first epigenetic effector may be capable of increasing methylation at a first target site, and a second epigenetic effector may be capable of decreasing methylation at a second target site. In some embodiments, the first epigenetic effector comprises methylation modifying activity, and the second epigenetic effector comprises methylation modifying activity, wherein tire first and second epigenetic effector have different methylation modifying activity.

[0230] In some embodiments, the set of epigene tic effectors comprises a first epigenetic effector comprising a first guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a first desired site of epigenetic modification and a second epigenetic effector comprising a second guide RN A comprising a sequence complementary' to a DNA sequence within 1 kb from a second desired site of epigenetic modification Tire first epigenetic effector may be any of the epigenetic effectors with guide RNAs described herein. The second epigenetic effector may be any of the epigenetic effectors with guide RNAs described herein. In some embodiments, the first epigenetic effector in the set of epigenetic effectors comprises a metbylase and a first guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a desired site of methylation, and the second epigenetic effector in the set of epigenetic effectors comprises a demethylase and a second guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a desired site of demethylation. In some embodiments, the first epigenetic effector in the set of epigenetic effectors comprises a transcriptional activator and a first guide RNA comprising a sequence complementary to a DNA sequence w ithin 1 kb from a desired site of transcriptional activation, and the second epigenetic effector in the set of epigenetic effectors comprise a transcriptional repressor and a second guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a desired site of transcriptional repression

[0231 j In some embodiments, a composition comprises a set of epigenetic effectors, e.g., a first epigenetic effector and a second epigenetic effector, comprising: (a) a first guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a first desired site of epigenetic modification, and (b) a second guide RNA comprising a sequence complementary to a DNA sequence within 1 kb from a second desired site of epigenetic modification, wherein the first guide RNA interacts with the first epigenetic and tire second guide RNA interacts with the second epigenetic effector. In some embodiments, the first effector and the second effector may act concurrently. In some embodiments, the first effector and the second effector may act substantially concurrently. In some embodiments, the first effector and the second effector may- act sequentially. In some embodiments, the first effector and the second effector may act sequentially within a time period of about 15 minutes, 30 minutes, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours, 6 hours, 7 hours, 8 hours, 9 hours, 10 hours, 12 hours, 15 hours, 20 hours, 22 hours, 24 hours or less.

[0232] In some aspects, the disclosure provides in part, a composition for simultaneous nucleic acid modification. In some embodiments, the composition comprises a set of epigenetic effectors comprising a first epigenetic effector and a second epigenetic effector for simultaneous epigenetic modification at one or more target sites. In some embodiments, the first epigenetic effector induces transcriptional activation at a first target site, and the second epigenetic effector induces transcriptional repression at a second target. In some embodiments, the first epigenetic effector may be capable of increasing methylation at a first target site, and a second epigenetic effector may be capable of decreasing methylation at a second target site. In some embodiments, the first epigenetic effector comprises methylation modifying activity, and the second epigenetic effector comprises methylation modifying activity, wherein the first and second epigenetic effector have different methylation modifying activity.

[0233] The disclosure provides, in part, polynucleotides encoding all epigenetic effectors, effector domains, nucleic acid binding domains, polypeptides, and functional RN As disclosed herein. Methods for design and construction of polynucleotides are known to those of skill in the art. Nucleotides are referred to by their commonly accepted single-letter codes. Unless otherwise indicated, nucleotide sequences are written left to right in 5' to 3' orientation. Nucleotides are referred to herein by their commonly known one-letter symbols recommended by the IUPAC- IUB Biochemical Nomenclature Commission. Accordingly, A represents adenine, C represents cytosine, G represents guanine, T represents thymine, U represents uracil. It will be understood that when a nucleotide sequence is represented by a DNA sequence (e.g., comprising, A, T, G, C), this disclosure also provides the corresponding RNA sequence (e.g., comprising, A, U, G, C) in which “U” replaces “T.” . Non-limiting examples of polynucleotides include coding or noncoding regions of a gene or gene fragment, loci (locus) defined from linkage analysis, exons, introns, messenger RNA (mRNA), transfer RNA (tRNA), ribosomal RNA (rRNA), short interfering RNA (siRNA), short-hairpin RNA (shRNA), micro-RNA (miRNA), ribozymes, cDNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, cell-free polynucleotides including cell- free DNA (cfDNA) and cell-free RNA (cfRNA), nucleic acid probes, and primers. Hie sequence of nucleotides can be interrupted by non-nucleotide components. Delivery Modalities

[0234] The present disclosure provides, in part, compositions and methods for delivering a composition described elsewhere herein to a cell. An epigenetic effector, an epigenetic modifying system, or a blocking reagent described herein can be delivered via a vector into a ceil via a variety of physical, mechanical and chemical methods. Examples include electroporation, chemical transformation, nucleofection, viral transduction, viral transfection, microfluidic techniques, transmembrane internalization assisted by membrane filtration (TRIAMF), and silicon nano blade chips. See Lotfi et al., Recent Advances in CRISPR/Cas9 Delivery Approaches for Therapeutic Gene Editing of Stem Cells. Stem Cell Rev and Rep (2023), which is incorporated by reference in its entirety.

[0235] It should be noted that the epigenetic effectors and effector moieties of the disclosure may be delivered to cells directly as polypeptides, or indirectly via polynucleotide moieties (e.g., DNA, RNA) that may be transcribed and/or translated into polypeptides in the cell .

Vectors

[0236] The present disclosure is further directed, in part, to vectors, e.g , a viral vector and/or a non-viral vector In some embodiments, the vector is a viral vector. Examples of viral vectors include expression vectors, replication vectors, probe generation vectors, and sequencing vectors. In general, a suitable vector contains an origin of replication functional in at least one organism, a promoter sequence, convenient restriction endonuclease sites, and one or more selectable markers. An expression vector may be used to express natural or synthetic nucleic acids by operably linking a nucleic acid encoding the gene of interest to a promoter. Vectors can be suitable for replication and integration in eukaryotes. Typical cloning vectors contain transcription and translation terminators, initiation sequences, and promoters useful for expression of the desired nucleic acid sequence. Viral vectors, including those derived from retroviruses such as lentivinis, are suitable tools to achieve long-term gene transfer since they allow long-term, stable integration of a transgene and its propagation in daughter cells. An expression vector may be provided to a cell in the form of a viral vector. Viral vector technology is well known in the art and described in a variety of virology and molecular biology manuals. Viruses, which are useful as vectors include, but are not limited to, retroviruses, adenoviruses, adeno- associated viruses (AAV), heipes viruses, and lentiviruses.

[0237] An AAV can be AAV1, AAV2, AAV4, AAV5, AAV6, AAV8, AAV9, AAV 10 or any combination thereof. One can select the type of AAV with regard to the cells to be targeted; e.g., one can select AAV serotypes 1, 2, 5 or a hybrid capsid AAV1 , AAV2, AAV5 or any combination thereof for targeting brain or neuronal cells; and one can select AAV4 for targeting cardiac tis-sue. AAV 8 is useful for delivery to the liver.

[0238] In certain instances, recombinant AAV (rAAV) may be used. rAAVs utilizes the cisacting 145-bp ITRs to flank vector transgene cassettes, providing up to 4.5 kb for packaging of foreign DNA.

[0239] In some embodiments, a vector comprises an expression cassette comprising the nucleic acid encoding a protein or functional RN A. In some embodiments, the protein or functional RNA in the expression cassette is operatively linked to a promoter sequence that controls the expression of the protein or functional RNA. The present disclosure should not be interpreted to be limited to use of any particular promoter or category' of promoters. In some embodiments, the promoter may be an inducible promoter that is capable of turning on expression of a polynucleotide sequence to which it is operatively linked, when such expression is desired. In some embodiments, die inducible promoter is capable of turning off expression when expression is not desired. Examples of inducible promoters include, but are not limited to a metallothionine promoter, a glucocorticoid promoter, a progesterone promoter, and a tetracycline promoter. [0240] In some embodiments, the vector comprising an expression cassette may contain a selectable marker gene (e.g., antibiotic resistance gene) or a reporter gene (e.g , luciferase, betagalactosidase, green fluorescent protein gene) to facili tate identification and selection of cells containing the vector. Suitable expression systems are well known to one of skill in the art and may be prepared using known techniques or obtained commercially.

[0241] In some embodiments, the present disclosure provides a composition of a vector or vector set encoding an epigenetic effector, a blocking reagent, a guide RNA, or any polypeptide or nucleic acid described elsewhere herein. In some such embodiments, provided vectors may be or include DNA, RNA, e.g., mRN A, or any other nucleic acid moiety or entity as described herein, and may be prepared by any' technology described herein or otherwise available in the art (e g., synthesis, cloning, amplification, in vitro or in vivo transcription, etc.). In some embodiments, provided nucleic acids that encode an epigenetic effector, a blocking reagent, a guide RNA, or a nucleic acid in a guided epigenetic editing composition described elsewhere herein may be operationally associated with one or more replication, integration, and/or expression signals appropriate and/or sufficient to achieve integration, replication, and/or expression of the provided nucleic acid in a system of interest (e.g., in a particular cell, tissue, organism, etc,).

[0242] In some embodiments, the vector is a non-viral vector, e.g., liposome, exosome, lipid nanoparticle. In some embodiments, the vector may be selected from a lipid nanoparticle, a liposome, an exosome, and a micro vesicle. In some embodiments, the viral vector may be derived from an adenovirus, a retrovirus, an adeno-associated virus, a vaccinia virus, a lentivirus, a phage virus, a herpes simplex virus, or a polio virus. In some embodiments, the lipid nanoparticle may comprise an ionizable lipid. In some embodiments, the lipid nanoparticle further comprises one or more of neutral lipids, ionizable amine-containing lipids, biodegradable alkyne lipids, steroids, phospholipids, polyunsaturated lipids, structural lipids (e.g, sterols), PEG, cholesterol, or polymer conjugated lipids.

[0243] In some embodiments, the vector may be provided as a component of a reaction mixture. In some embodiments, the vector may be provided as a component of a composition comprising the vector and a pharmaceutically acceptable carrier. In some embodiments, the vector may be provided as a component of a culture comprising a cell. In some embodiments, the vector may be provided as a component of a production vector.

Cells

[0244] The present disclosure is further directed, in part, to cells comprising an epigenetic effector, a blocking reagent, a guide RNA, a template, or a combination thereof. Any cell, e.g., cell line, e.g., a cell line suitable for expression of a recombinant polypeptide, known to one of skill in the art is suitable to comprise an epigenetic effector or an epigenetic modifying composition described herein. In some embodiments, a cell, e.g., cell line, may be used to express an epigenetic effector or a composition described herein. In some embodiments, a cell, e.g., cell line, may be used to express or amplify' a nucleic acid, e.g,, a vector, encoding an epigenetic effector or a composition described herein. In some embodiments, a cell comprises a nucleic acid encoding a composition (e.g., a targeting nuclease effector or a component of a DMA repair machinery) described herein.

[0245] In some embodiments, a ceil comprises a first nucleic acid encoding a first component (e g, an epigenetic effector) and a second nucleic acid encoding a second component, (e.g, a blocking reagent) of an epigenetic effector composition. In some embodiments, wherein a cell comprises nucleic acid encoding an epigenetic effector and a blocking reagent, the sequences encoding each component are disposed on separate nucleic acid molecules, e.g, on different vectors, e.g, a first vector encoding an epigenetic effector and a second vector encoding a blocking reagent. In some embodiments, the sequences encoding each component are disposed on the same nucleic acid molecule, e.g, on the same vector. In some embodiments, some or all of the nucleic acid encoding epigenetic effector or blocking reagent is integrated into the genomic DNA of the ceil. In some embodiments, some or all of the nucleic acid encoding epigenetic effector or blocking reagent is not integrated into the genomic DNA of the cell. In some embodiments, the nucleic acid encoding a first component is integrated into the genomic DNA of a cell, and the nucleic acid encoding a second component is not integrated into the genomic DNA of a cell (e.g., is situated on a vector).

[0246] Examples of cells that may comprise and/or express an expression repression composition or expression repressor described herein include, but are not limited to, hepatocytes, neuronal cells, endothelial cells, myocytes, and lymphocytes.

[0247] The present disclosure is further directed, in part, to a cell made by a method or process described herein. In some embodiments, the disclosure provides a cell produced by providing a guided epigenetic editing composition described herein, providing the cell, and contacting the ceil with the guided epigenetic editing composition. In some embodiments, contacting a cell with a guided epigenetic editing composition comprises contacting an organism that comprises the cell with one or more components of the guided epigenetic editing composition and/ or nucleic acid encoding one or more components of tire guided epigenetic editing composition under conditions that allow the cell to produce the epigenetic effector, Software, Systems, and Devices

[0248] In some other aspects, provided herein are lion-transitory computer-readable storage media. In some embodiments, the non-transitory' computer-readable storage media comprise one or more prograins for execution by one or more processors of a device, the one or more programs including instractions which, when executed by the one or more processors, cause the device to generate a cellular state profile (e.g., a cellular state profile for a modified cell, a current cellular sate profile or a rejuvenated cellular state profile), a differential cellular state profile, and/or obtain a target list of epigenetic markers and associate modifications, for example based on inputted profiling data.

[0249] FIG. 5 illustrates an example of a computing device or system in accordance with one embodiment. Device 500 can be a host computer connected to a network. Device 200 can be a client computer or a server. As shown in FIG. 5, device 500 can be any suitable type of microprocessor-based device, such as a personal computer, workstation, server or handheld computing device (portable electronic device) such as a phone or tablet. The device can include, for example, one or more processor(s) 510, input devices 520, output devices 530, memory or storage devices 540, communication devices 560, and a profiling data generation device (e.g., a nucleic acid sequencer) 570. Software 550 residing in memory' or storage device 540 may comprise, e.g., an operating system as well as software tor executing the methods described herein Input device 520 and output device 530 can generally correspond to those described herein and can either be connectable or integrated with the computer.

[0250] Input device 520 can be any suitable device that provides input, such as a touch screen, keyboard or keypad, mouse, or voice -recognition device. Output device 530 can be any’ suitable device that provides output, such as a touch screen, haptics device, or speaker.

[0251] Storage 540 can be any suitable device that provides storage (e.g., an electrical, magnetic or optical memory’ including a RAM (volatile and non-volatile), cache, hard drive, or removable storage disk). Communication device 56(1 can include any suitable device capable of transmitting and receiving signals over a network, such as a network interface chip or device. Tire components of the computer can be connected in any suitable manner, such as via a wired media (e.g., a physical system bus 580, Ethernet connection, or any other wire transfer technology) or wirelessly (e.g., Bluetooth®, Wi-Fi®, or any other wireless technology).

[0252] Software module 550, which can be stored as executable instructions in storage 540 and executed by processors) 510, can include, for example, an operating system and/or the processes that embody’ the functionality of the methods of the present disclosure.

[0253] Software module 550 can also be stored and/or transported within any non-transitory computer-readable storage medium tor use by or in connection with an instruction execution system, apparatus, or device, such as those described herein, that can fetch instructions associated with the software from the instruction execution system, apparatus, or device and execute the instructions. In the context of this disclosure, a computer-readable storage medium can be any medium, such as storage 540, that can contain or store processes for use by or in connection with an instruction execution system, apparatus, or device. Examples of computer- readable storage media may include memory' units like hard drives, flash drives and distribute modules that operate as a single functional unit. Also, various processes described herein may be embodied as modules configured to operate in accordance with the embodiments and techniques described above. Further, while processes may be shown and/or described separately, those skilled m the art will appreciate that the above processes may be routines or modules within other processes.

[0254] Software module 550 can also be propagated within any transport medium for use by or in connection with an instruction execution system, apparatus, or device, such as those described above, that can fetch instractions associated with the software from the instruction execution system, apparatus, or device and execute the instructions. In the context of this disclosure, a transport medium can be any medium that can communicate, propagate or transport programming for use by or in connection w⁷ith an instruction execution system, apparatus, or device. The transport readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic or infrared wired or wireless propagation medium.

[0255} Device 500 may be connected to a network (e.g., network 604, as shown in FIG. 6 and described below), which can be any suitable type of interconnected communication system. The network can implement any suitable communications protocol and can be secured by any suitable security protocol. The network can comprise network links of any suitable arrangement that can implement the transmission and reception of network signals, such as wireless network connections, T1 or T3 lines, cable networks, DSL, or telephone lines.

[0256] Device 500 can be implemented using any operating system, e.g., an operating system suitable for operating on the network. Software module 550 can be written in any suitable programming language, such as C, C++, Java or Python. In various embodiments, application software embodying the functionality of the present disclosure can be deployed in different configurations, such as in a client/server arrangement or through a Web browser as a Web-based application or Web service, for example In some embodiments, the operating system is executed by one or more processors, e.g., processors) 510.

[0257] Device 500 can further include, for example, a nucleic acid sequencer 570, which can be any suitable nucleic acid sequencing instrument. Exemplary sequencers can include, without limitation, Roche/454’s Genome Sequencer (GS) FLX System, Illumina/Solexa’s Genome Analyzer (GA), Illumina’s HiSeq 2500, HiSeq 3000, HiSeq 4000, and NovaSeq 6000 Sequencing Systems, Life/APG’s Support Oligonucleotide Ligation Detection (SOLiD) system, Poionator’s G.007 system, Helicos BioSciences’ HeliScope Gene Sequencing system, or Pacific Biosciences’ PacBio RS system.

[0258] FIG. 6 illustrates an example of a computing system in accordance with one embodiment. In computing system 600, device 500 (e.g., as described above and illustrated in FIG. 5) is connected to network 604, which is also connected to device 606. In some embodiments, device 606 is a sequencer. Exemplary sequencers can include, without limitation, Roche/454’s Genome Sequencer (GS) FLX System, Illumina/Solexa’s Genome Analyzer (GA), Illumina’s HiSeq 2500, HiSeq 3000, HiSeq 4000 and NovaSeq 6000 Sequencing Systems, Life/APG’s Support Oligonucleotide Ligation Detection (SOLiD) system, Poionator’s G.007 system, Helicos BioSciences’ HeliScope Gene Sequencing system, Pacific Biosciences’ PacBio RS system, MinlON, GridlON, or PromethlON. [0259] Devices 500 and 606 may communicate, e.g., using suitable communication interfaces via network 604, such as a Local Area Network (LAN), Virtual Private Network (VPN), or the Internet. In some embodiments, network 604 can be, for example, the Internet, an intranet, a virtual private network, a cloud netw ork, a wired network, or a w i reless network. Devices 500 and 306 may communicate, in part or in whole, via. wireless or hardwired communications, such as Ethernet, IEEE 802.1 lb wireless, or the like. Additionally, devices 500 and 606 may communicate, e.g., using suitable communication interfaces, via a second network, such as a mobile/cellular network. Communication between devices 500 and 606 may further include or communicate with various servers such as a mail server, mobile server, media server, telephone server, and the like. In some embodiments, devices 500 and 606 can communicate directly (instead of, or in addition to, communicating via network 604), e.g., via wireless or hardwired communications, such as Ethernet, IEEE 802.11b wireless, or the like. Tn some embodiments, devices 500 and 606 communicate via communications 608, which can be a direct connection or can occur via a network (e.g., network 604).

[0260] One or all of devices 500 and 606 generally include logic (e.g., htp web server logic) or are programmed to format data, accessed from local or remote databases or other sources of data and content, for providing and/or receiving information via network 604 according to various examples described herein.

EXAMPLES

[0261] These examples are provided for illustrative purposes only and not to limit the scope of the claims provided herein.

Example 1: Identifying epigenetic editing target sites for modifying a T-cell differentiation state based on differential epigenetic maps of different T-cell differentiation states

[0262] Epigenetic editing of specific target genomic sites can be applied to modify a cell in an initial cellular state (e.g., a highly differentiated cell) to produce a modified cell in a desired cellular state (e.g., a less differentiated cell). This example shows a method for using differential epigenetic maps to identify epigenetic editing target sites for modifying a T-cell differentiation state. In this example, four different populations of CD8+ T-cells m different cellular differentiation states were first profiled by epigenetic profiling. Epigenetic maps of the four differentiation states were generated from methylation sequencing data using a method of unsupervised clustering of epigenetic states, as described in Example 3. The differential between the epigenetic maps of the four differentiation states w as used to identify target genomic regions for epigenetic editing for modifying a differentiation state of a CD8+ T cell.

[0263] To profile CD8+ T-ceils in different cellular differentiation states, CD8+ T-cells from a donor were first sorted by fluorescence activated cell sorting (FACS) into the following populations: Naive CD8+ T-cells, 2) central memory CD8+ T-cells, 3) effector memory CD8+ T-celis, and 4) effector CD8+ T-cells and sequenced by whole methylome sequencing across the whole genome using long read ONT sequencing. Epigenetic maps for the whole genome (20,000+ genes) were prepared showing methylation sites for each population. The epigenetic maps were used to assess the differences in methylation states across each gene locus, including CpG sites, for different CD8+ T-cell differentiation states

Sorting CD8+ T-cell differentiation subsets from donor T-cells and whole methylome sequencing

Cell Thawing and Incubation

[0264] T cells from a donor w ere thawed and incubated overnight to induce expression of CD62L m preparation for staining and sorting. Vials of T-cells from donor TIS006, CEL021, Aliquot CHS-0001504791 were taken from a liquid nitrogen stock and thawed in a 37 °C water bath for 2-3 minutes or until only small chunks of frozen contents can be visualized A 1 ml, volume of pre-warmed T cell draw medium (10% Heat Inactivated Fetal Serum, 1 ug/mL DNAsel in lx Phosphate Buffered Saline (PBS)) was slowly added into each T cell cryopreserve vial in a drop-wise manner. The cells were mixed by gentle pipetting and then diluted in prewanned T cell thaw medium, such that the final volume ofT cell thaw medium to cryopreserved ceil stock is at 10: 1 (v:v) ratio. Multiple T cell vials form the same donor can be thawed and pooled by scaling the volume of the T cell thaw proportionally. The cells were centrifuged at 600 xg for 5 minutes at room temperature. Tire cells were resuspended in culture media (RMPI 1640 + 10% FBS + lx Glutamax) at a concentration of 250,000 cells/mL. The cells were incubated overnight to induce expression of CD62L.

Cell Staining

[0265] In total, about I million cells were stained in preparation for sorting. The follow? ing antibodies were used for staining: APC anti-human CD45RO and an anti-human CD62L antibody. [0266] Following overnight incubation, the T cells were spun at 600 xg for 5 minutes and resuspended in 200 pL of FACS buffer (Mg²7Ca² " -free lx PBS + 2% HI FBS). Aliquots of 10 rd. of cells were put aside for the follo wing: blank, 7AAD-only, CD45RO-only, and CD62L- only for single staining (sorter compensation). The volume of each was brough up to 200 uL with FACS buffer. The remaining 160 pL of cells were stained for sorting after bringing the volume up to 200 uL. For staining, 2 jxL of each antibody stock was used to stain cells, according to the experimental condition. The cells were incubated for 30 min. at 4 C. Following incubation, the cells were washed three times by adding 1 mL of F ACS buffer and centrifuged at 300 xg for 5 min. at 22°C and removing the supernatant. An aliquot of 10 pL of double-stained cells were put aside to incubate for 5 min. at 70°C as a positive control of dead cells (7AAD+).

Sorting

[0267] Before sorting the ceils into plates, the respective percentages of the naive CD8+ T-cell population (CD62L+ / CD45RO-), the central memory CD8+T-cell population (CD62L+ / CD45RO+), ths effector memory CD8+ T-cell population (CD62L- / CD45RO+), and effector CD8+ T-cell population (CD62L- / CD45RO-) were verified using the CD62L and CD45RO markers.

[0268] Idle T-ceils were then sorted into the populations: 1) Naive CD8+ T-ceils, 2) central memory CD8+ T-cells, 3) effector memory’ CD8+ T-cells, and 4) effector CD8+ T-cells, as shown in FIG. 20, and index sorted into an Eppendorf twin-tech, loBmd 96-well plate. The sorted cells can be stored at -80°C until ready to use for library preparation. The genomic DNA from the sorted cells were then extracted using the method described in Example 2. Sequencing libraries were prepared from the genomic DNA using the method described in Example 3 and sequenced using ONT sequencing.

Preparation of epigenetic maps and identification of target epigenetic editing regions

[0269] The sequencing results were used to prepare epigenetic maps that are specific to each

Cl.) • T-cell differentiation subset for 20,000+ genes in the genome using a method of unsupervised clustering of epigenetic states, as described in Example 3. Each epigenetic map shows methylation states across each gene locus collected from the methyl ome sequencing results of a particular CD8+ T-cell subset. FIGs. 21A-21D show an example of epigenetic maps of the GZMK gene prepared from the sequencing results for the naive CD8+ T-cells (FIG.

21A), the central memory (CM) CD8+ T-cells (FIG. 21B), the effector CD8+ T-cells (FIG. 21C), and the effector memory (EM) CD8+ T-cells (FIG. 21 D). The black bands represent an unmethylated state, while the light gray bands represent a methylated state. The x-axis in each map represents the chromosome position across the GZMK gene region. The y -axis in each map represents an individual sequencing read from a single cell. The blocks below each epigenetic map represent regions representing promoters, introns, and exons.

[0270] As FIGs. 21A-21D show, the GZMK gene is overall more highly methylated in naive CD8+ T cells as compared to the CM CD8+ T-cells, EM CD8+ T-cells, and effector CD8+ T~ cells. Comparison of the epigenetic maps in FIGs. 21A-21D revealed a region at the 5’ end of the gene, indicated by the boxed region in FIG. 21 A, that showed substantially higher levels of methylation in naive CD8+ T cells compared to the CM CD8+ T-cells, EM CD8+ T-cells, and effector CD8+ T-cells. Based on this differential between the epigenetic maps, this region was identified as a target region for epigenetic editing. It is predicted that targeting this region for methylation in a CM CD8+ T-cell, an EM CD8+ T-cell, or an effector CD8+ T-cell may produce a modified CD8+ T-cell that is closer in phenotype/function to a naive CD8+ T-cell .

[0271] FIGs. 22A-22D show an example of epigenetic maps prepared from the sequencing reads for the SELL gene. The results show that the SELL gene had lower levels of methylation in naive CD8+ T cells and CM CD8+ T-cells as compared to EM CD8+ T-cells and effector

CD8+ T-cells. Comparison of the epigenetic maps in FIGs. 22A-22D revealed a region at the 3’

:nd of the gene, indicated by the boxed region in FIG. 22A and FIG. 22B, that showed substantially lower levels of methylation in naive CD8+ T cells and CM CD8+ T-cells compared to effector CD8+ T-cells and EM CD8+ T-cells. Based on this differential between the epigenetic maps, this region was identified as a target region for epigenetic editing. It is predicted that targeting this region for demethylation in an EM CD8 + T-cell or an effector CD8+ T-cell may produce a modified CD8+ T-cell that is closer in phenotype/function to a naive CD8+ T-cell or a CM CD8+ T-cell.

[0272] FIGs. 23A-23D show an example of epigenetic maps prepared from the sequencing reads for the CD27 gene. The results show that the CD27 gene had higher levels of methylation in effector CD8+ T cells as compared to naive CD8+ T ceils, CM CD8+ T-cells, and EM CD8+ T-cells. Comparison of the epigenetic maps in FIGs. 23A-23D revealed a region at the 5 ’ end of the gene, indicated by the boxed region in FIG. 23C, that showed substantially higher levels of methylation in effector CD8+ T-cells compared to nai ve CD8+ T cells, CM CD8+, and EM CD8-:- T-cells. Based on this differential between the epigenetic maps, this region was identified as a target region for epigenetic editing. It is predicted that targeting this region for demethylation in an effector CD8+ T-cell may produce a modified CD8+ T-cell that is closer in phenotype/function to a naive CD8+ T-cell, a CM CD8+ T-cell, or an EM CD8+ T-cell.

[0273] Beyond the genes shown in this example, epigenetic maps were also prepared for the four CD8+- T cell subsets for each gene in the human genome. Differential analysis can be conducted to identify target regions in different regions in these genes for epigenetic editing with the goal of modifying a CD8+ T-cell in one differentiation state to produce a CD8+ T-cell in another differentiation state.

Example 2: Identifying epigenetic editing target sites for modifying a liver hepatocyte with minimal modifications to off-target celi/tissue types based on differential epigenetic maps of different cell/tissue types

[0274] When in troducing epigenetic edits to cells, such as for the purpose of modifying a cellular state, it may be desirable to control the effects of epigenetic editing to specific target cell ty pes and minimize modifications to off-target cell types/tissues. This example shows a method of using differential epigenetic maps for narrowing the search space for favorable epigenetic editing target sites in a target liver hepatocyte by identifying target regions for epigenetic editing that would introduce minimal modifications to off-target cells of another cell/tissue type. In this example, epigenetic maps of cells of different cell types were compared to inform the selection of epigenetic editing target sites in target liver hepatocytes that 'would minimize the level/risk of undesired epigenetic editing in other off-target cell types and tissues.

[0275] Epigenetic maps were constructed from a public data set of whole genome methylation data of different cell types. As shown in FIG. 26, the epigenetic maps depict methylation of the genomic sites within tire PCSK9 gene and the promoter region of the PCSK.9 gene. From top to bottom, 2601, 2602, 2603, 2604, and 2605 in FIG. 26 are five epigenetic maps of liver hepatocytes, 2606 is an epigenetic map of liver macrophages, 2607 is an epigenetic map of liver endothelium cells, 2608 is an epigenetic map of gastric body epithelium cells, 2609 is an epigenetic map of pancreas alpha cells, 2610 is an epigenetic map of pancreas ductal cells, 2611 is an epigenetic map of pancreas beta cells, 2612 is an epigenetic map of pancreas acinar cells, 2613 is an epigenetic map of pancreas delta cells, and 2614 is an epigenetic map of pancreas endothelium cells. Within each epigenetic map, the height of the bars represents the degree of methylation, with tall bars representing genomic sites with high methylation levels and short bars or non-existent bars representing genomic sites with low' methylation levels or unmethylated genomic sites. [0276] In this example, liver hepatocytes were designated as the target cells and the other cell types were designated as off-target cells. Based on the liver hepatocyte epigenetic maps, two substantially unmethyiated regions (that are boxed) were identified as potential target regions for methylation. The first boxed region 2621 comprises the promoter region of the PCSK9 gene.

Tire second boxed region 2622 comprises a region within the PCSK9 gene body. Comparison of tlie liver hepatocyte epigenetic maps and the epigenetic maps of the other off-target cell types shown m FIG. 26 revealed that the second boxed region within the PCSK9 gene body is substantially unmethyiated in liver hepatocytes but substantially methylated in other off-target ceil types, suggesting that this region would be a favorable target region for methylation in liver hepatocytes. Since the lack of methylation in this second boxed region is specific to liver hepatocytes, it was predicted that that targeting this region for methylation would produce the intended modifications to the liver hepatocytes, while minimizing the risk / degree of unintended modifications to the off-target cell types (which are already substantially methylated in this region). On the other hand, comparison of the epigenetic maps in FIG. 26 revealed that the promoter region of the PCSK9 gene is substantially unmethyiated in liver hepatocytes and in the other off-target cell types, suggesting that the promoter region of the PCSK9 gene may be a less favorable target region for methylation given the larger risk of considerable modification to off- target ceil types. Since the promoter region of the PCSK9 gene is substantially unmethyiated across multiple cell types, it was predicted that targeting this region of the genome for methylation would simultaneously methylate this region in the target liver hepatocytes and in the off-target cells unless other measures are put in place to selectively target tlie liver hepatocytes.

[0277] As shown in this example, comparison of epigenetic maps of different cell and tissue types can reveal genomic regions that are specifically methylated or unmethylated in certain ceil/tissue types, which may inform selection of target sites for epigenetic editing that would minimize modifications to off-target cells/tissues. By identifying target sites that are in an undesired methylation state in the target cell but are already in the desired methylation state in off-target cells/tissues, one can safely introduce a targeted epigenetic intervention that only modifies the intended target cell and does not affect the off-target cells/tissues. For instance, if a target genomic site is substantially unmethyiated in liver hepatocytes but already substantially methylated in off-target cells/tissues, then introducing an methylase fusion protein targeting the target genomic site would modify the liver hepatocytes but minimize modifications to the off- target cells/tissues. which are already methylated in the target genomic site. [0278] This strategy of using differential epigenetic m aps of different cell/tissue types can be useful tor targeting any cell/tissue type with minimal modifications to another off-target cell/tissue, by revealing methylation patterns that are unique to the target cell/tissue type.

[0279} This strategy considerably reduces the search space for favorable target genomic sites for epigenetic editing. For particular applications, the methods described in this example (that identify an editing region would that minimize unintended modifications to off-target cell types) can be combined with the methods described in Example I (that identify an editing region for the purpose of modifying a cellular state). By combining these methods, one can identify a target epigenetic editing site that would both serve in modifying a target cell from an initial cellular state (e.g., a highly differentiated state) to a desired cellular state (e.g., a less differentiated state) and also minimize unintended modifications to off-target cell types.

Example 3: Generating Epigenetic Maps Based on Unsupervised Clustering of Epigenetic States Using Long Read Sequencing

[0280] Uiis example shows a method of generating epigenetic maps that depict methylation patterns in DNA from methylation sequence data, as shown in Example 1 and Example 5, that can be used in differential analysis to identify favorable epigenetic editing target sites.

Unsupervised clustering scheme was developed to identify epigenetic states on a whole genome and gene-level bases, using long read sequencing with methylation calling. Oxford Nanopore Technologies (ONT) was used to generate sequencing reads from CD8+ T-cells, isolated from three normal, healthy donors. All *.bam files were merged into one *.bam file to maximize coverage for this analysis.

[0281] Unsupervised clustering analysis was performed with the *.bam file. First, the region of interest (ROI) was selected. Given a set of coordinates spanning a genomic region (e.g., a gene), all fragments that span that region and the methylation status of any contained CpGs was extracted. All regions from the *.bam files were annotated as genes in the Gencode .v42 database including promoter regions (defined as Ikb upstream as determined by strand annotation) (https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_42/gencode.v42.basic.ann otation.gtf.gz).

[0282] Next, for a given ROI, a distance matrix which contains a distance measure between all fragments that span that gene was computed. Each fragment was a vector of binary values corresponding to CpGs with either methylated (I ) or unmethylated (0) values. Various distance metrics exist for computing the distance between two binary-valued vectors including Hamming, Random Forest and Simple Matching. In this implementation. Simple Matching, which evaluates the number of CpGs that match (e.g., both unmethylated or both methylated) and normalizes to the total number of comparable (i.e., CpGs) in the ROI was used.

[0283] With the commuted distance matrix, various fragments were grouped (clustered) to optimize an inter-cluster metric (e.g., minimize inter-cluster average distance) and an intracluster metric (e.g., maximize the distance between the two closest residents of two separate clusters). Tire two most common methods tor clustering are hierarchical and k-means clustering. In this approach, hierarchical clustering was performed. Specifically, an agglomerative. hierarchical clustering with complete linkage (see: https:.7en.wikipedia.org/wiki/Completelinkage_clustering) was used.

[0284] Finally, the optimal number of clusters was determined. Common methods for determining the appropriate number of clusters include the Elbow Method, Silhouette, and the Gap Statistic. The appropriate number of clusters was determined by computing a figure of merit (FOM) while varying the number of clusters and selecting an optimal cluster number derived from the graph of the FOM vs. clusters (e.g.. the elbow, maximum, etc ). Here, a version of the Gap Statistic was used.

[0285] The Gap Statistic provides a method to evaluate the correct number of clusters by comparing the dispersion of inter-cluster distances to that obtained using a reference null distribution in which all samples are equidistant from one another (i.e., there should only be 1 cluster for the null hypothesis). To generate the correct reference null distribution, for each CpG, a state (1 or 0) from the distribution of fragments that span that CpG was randomly sampled, 'the resultant reference null data set eliminated the dependency structure of the actual data by ensuring all features (i.e,, CpGs) were independent of one another. As shown in FIG. 11, actual and reference null data, sets for TCF7 was compared. Tire columns represent CpGs in TCF7, and the rows represent individual fragments spanning TCF7.

[0286] This process was repeated multiple times (e.g., 50 times) to generate man}/ reference null distributions. For each reference null distribution, a dispersion FOM (log(Wk)) was calculated. Hiis was repeated for varying cluster number (up to a maximum determined by the number of fragments for that gene). The mean of the reference distribution FOM for each cluster number was compared to that obtained from the actual data and the Gap Statistic was calculated. Further, the standard error of the reference null FOM for each cluster number to as a means to assess the impact of random sampling on a given FOM to another was used , [0287] In this example, the smallest cluster number (k) that satisfies Gap(k) >= Gap(k+i)~ 3*SE(k+l) was selected. This enabled a statistical approach to selecting the appropriate number of clusters based on the underlying data distributions. As shown in FIG. 12, the dotted line, representing the optimal number of clusters for TCF7 (e.g., two clusters), was generated to satisfy Gap(k) >= Gap(k+l)-3*SE(k+l).

[0288] Once the optimal number of clusters was determined, fragm ents were assigned to the appropriate cluster. Finally, annotations tor each CpG based on the UCSC database were added. An example plot for the TCF7 gene is shown in FIG. 13. One of the primary differences between the two clusters appeared to be the methylation of a large intron (shortest gray bar height in FIG. 13). Aside from plot for TCF7, various heatmaps of T-cell related genes was also generated to show optimal number ofclusters based on the Gap Statistic (FIGs. 14A-14Z, FIGs.

14AA-14HH).

[0289] As show n in FIG. 15, distribution of optimal number of clusters based on the Gap Statistic across >14,000 Hg38 genes (y axis is log scale) was generated. While a minority of the overall distribution, genes exhibiting high numbers of clusters (>5-10) can likely be overclustered (i.e., clusters that do not correspond to true epigenetic states). Similarly, the optimal number of clusters was identified per chromosome. As shown in FIG. 16, the majority of the genes with a large number of epigenetic states appeared to come from X chromosome

[0290] Looking more closely at the chromosome (FIGs. 17A-17Z, FIGs. 17AA-17II), a pattern was observed, where about 50% of the fragments were heavily methylated and clustered separately, while the remaining 50% were clustered with the large coherent regions of metliylated/unmethylated CpGs. This may be indicative of X-activation, as all the donors in this data set were female.

[0291] Collectively, the implementation of unsupervised clustering analysis method enabled the definition of epigenetic states at the gene level. Future advancements will move towards enabling multi-gene (ideally whole genome) state profiling. Thi s may require one to link the states defined for one gene to those arising from a different gene. This may be accomplished through tire use of fragments that span multiple genes (thereby enabling one to understand mter- genic correlations of epigenetic states). Alternatively, the inter-genic state relationships using other data modalities such as single cell methylation profiling and/or gene expression may be mapped. Ensuring that the resultant clusters represent true epigenetic states will require further optimization. Methods to improve may involve tightening the gap statistic selection criteria (increasing the number of SE(k+l)'s that Gap(k+1) must be from Gap(k)), placing an upper limit on the number of allowed epigenetic states per gene (currently it is capped by the number of available fragments), denoising techniques to account for technical/biological noise, and incorporating various heuristics (e.g. weighting CpGs in promoter regions more heavily than introns in distance calculations, developing heuristics for accommodating known biological phenomenon such as X-inactivation).

Example 4: Assessing the Relative Importance of CpGs to a given Classification

[0292] Read ONT data from CD8+ T-cells described in Example 3 was used to assess the relative importance of CpGs to a given classification (e.g., cluster, experimental condition), which can aid in differential analysis to identify favorable epigenetic editing target sites. As described in Example 3, using the ONT data from CD8+ T-cells, the region of interest was selected and subjected to clustering. Those clusters then defined the classification. Next, information gain for each CpG in a gene was calculated. Information gain measures the gain in information (reduction in entropy) when partitioning a dataset on a given attribute (e.g., CpG methylation value). Information gain is commonly used in decision tree creation where it is used in a recursive fashion to select the order of attributes to partition on to maximize classification accuracy. Information gain was calculated with the following equation: i) Information Gain = Entropy(T) - Entropy(T|a), where T is a random variable (e.g., epigenetic state) and a is an attribute (e.g., a specific CpG methylation status). Entropy(T|a) can be interpreted as the Expected value of the resulting entropy when the dataset is partitioned on atribute, a. Thus, given knowledge of the methylation of a CpG, how much information is gained regarding the underlying random variable (e.g., epigenetic state) can be calculated ii) Entropy = -p*log2(p) - (l-p)*log2(l-p), where p is the probability of event in question (e.g., whether a given CpG is methylated or not).

[0293] After the entropy of all clusters (i.e,, all fragments) was first calculated, the weighted average of the entropy of each individual cluster of fragments was subtracted. The difference was the information gam.

[0294] Information gain of various genes provided a method to quantitate the relative importance of a CpG methylation status on the underly ing state classification. FIG. 18 shows an example of the calculated information gain for the LAG3 gene. As shown in FIG. 18, regions with high information gain also had clear differences in methylation states between the two clusters. Higher values of information gain indicated those CpGs were more important in defining the clusters. In FIG. 19, the MYC gene had only' one cluster; thus, the information gain is zero.

[0295] The knowledge of the relative importance of various CpG to some classification (e.g., epigenetic state, experimental condition) afforded the ability to determine which CpG/genomic locations were most important in classification. This information can be used in applications including decision-tree based classification, targeted assays (e.g., use of panels vs. whole genome sequencing), or fundamental understanding of underlying biological processes (e.g., correlating regions of high information gain to differential expression of genes).

Example 5: Using epigenetic maps to identify transcription factors and transcription factor footprints in differentially methylated regions of different T-cell states

[0296] In this example, differential epigenetic maps of different T-cell states were used to identify transcription factor footprints in differentially methylated regions (DMRs). These footprints can serve as target sites for targeted epigenetic editing to modify one T-cell state to another T-cell state.

[0297] First, a population of CD8+ T cells were sorted into naive, central memory (CM), effector memory' (EM), and effector subsets using flow cytometry: naive CD8+ T-cell population (CD62L+ / CD45RO-), the central memory' CD8+T-cell population (CD62L+ / CD45RO+), the effector memory' CD8+ T-cell population (CD62L- / CD45RO-f ), and effector CD8+ T-cell population (CD62L- / CD45RO-). Next, each subset was subjected to epigenetic sequencing and mapping through unsupervised clustering as described in Example 3. Epigenetic maps of the different T-cell subsets were analyzed to identify differentially methylated regions (DMRs) between one T-cell state and another T-cell state. Footprints of known transcription factors that were tamed on during differentiation of naive cells to effector cells were identified using the Homer analysis and analyzed within open differential methylation windows, derived from epigenetic maps of naive cells versus effector cells to discover transcription factors that are active between epigenetic states, as shown in FIG. 29. Here, dark gray represents an unmethylated state and light gray' represents a methylated state.

[0298] Further, transcription factors that are active between epigenetic states were identified by looking at DMRs that are directly associated with a transcription factor (e.g,, DMRs that are directly in promoter, enhancer, or gene body of a particular transcription factor gene). FIGs.

30A-30C shows transcription factors (e.g., RUNX1, F0XN3, ELK1, BACH2) with distinct epigenetic states, where for some transcription factors, the window (e.g., region) was unmethylated in naive cells while in some transcription factors, the window (e.g., region) was unmethylated in effector cells. Here, dark gray represents an unmethylated state and light gray represents a methylated state. The transcription factors with footprints enriched in differentially methylated region were compared to transcription factors that have differential methylation states to identify target sites for targeted epigenetic editing.

Example 6: Epigenetic mapping for discovery of mechanism and approaches to optimize target

[0299] Epigenetic mapping of the genes present in specific pathways can help determine the mechanism and approaches to optimize a particular target, inhibition ofGSKBbeta signaling pathway reprogramed CD8+ T cells towards a more naive state (data not shown). Thus, epigenetic mapping of effector vs nai ve cell states, generated as described in Example 5, were analyzed for genes that are part of the GSK3beta pathway (FIG. 31A). Analysis showed various differentially methylated regions in enzymes active in the cytoplasm (e.g., GSK3, AXIN1, AXIN2) (FIGs. 31B-31D) and also transcription factors downstream in the nucleus of the GSK3beta pathway (e.g., LEF1, BCL1 IB, TCF7, TLE) (FIGs. 31E-31H), which provide insight to an approach to reprogram CD8+ T cells towards a more naive state via the GSKSbeta pathway. Here, dark gray represents an unmethylated state and light gray represents a methylated state.

[0300] Methylated genes related to transcription factors that were found to have their footprint enriched in differentially methylated regions (e.g., AP-1, RUNX), as described in Example 6, were also investigated to further determine the mechanism to optimize a transcription factor target. As shown in FIGs. 32A-32C, genes related to AP-1 and RUNX (e.g., NFATC2, RUNX1) were found to be differentially methylated in naive cells (dark gray on right hand bar) versus effector cells (light gray on right hand bar). Here, dark gray represents an unmethylated state and tight gray represents a methylated state.

Example 7: Overview of Reprogramming Ceils with sgRNA and Effector Library

[0301] This example provides an overview of a method of introducing targeted epigenetic edits to target genomic sites using CRISPR-based epigenetic editing systems, as described in certain embodiments herein. In some embodiments, CRISPR-based epigenetic editing systems comprise an epigenetic effector and a guide RNA that targets the epigenetic effector to a target nucleic acid site, where the epigenetic effector introduces an epigenetic edit (e.g., methylation or demethylation of the target site). One example of an epigenetic effector is a dCas9 fused to an epigenetic editor (e.g., methylase). A guide RNA targeting a specific promoter region of target gene 1 can guide the epigenetic effector to the target site, where the epigenetic editor methylates the target site, thereby silencing gene expression of target gene 1 , as depicted in FIG. 4. In this example, a target list of one or more CpG targets and associated effector types is provided by data or an artificial intelligence (Al) core. This can include targets sites identified from differential analysis of epigenetic maps identifying favorable epigenetic editing target sites. This can include target sites identified from differential analysis of epigenetic maps of two different cellular states (e.g., two different differentiation states), epigenetic maps of two different cell types, or a combination thereof, such as described in Example 1 or Example 2. In some cases, data is provided to an artificial intelligence (Al) core, which is trained to conduct such differential analyses and identify favorable epigenetic editing target sites.

[0302] As shown in FIG. 1, FIG. 2, and FIG. 3, data/AI core can determine a list of targets (e.g., CpGs, histones, transcription factors, proteins) that are required to be augmented into to implement a specific reprogramming protocol. 'This target list is used to generate a guide RNA library specific to each CpG location. One or more guide RNAs are placed on the same transfer plasmid.

[0303] In parallel to the guide RNA plasmid library construction, an effector library is designed to deliver the required effector types. Vectors are built to specifically modify the epigenome (e.g., CpG methylation, histone acetylation). These effectors may be inducible and target multiple epigenetic loci and elicit different effector function (e.g., methylation vs. demethylation) to achieve parallelized modification of the epigenome. In this embodiment, this may be a library of native dCas9 and d€as9 fusion proteins specific to (de)methylation and/or (de)acetylation The dCas9 variety may be from the aureus or pyogenes lineage. This effector library is loaded into one or more viral vectors (e.g., LVV, AAV), transduced into the sample or cells of interest, and reprogramming is initiated. Optionally, a second class of viral vectors may be transduced into the sample, which enables tire dCas9 construct to be expressed in the presence of an induction reagent (e.g , Dox). In the case of an inducible system, the reprogramming may be controlled via exposure to a chemical which allows tor time-based control of the reprogramming vectors. Sample cells with the desired edits are sorted from ceils, which did not receive the edits via a chemical selection or fluorescence reporter. [0304] With the sample containing the effector library, the sgRNA library is then delivered to the sample via electroporation, nucleofection, or other similar techniques. Sample cells that have received the desired edit are selected via a fluorescent reporter.

[0305] Sample cells which now have both the sgRNA and Effector library are reprogrammed via a time-coursed exposure to a cocktail containing the induction reagent. Under exposure to the induction reagent, the effector protein is expressed, combines with the sgRNA library and effects the desired epigenetic edit. Multiple reprogramming protocols may be delivered to separate cohorts of the sample and then combined for sequencing by exposing each cohort, prior to combination, to a barcoded oligo that enables downstream deconvolution via sequencing.

[0306] Finally, tire effectiveness of the reprogramming protocol is assessed via deep multi-omic profiling. The sample cells with desired epigenetic edits are pooled and profiled via a variety of techniques that may include: scRNA-seq, scATAC-seq, WGBS, Flow Cytometry, and Functional Assay. These data are then fed back into the Data/AI core for future optimization and/or improvements.

Example 8: Targeted Epigenetic Modification of HEK293 using a CRISPR epigenetic editing system

[0307] This example shows targeted epigenetic modification of specific targets CD 151 and CD81 in HEK293 cells using a CRISPR epigenetic editing system with guide RNAs targeting specific target sites within CD 151 and CD81 for methylation. In this example, successful methylation of the targets by the CRISPR epigenetic editing system was inferred upon downregulation of protein expression, which was evaluated using flotv cytometry. Changes in DNA methylation patterns were analyzed using epigenetic maps generated from read methylation sequencing results of the edited cells and control cells (cells that were not treated with the guide RNAs). The results showed that in the edited ceils, the target site in the CD151 promoter was successfully methylated by the CRISPR epigenetic editing system ,

Optimization of ExpOFF Epigenetic Editing System

[0308] ExpOFF epigenetic editing system (e.g., OFF system) was created and optimized to induce epigenetic silencing via transient transfection methods. The ExpOFF system was composed ofZNFlO KRAB, DNMT3A, and DNMT3L domains fused to a catalytically inactive

S. pyogenes dCas9. The ExpOFF system served to silence gene expression through DNA methylation at a target site In this example, CD 151 and CD81 were selected as initial targets. Three sgRNAs were designed to target three target sites in CD 151 (including one targeting a promoter region), and three sgRNAs were designed to target three targets in CD81 .

[0309] To test the system, Hek293.2sus cells (e.g., ATCC (CRL-1573.3) were cultured and passaged in 293 SFM II media (Gibco CAT# 11686029) with 100 units/mL of penicillin/streptomycm (Gibco Cat# 15140122) and 4mM Glutamax (Gibco Cat# 35050061). For 3 days post-electroporation, Hek293.2sus cells were cultured in the same media composition as stated above minus the penicillin/streptomycin. Next, cells were collected in a 50mL Falcon tube then spun down at 300g for 5 minutes and washed with IX DPBS. Hie cell pellet was then resuspended in 5mL of TrypLE IX (Gibco Cat#12604013) and incubated at RT for 5 minutes. The cell suspension was strained through a ceil strainer to remove clumps, followed by cell counting and washing with 1 X DPBS. The cells were resuspended to a density of 5e7 cells/mL and transfected according to Neon Transfection System lOOuL kit protocol. Electroporation parameters of 1200V/20ms pulse width/2pulses were used for all samples. Transfection setup details can be found in Table 3. ExpOFF plasmids (FIG. 10A) were sourced from Thermofisher (GeneART) and sgRNAs were sourced from Synthego. Sequences of ExpOFF and gRNAs that were used are listed in Table 4b. In Table 4b, the SEQ ID NO: 107 sequence corresponds to the structural sgRNA component that interacts with the Cas system. The remainder of the sequence is the portion of the sgRNA targeting the gene location of interest. For this experiment, CD151 and CD81 were chosen as initial targets as they are not essential to cell proliferation or survival. In addition, they are highly expressed in HEk293 cell line and are surface markers that can be easily detected in a non-destructive manner.

[0310] Transfected ceils (e.g., transfection with ExpOFF plasmid and CD151 or CD81 targeting sgRNAs or non-targeting control) were sorted 72 hours after transfections via a BFP protein fused on the ExpOFF protein for positive gating. Sorted cells were passaged every 2-3 days based on confluency. Flow analysis was conducted using a Beckman Coulter Cytoflex and cell sorting was conducted using a Beckman Coulter Cytoflex SRT. Antibodies that were utilized tor staining included PE anti-human CD151(CAT# 350408) and APC anti-human CD81(CAT# 349510). Ceil staining was conducted via incubation with antibodies at 4C for 30 minutes in PBS with 1% FBS. Cells are then washed and stained with a viability stain. Viability staining was performed for all experiments using eBioscience 7-AAD Viability Staining Solution(CAT# 00-6993-50). As shown in FIG. 8, FSC-A and SSC-A gating and viability by 7AA exclusion was used for gating strategy. Furthermore, FACS was gated for BFP expression cells transfected with ExpOFF plasmid and CD151 or CD81 targeting sgRNAs, or non-targeting sgRNA control to yield an enriched population of successfully transfected cells. These cells were cultured and expanded (e.g., passaged every 2-3 days based on confluency) until enough total cells were present for flow analysis.

[0311] 13 days after flow sorting, the sorted samples were stained with anti-CD151 and anti- CD81 antibodies and underwent flow analysis to profile if methylation has occurred at the targeted sites as shown in FIG. 9A-9C. Successful methylation was inferred upon downregulation of protein expression. In samples transfected with gene-targeting sgRNAs, their cognate targets were observed to be down-regulated compared to the blank control. The signature was retained at 12 days (FIG. 9A), at days 24 (FIG. 9B), and 35 days (FIG. 9C) after transfection, suggesting that the methylation can be retained for several days. The non-targeting sgRNA negative control sample did not recover post sorting and the sample could not be cultured further for analysis; however, the blank control was utilized as a substitute negative control.

[0312] Following 3 months of culture, cells from the samples transfected with the CD151 genetargeting sgRNAs and cells from a control sample (with dCas9 and DNMT3A only and no sgRNAs) were sequenced using read methylation sequencing and the DNA methylation patterns were analyzed by generating epigenetic maps from the sequencing data. FIG. 24 shows epigenetic maps of chromosome 11 (positions 831,698-834,439), depicting the methylation patterns in the CD151 gene of the edited cells and of the control cells. The epigenetic maps show a differential in methylation patterns between the edited cells and the control cells. Importantly, the targeted site in the CD151 promoter region is methylated (indicate by light gray lines) m the edited cells and unmethylated (indicated by dark gray lines) in the control cells.

[0313] Epigenetic maps of the edited cells and the control cells were further generated using unsupervised clustering of epigenetic states, as further described in Example 3. FIG. 25 shows the epigenetic maps generated for the edited cells and the control cells, indicating differentially- methylated regions. In FIG. 25, the dark gray regions represent unmethylated regions and the light gray regions represent methylated regions. Tfre epigenetic maps indicate a region that is substantially unmethylated for the control cells but are substantially methylated for the edited cells.

[0314] This example indicates that CRISPR epigenetic systems can introduce epigenetic modifications to target sites, specified by an associated guide RNA sequence, as shown by the targeted methylation of tire CD151 promoter in HEK293S cells. [0315] The methods described in this example can further be used to screen various CRISPR epigenetic systems and guide RNAs for their ability to edit the desired target sites and refine epigenetic editing to reduce editing of off-target DNA sites. For example, multiple sgRNAs can be screened using these methods and the epigenetic editing can be iteratively improved through improving guide designs to be more accurate/specific for the target site.

Table 3. Details of Transfection Setup

Table 4b. ExpOFF and CD151/CD81 sgRNA sequences

TGACACTCCAGGATGTTCGGGGCAGAGACTACCAGAACGCC ATGAGAGTGTGGTCTAACATCCCCGGCCTGAAGTCCAAACA CGCCCCACTGACACCCAAAGAGGAAGAGTACCTGCAGGCCC AAGTGCGGAGCAGATCCAAACTGGATGCCCCTAAGGTGGAC CTGCTGGTCAAGAACTOTCTOCTGCCCCTGAGAGAGTACTT CAAGTATTTCAGCCAGAACAGCCTGCCTCTCGGCGGACCTT CTAGCGGAGCACCTCCTCCAAGCGGAGGATCTCCTGCTGGA AGCCCTACCTCTACCGAGGAAGGCACAAGCGAGTCTGCCAC ACCTGAGTCTGGCCCTGGCACATCTACAGAGCCTAGCGAAG GTTCTGCCCCTGGATCTCCAGCCGGCTCTCCTACATCTACTG AAGAGGGCACCAGCACCGAGCCATCTGAAGGCAGTGCACC 1 GGC AC AAGCACAGAGCCCTCCGAAAT GGACA AGAAG FAC AGCATCGGCCTGGCCATCGGCACCAATrCTGTI’GGATGGGC CGTGATCACCGACGAGTACAAGGTGCCCAGCAAGAAG1TCA AGGTCCTGGGCAACACCGACCGGCACTCCATCAAGAAGAAT CTGATCGGCGCCCTGCTGTTCGACTCTGGCGAAACAGCCGA AGCCACCAGACTGAAGAGAACCGCCAGAAGGCGCTACACC CGGCGGAAGAACCGGATCTGTTACCTGCAAGAGATCTTCAG CA ACGA GATGGCCA AGGTGGA CGACA GCTTCTTCC AC AGAC TGGAAGAGTCCTrCCTGGTGGAAGAGGATAAGAAGCACGA GCGGCACCCCATCTrCGGCAACATCGTGGATGAGGTGGCCT ACCACGAGAAGTACCCCACCATCTACCACCTGAGAAAGAAA CTGGTGGACAGCACCGACAAGGCCGACCTGAGACTGATCTA TCTGGCTCTGGCCCACATGATCAAGTTCCGGGGCCACTTTCT GA' FCGAGGGCG A' FCT G AA CC C CGACAAC I C CG AC GTGG ACA AGCTGTTCATCCAGCTGGTGCAGACCTACAACCAGCTGTTC GAAGAGAATCCCATCAACGCCTCTGGCGTGGACGCCAAGGC TATCCTGTCTGCCAGACTGAGCAAGAGCAGACGGCTGGAAA ACCTGATCGCTCAGCTGCCAGGCGAGAAGAAGAACGGCCTG TTCGGCAACCTGATTGCCCTGAGCCTGGGCCTGACACCTAA CTTCAAGAGCAACTTCGATCTGGCCGAGGATGCCAAACTGC AGCTGTCCAAGGACACCTACGACGACGACCTGGATAATCTG CTGGCCCAGATCGGCGACCAGTACGCCGACTTGT IT C TGGC CGCCAAGAACCTGTCCGACGCCATCCTGCTGAGCGACATTC

TGAGAGTGAACACCGAGATCACCAAGGCACCTCTGAGCGCC AGCATGATTAAGAGATACGACGAGCACCATCAGGATCTGAC CCTGCTGAAGGCCCTCGTCAGACAGCAGCTCCCAGAGAAGT ACAAAGAGATTTTCTTCGACCAGAGCAAGAACGGCTACGCC GGC FACA1 TGA I GGCGGAGCCAGCCAAGAGGAATTCTACAA GTTCATCAAGCCCATCCTCGAGAAGATGGACGGCACCGAGG AACTGCTCGTGAAGCTGAACAGAGAGGATCTGCTGAGAAA GCAGAGGACCTTCGACAACGGCAGCATCCCTCACCAGATCC ACCTGGGAGAACTGCACGCCATTCTGCGGAGACAAGAGGA CTTTTACCCATTCCTGAAGGACAACCGGGAAAAGATTGAGA AGATCCTGACCTTCAGGATCCCCTACTACGTGGGACCACTG GCCAGGGGCAATAGCAGATTTGCCTGGATGACCAGAAAGA GCGAGGAAACC ATCAC ACC CI GGAACTTCGAGGAAGTGGTG GATA AGGGC GC C AGC GC TC AGTC CI TC AT C GAGC GGATGAC CAACTTCGACAAGAATCTGCCTAACGAGAAGGTGCTGCCCA AGCACAGCCTGCTGTACGAGTACTTTACCGTGTACAACGAG CTGACCAAAGTCAAATACGTGACCGAGGGGATGAGAAAGC

CCG C C IT TC' FGAGC GGC GAG C AGA A A A A GGC C A TCG TCGA T

Example 9: Identifying Off-Target Genomic Sites for Blocking During CRISPR-Guided Epigenetic Editing

[0316] This example demonstrates a method of analyzing the effects of a CRISPR epigenetic editing system across the epigenome and the location of the modifications. This method of analysis can be useful to locate unintended modifications at off-target sites and contribute to designing approaches to minimize unintended modifications, such as selectively blocking off- target sites during CRI SPR-guided epigenetic editing to block those sites from being modified Unintended modifications can result from direct off-target editing by the CRISPR-guided epigenetic editing system or from a long-range effect from an epigenetic edit by the CRISPR- guided epigenetic editing system (e.g., by modulating a signaling pathway).

[0317] In this example, following epigenetic editing of CD151 using the 3 sgRNAs targeting CD 151 shown in Table 3 and methylation sequencing, as described in Example 9, epigenetic maps were generated for other parts of the genome to analyze differentially methylated regions between the control cells and the edited ceils in other parts of the genome that were not targeted by the 3 sgRNAs FIGs. 27 and 28 are example epigenetic maps that were generated that show differentially methylated regions (light gray representing methylated regions and dark gray representing unmethylated regions) between the control cells and the edited cells from the experiment described in Example 9 in regions of chromosome 19 (FIG. 27) and chromosome 12 (FIG. 28). Some of these differentially methylated regions may be a result of direct off-target editing by the CRISPR epigenetic editing system. Others may be a result of a signaling pathway modulation resulting from a change in expression of CD 151. Table 14 provides the full list of genes affected by epigenetic editing of CD151 . The table lists potential off-target edits and genes that may be involved in the same signaling pathway as CD151. Each column provides additional information of each genes is described below. Columns 1-9 represents Browser Extensible Data (BED) fields to generate epigenetic maps.

[0318] Column 1. Cbrom - The name of the chromosome (e.g., chr3, chrY, chr2_random) or scaffold (e g., scaffold 10671).

[0319] Column 2. chromStart - The starting position of the feature in the chromosome or scaffold. The first base in a chromosome is numbered 0.

[0320] Column 3. chromEnd - Tire ending position of the feature in the chromosome or scaffold.

[0321] Column 4. Name - Defines the name of BED line. [0322] Column 5. Score – A score between 0 and 1000. If the track line useScore attribute is set to 1 for this annotation data set, the score value will determine the level of gray in which this feature is displayed (higher numbers = darker gray). [0323] Column 6. Strand – defines the strand, wherein “.” = no strand or “+” = positive strand or “-” = negative strand. [0324] Column 7. thickStart - The starting position at which the feature is drawn thickly (for example, the start codon in gene displays). When there is no thick part, thickStart and thickEnd are usually set to the chromStart position. [0325] Column 8. thickEnd - The ending position at which the feature is drawn thickly (for example the stop codon in gene displays). [0326] Column 9. itemRgb - An RGB value of the form R,G,B (e.g., 255,0,0). If the track line itemRgb attribute is set to “On”, this RBG value will determine the display color of the data contained in this BED line. [0327] Column 10. blockCount - The number of blocks (exons) in the BED line. [0328] Column 11. blockSizes - A comma-separated list of the block sizes. The number of items in this list should correspond to blockCount. [0329] Column 12. blockStarts - A comma-separated list of block starts. All of the blockStart positions should be calculated relative to chromStart. The number of items in this list should correspond to blockCount. [0330] Column 13. #geometric mean pval: Geometric mean of the Fisher Exact Test p-values of all CpGs in the DMR. [0331] Column 14. #geometric mean odds: Geometric mean of the Fisher Exact Test odds ratio of all CpGs in the DMR. [0332] Column 15. #annotation: Genic annotation of the DMR per UCSC database. [0333] Analyzing the locations of the off-target modifications can be used to refine editing methods by designing selective blockers that can be incorporated during CRISPR-guided epigenetic editing to block important off-target sites from epigenetic editing. A method of selectively blocking an off-target site while simultaneously editing a target site is using combinations of orthogonal Cas systems (or Cas systems that do not cross-react), wherein one or more orthogonal Cas systems can be used to selectively block one or more off-target sites (using guide RNAs that guide the respective Cas protein(s) to bind to the off-target sites, thereby- blocking epigenetic modifications), while another orthogonal Cas system introduces an epigenetic modification to a specific target site. In this example, epigenetic mapping was used to identify the location of off-target modifications in chromosome 19 and chromosome 12 resulting from the CRISPR-guided epigenetic editing of CD 151 described in Example 9. Guide RNAs for an orthogonal Cas system comprising a catalytically inactive orthogonal Cas protein can be designed to selectively block those sites of interest via binding. Such an orthogonal Cas system targeting the off-target sites for binding can be used together with the same ExpOFF epigenetic editing system targeting CD151 for methylation (described in Example 9) to refine epigenetic editing.

Example 10: Testing of Orthogonal Cas System

[0334] In this example, an orthogonal Cas system was investigated to facilitate the simultaneous manipulation of multiple epigenetic locations and efficiently combine activation and repression of distinct genomic sites, while avoiding cross-talk among different guide RNAs.

[0335] A total of ten different orthogonal Cas protein variants were designed: 4 variants from ciass IL type II (e.g., Lan, Sagl, Imo); 4 variants from class II, type V (e.g., HkCasl2a, PiCas 12a, Fn3Casl2a and Pb2Casl2a); a representative from class II, subtype V-C (e.g,, Casl2cl) and a representative of Cas^ (e.g., CasPhi-2) (Table 5). These members were selected due to the flexibility offered by the sequence of their PAM motifs, which is well represented in CpG islands. One key feature of these selected molecules is that their distinct RNA guide elements (spacer, crRNA ort.racrRNA) are sufficiently distinct that they may simultaneously mix and match among them without interfering with each other, enabling it to simultaneously methylate and demethylate different areas of the genome while minimizing or eliminating risk for cross-reactivity.

[0336] FIG. 7 shows the different constructs and sgRNA designed that were utilized. In addition to the ExpOFF system described in Example 2, an ExpON epigenetic editing system (e.g., ON system) was also designed, as shown in FIG. 7. The ExpON system was composed of a TET1 protein fused to a catalytically inactive A. pyogenes dCas9. This system served to reverse gene silencing through targeted DNA demethylation. Since the ExpON system alone is not sufficient to ensure expression of the target gene, some of the ExpON systems were designed with a separate module (e.g., MCP VPR) to enable transcriptional activation (FIG. 7). [0337] To test the ability of orthologous Cas systems to simultaneously methylate and demethylate different areas of the genome while minimizing or eliminating risk for crossreactivity, the first step was to verify the acti vity of the different constructs and test whether they can cross-react among themselves by mixing and matching each construct with a different sgRNA. Given the previous results observed with the ExpOFF system (FIG. 9A-9C), CD 151 gene was selected as a target to conduct some of these experiments and sgRNAs were designed for a small subset of constructs (Table 6). In Table 6, underlined sequences in bold represent the PAM sequence, which is removed in the final sgRNA design. Uppercase underlined sequences represent the structural RNA component of the orthogonal Cas, while lowercase represents the spacer targeting a specific genomic location.

[0338] For this initial experimental phase, only silencing activity was tested to triage the initial list of viable orthogonal Cas candidates to combine.

Table 5. Nomenclature and description of the orthologous CAS constructs tested

*sgRNA on variants are modified to incorporate MS2 sequence to engage the VPR transactivator in addition to demethylase TETi fused to the corresponding orthologous cas

Table 6. List of Target sequence and corresponding sgRNAs

Testing of Cross Reactivity of the Orthologous Cas System

[0339] Once the activity of the different orthologous Cas systems was determined, additional experiments were conducted to determine the level of cross-reactivity⁷ among the different constructs. To test this, orthologous Cas were electroporated in HEK293.2sus alone, with the positive control matching sgRNA or with an orthogonal sgRNA.

Following the same methodology as previously described, HEK293.2sus were electroporated with plasmid and corresponding sgRNA, positive and negative controls. Sequences ofsgRNAs used are listed in Table 6. After 72 hours post electroporation, cells expressing transfected DNA (BFP+ cells) from all samples except for the blank control were sorted using FACS to yield an enriched population of successfully transfected cells. These cells were cultured and expanded until enough total cells were present for flow analysis. 13 days after flow sorting, the sorted samples were stained with anti-CD151 antibodies and underwent flow analysis to profile if methylation has occurred at the targeted sites. In samples transfected with gene-targeting sgRNAs, their cognate targets were observed to be down-regulated compared to the blank control. A summary of the conditions and results obtained can be found in Table 7.

Table 7. Summary of orthologous Cas cross-reactivity testing

Condition Orthologous Cas sgRNA CD151 Downregulation

1 ExpOFF Control

(negative)

2 ExpOFF sgEXP -i— j— j-

(positive)

3 ExpOFF sgLan

4 ExpOFF sgPhi2

5 ExpOFF sgFn3 -

6 ExpOFF sgTIk

7 Lan _ OFF Control

(negative)

8 Lan OFF sgLan +++

(positive)

Multitarget Bidirectional Epigenetic Editing Using Orthologous Cas

[0340] Utilizing all the above validated tools, a series of experiments were conducted to simultaneously regulate multiple genes at once, utilizing the orthogonal Cas system to promote gene activation and repression while avoiding cross-talk. For this experiment, ExpON with VPR system targeting both ACE2 and LRRC15 was combined with the best performing OFF system that demonstrated less cross-reactivity with ExpOFF (e.g., CasPhi2_OFF using sgRNAs against both CD151 and CD81), ExpON plasmid and MCP- VPR plasmid that were used is shown in FIG. 10B and FIG. IOC. Sequences of sgRNAs targeting ACE2, sgRNAs targeting LRRC15, ExpON and exemplary MCP-VPR is shown in Table 8.

[0341] Following the same methodology as previously described, HEK293.2sus were electroporated with plasmid and corresponding sgRNA, positive and negative controls. The experimental conditions are outlined in Table 9. CasPhi2 OFF sequences referenced in Table 9 correspond to SEQ ID NOs: 23, 24, and 25 for targeting CDI51 (Table 6), and SEQ ID NOs: 100, 101, and 102 for targeting CD81 (Table 6). The ExpOFF sgEXP sequences referenced in Table 9 correspond to SEQ ID NOs: 88, 89, and 90 for targeting CD151 (Table 4b), and SEQ ID NOs: 91 , 92, and 93 for targeting CD81 (Table 4b). Two sgRNAs were used for targeting ACE2 and LRRCI5 (SEQ ID NOs: 103, 104, 105, 106; Table 8). After 72 hours post electroporation, cells expressing transfected DNA (BFP+ cells) from all samples except for the blank control were sorted using FACS to yield an enriched population of successfully transfected cells. These cells were cultured and expanded until enough total cells were present for flow analysis. 13 days after flow sorting, the sorted samples were stained with anti-CD151 antibodies and underwent flo w analysis to profile if methylation has occurred at the targeted sites. In samples transfected with gene -targeting sgRNAs, their cognate targets were observed to be down-regulated compared to the blank control. A summary of the results is detailed in Table 9.

Table 8. Sequences of sgRNAs targeting ACE2, sgRNAs targeting LRRC15, ExpON and

MCP-VPR

Name SEQ Sequences

ID NO. sgRNA 103 AGGAGAGGUAAGGUUCUCUGUUUAAGAGCUAaGCCAACAUG ~~ AGGAUCACCCAUGUCUGCAGGGCaUAGCAAGUUUAAAUAAG GCUAGUCCGUUAUCAACUUGGCCAACAUGAGGAUCACCCAU

GUCUGCAGGGCCAAGUGGCACCGAGUCGGUGCUUUUUUU sgRNA ; 104 GGCCAUAAAGUGACAGGAGGUUUAAGAGCUAaGCCAACAUG

MS2 AGGAUCACCCAUGUCUGCAGGGCaUAGCAAGUUUAAAUAAG

ACE2_ 2 \ GCUAGUCCGUUAUCAACUUGGCCAACAUGAGGAUCACCCAU

GUCUGCAGGGCCAAGUGGCACCGAGUCGGUGCUUUUUUU

GAGCCTCTGTCCGACGATCCTCTGAGCCCTGCCGAGGAAAAG CTGCCCCACATCGACGAGTATTGGAGCGACAGCGAGCACATC TTTCTGGACGCCAATATCGGCGGCGTGGCAATCGCTCCTGCT CACGGATCTGTGCTGATCGAGTGCGCCAGAAGAGAGCTGCAC GCCACCACACCTGTGGAACACCCCAACAGAAATCACCCCACC AGGCTGTCCCTGGTGITCTACCAGCACAAGAATCTGAACAAG CCCCAGCACGGCTrCGAGCTGAACAAGA'n'AAGITCGAGGCC AAAGAGGCTAAGAACAAGAAGATGAAGGCCAGCGAGCAGA AGGACCAGGCCGCTAACGAAGGACCTGAGCAGAGCAGCGAA GTGAACGAGCTGAATCAGATCCCCAGCCACAAGGCCCTGACA CTGACCCACGACAACGTGGTCACCGTGTCTCCATACGCTCTG AC C CA I GTGGC CGGAC C T TACAACCAC1 GGGT FGGAGGACC F TCTAGCGGAGCCCCTCCACCITCTGGTGGATCrCCAGCAGGC AGCCCTACAAGCACAGAGGAAGGCACAAGCGAGAGCGCCAC ACCTGAATCTGGCCCTGGCACATCTACAGAGCCTAGCGAAGG ATCTGCCCCTGGCTCTCCTGCTGGAAGCCCTACCTCTACAGAA GAGGGCACCAGCACCGAACCTAGCGAGGGAAGTGCTCCTGG AACCAGCACAGAGCCCTCCGAGATGGACAAGAAGTACAGCA TCGGACTGGCCATCGGCACCAATTCTGTTGGCTGGGCCGTGA TCACCGACGAGTACAAGGTGCCCAGCAAGAAAITCAAGGTG CTGGGCAACACCGACCGGCACAGCATCAAGAAAAACCTGAT CGGCGCCCTGCTGTTCGACTCTGGCGAAACAGCTGAGGCCAC ACGGCTGAAGAGAACTGCCAGAAGAAGATACACCAGACGGA AGAACCGGATCTGCTACCTGCAAGAGATCTTCAGCAACGAGA TGGCCAAGGTGGACGACAGCTTC FT CCA T CGGC TGGAAGAGT CCTTCCTGGTCGA GGA AGATA AGAAGCA CGA GCGGCACCCC ATCTTCGGCAACATCGTGGATGAGGTGGCC’FATCACGAGAAG TACCCCACCATCTACCACCTCCGGAAGAAACTGGTGGACAGC ACCGACAAGGCCGACCTGAGACTGATCTATCTGGCTCTGGCC CACATGATCAAGTTCCGGGGCCACTTFCTGATCGAGGGCGAT CTGAACCCCGACAACTCCGACGTGGACAAGCTGTTTATCCAG CTGGTGCAGACCTACAACCAGCTGTTCGAGGAAAACCCCATC A ACGC C AGCGGC G FGG AC GC I A AGGCT A FCCTG TCTGCC AG A CTGAGCAAGTCCAGACGGCTGGAAAATCTGATCGCCCAGCTG CCTGGCGAGAAGAAGAATGGCCTGTTCGGCAACCTGATTGCC CTGAGCCTGGGCCTGACACCTAACTTCAAGAGCAACTFCGAC CTGGCCGAGGACGCCAAACTGCAGCTGAGCAAGGACACCTA CGACGACGACCTGGACAATCTGCTGGCCCAGATCGGCGATCA G1 ACGCCGAC FTGF3 FCTGGCCGC I AAGAACCTGAGCGACGC CATCCTGCTGAGCGATATCCTGAGAGTGAACACCGAGATCAC A A AGGC C C CTC TGAGCGC CTCTATGATCA AGAGATACGACGA ACACCACCAGGACCTGACTCTGCTGAAGGCCCTCGTTAGACA GCAGCTGCCCGAAAAGTACAAAGAGATnTCTTCGACCAGAG CAAGAACGGCTACGCCGGCTACATFGATGGCGGAGCCAGCC

AAGAGGAATTCTACAAGTTCATCAAGCCGATCCTCGAGAAGA TGGACGGCACCGAGGAACTGCTGGTCAAGCTGAATAGAGAG GACC I’GCTGCGGAAGCAGCGGACCTTCGACAATGGCTCTATC CCTCACCAGATCCACCTGGGCGAGCTGCATGCCATCCTGAGA AGGCAAGAGGACTTTTACCCATTCCTGAAGGACAACCGGGAA AAGATTGAGAAGATCCTGACCTTCAGGATCCCGTACTACGTG GGACCACTGGCCAGAGGCAATAGCAGATTCGCCTGGATGACC

AGAAAGAGCGAGGAAACCATCACACCCTGGAACT1 CGAGGA

CTCCCTGTTCGAGCTGGAAAACGGCCGGAAGAGAATGCTGGC

CTCTGCTGGCGAACTGCAGAAGGGAAACGAACTGGCTCTGCC

CTCCAAATATGTGAACTTCCTGTACCTGGCCTCTCACTACGAG

AAACTGAAGGGCAGCCCCGAGGACAATGAGCAAAAGCAGCT

GTTTGTCGAGCAGCACAAGCACTACCTGGACGAGATCATCGA

GCAGATCTCCGAGTTCAGCAAGCGCGTGATCCTGGCCGACGC

CAATCTGGATAAGGTGCTGAGCGCTTACAACAAACACAGGG

ATAAGCCCATCAGAGAGCAGGCCGAGAATATCATCCACCTCT

TCACCCTGACAAACCTGGGAGCCCCTGCCGCCTTTAAGTACT

TCGATACCACCATCGACCGGAAGCGGTACACCTCCACCAAAG

AGGTCCTGGACGCTACCCTGATTCACCAGAGCATCACCGGCC

TGTACGAGACAAGAATCGATCTGTCCCAGCTCGGAGGCGACG

GTGGCGGAGGATCTCCCAAGAAAAAGCGGAAGGTGGACCCC

AAAAAGAAGAGAAAGGTCGACCCTAAAAAGAAACGGAAAGT

CGGCGGCTCCGGCGCCACCAATTTCTCACTGCTTAAACAGGC

CGGCGACGTGGAAGAGAACCCTGGACCTAGCGAACTGATCA

AAGAAAACATGCACATGAAGCTCTACATGGAAGGCACCGTG

GACAATCACCACTTCAAGTGCACCAGCGAAGGCGAGGGCAA

GC CT FA TGAGGGC A C C CA GAC A AT G CGGAT C A AG GTC G TGGA

AGGCGGCCCTCTGCCATTCGCCTTTGATATCCTGGCTACCAGC

TTTCTGTACGGCAGCAAGACCTTCATCAATCACACCCAGGGC

ATCCCCGATTTCTTCAAGCAGAGCTTCCCCGAGGGCTTCACCT

GGGAGAGAGTGACCACATACGAAGATGGCGGCGTGCTGACC

GCCACACAGGATACAAGTCTCCAGGACGGCTGCCTGATCTAC

AACGIGAAGArCCGGGGCGTGAACTICACCAGCAACGGCCCC

GTGATGGAGAAGAAAACCCTTGGCTGGGAAGCCTTCACCGAG

ACACTGTACCCTGCAGACGGTGGCCTGGAAGGCAGAAACGA

TATGGCCCTGAAGCTCGTCGGAGGCTCTCACCTGATCGCTAA

CATCAAGACCACCTACAGAAGCAAGAAGCCTGCCAAGAACC

TCAAGATGCCCGGCGTGTACTATGTGGACTACCGGCTGGAAC

GCATCAAAGAGGCCAACAACGAGACATACGTGGAACAGCAC GAGG FGGCCGT GGC TAGA TACTGCGA TCTGCCT AGCAAGCTG GGCCACAAGCTGAACTAG

Ex p O N ? 95 MALPTCSCLDRVIQKDKGPYYTHLGAGPSVAAVREIMENRYGQ protein KGNAIRIEIVVYTGKEGKSSHGCPIAKWVLRRSSDEEKVLCLVR sequence QRTGHHCPT AVMV VLIMVWDGIPLPMA DRLYTELTENLK S YNG HPTDRRCTLNENRTCTCQGIDPETCGASFSFGCSWSMYFMGCKF

GRSPSPRRFRIDPSSPLHEKNLEDNLQSLATRLAPIYKQYAPVAY

QNQVEYENVARECRLGSKEGRPFSGVTACLDFCAHPHRDIHNM NNG STWCTLTREDNRSLGVIPQDEQLFTVLPLYKLSDTDEFGSK

EGMEAKIKSGAIEVLAPRRKKRTCFTQPVPRSGKKRAAMMTEV IAHKIRAVEKKPIPRIKRKNNSTTTNNSKPS SLPTLG SNTETVQPE

VKSETEPHFILKSSDNTKTYSLMPSAPHPVKEASPGFSWSPKTAS ATPAPLKNDATASCGFSERSSTPHCTMPSGRLSGANAAAADGPG ISQLGEVAPLPTLSAPVMEPLINSEPSTGVTEPLTPHQPNHQPSFL

TSPQDLASSPMEEDEQHSEADEPPSDEPLSDDPLSPAEEKLPHIDE

YWSDSEHIFLDANIGGVAIAPAHGSVLIECARRELHATTPVEHPN

§ RNHPTRLSLVFYQHKNLNKPQHGFELNKIKFEAKEAKNKKMKA

SEQKDQAANEGPEQSSEV’NELNQIPSIIKALTLTHDNWTVSPYA

Confirmation of Multitarget Bidirectional Epigenetic Editing Using Orthologous Cas via DNA Epigenetic Analysis

[0342] To confirm that the changes in expression observed when combining ExpON and CasPhi2 systems were a direct result of changes in DNA methylation patterns, endpoint samples were collected from the experiment detailed in Table 9 for DNA extraction and downstream sequencing.

[0343] DNA was extracted from 2xl0⁶ cells with PureLinK Genomic DNA Mini Kit (Thermo Fisher Scientific, Waltham, MA, USA), foilowing manufacturer instructions. Bisulfite conversion of up to one microgram of gDNA was performed using the EZ DNA Methylation-

Direct Kit (Zymo Research, Inc., Irvine, CA, USA), followed by column-based purification.

[0344] Next, fifty nanograms of purified, bisulfite -converted DN A was amplified by PCR using KAPA HiFi Hotstart Uracil + Kit (Roche, Basel, Switzerland), with lx KAPA HiFi HotStart Uracil+ ReadyMix, 0.3 pM forward tailed primer (including universal Nextera Read! at the 5’ end of the primer; Table 10), 0.3 pM reverse tailed primer (including universal Nextera Read2 at the 5’ end of the primer; Table 10), with the following thermal program: denaturation at 98°C for 2 min.; 35 cycles of 98°C for 15 s, 62°C for 30 s and 72°C for 30 s; final extension of 72°C for 3 min. PCR products w'ere purified with 1 ,5X volumes of Mag-Bind TotalPure NGS beads (Omega Bio-tek, Norcross, GA, USA) and quantified by Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA). [0345] The yield and specificity of purified PCR products were analyzed using the Fragment Analyzer system and the HS NGS Fragment Kit (l-6000bp; Agilent Technologies, Santa. Clara, California, USA). During method development, the sequence specificity of each amplicon was verified by Sanger sequencing (Elim Biopharmaceuticals Inc., Hayward, CA, USA).

[0346] Dual-indexing Next Generation Sequencing (NGS) libraries were prepared by amplifying 2 uL of purified PCR product with lx GXL Buffer, 0.62U PrimeSTAR GXL DNA Polymerase, 0.8 mM dNTP Mix, with unique combinations of 0.1 pM Nextera P5-X, and 0.1 pM Nextera P7-X oligos (see Table 11), using the following thermal program: denaturation at 98°C for 3 min.; 14 cycles of 98°C for 10 s, 60°C for 30 s and 68°C for 30 s; final extension of 68°C for 3 mm. Libraries products rvere purified with IX volume of Mag-Bind TotalPure NGS beads (Omega Bio-tek, Norcross, GA, USA), and eluted in 15 pL of 10 mM Tris HC1 pH 8.0, 0.1 mM EDTA. Upon confirmation of the absence of adapter dimers by Fragment Analyzer, (HS NGS Fragment Kit (l-6000bp), the libraries were quantified using the Kapa Library Quant Kit (Illumina), Lightcycler 480 qPCR Kit.

Table 10. Sequen ce of primer-specific, Nextera-tailed PCR oligonucleotides

Oligo_lD i SEQ Oligonucleotide Sequence 5' -> 3'

: ID : NO. 1 forward t;ulcd primer 34 TCGTCGGCAGCGTCAGATGTGTATAAGAGAC'AGN i j NNNNNNNNNNNNNNN AGAGACAG :

CD81 sgl 2 BS Pair? i 42 GTGGGGTTTATGGAGGGG

! FW i

CD81_sgl_2_BS_Pair2_ i 43 TACACTTAATACAACCCTCCACTC

RV 1

CD81_sg3_Pairl_FW i 44 AGGGAGGAATGGGTTGTTCTCCC

CD81_sg3_Pairl_RV ! 45 ACTTATAGGGCGCCGCGGTCC

CD81__sg3_ Pair2_FW ! 46 ATGGGTTGTTCTCCCGGCA

CD81_sg3_Pair2_RV ! 47 CTTATAGGGCGCCGCGGT

Table 11. Sequence of indexing P5/15 and P7/i7 oligonucleotides

were further diluted to 7.5 pM and spiked with 15% PhiX control v3 (Illumina, San Diego, CA, USA) before denaturing and sequencing on a MiSeq with MiSeq Reagent Kit v2 and 2 x 151 cycles

[0348] The quality of the sequencing reads was assessed with FastQC (https://github.com/s- andrews/FastQC). Next, read! and read2 .fastq files were merged using Flash (htps://ccb.jhu.edu/sofhvareZFLASH/) and reads with a Phred score < 30 were filtered out. Merged reads were aligned against the amplicon reference sequence from HG38 using a methylation-specific Burrows-Wheeler aligner (BWA-meth; https://github.com/brentp/bwa- meth). Samtools (https://github.com/samtools/samtools), was used to convert .sam into .bam, as well as to sort and index .bam files. The methylation levels were analyzed with amplikyzer2 (https://bitbucket.oig/svenrahmann/amplikyzer/wiki/Home) and analyzed to quantify changes in DNA methylation using bisulfite conversion PC R and NGS sequencing.

[0349] Methylation changes relative to control for multitarget bidirectional epigenetic regulation using ExpOFF and CasPhi2 is shown in Table 12. The experimental conditions are also outlined in Table 12. CasPhi2 OFF sequences referenced in Table 12 correspond to SEQ ID NOs: 23, 24, and 25 for targeting CD151 (Table 6). and SEQ ID NOs: 100, 101, and 102 for targeting CD81 (Table 6). The ExpOFF sgEXP sequences referenced in Table 12 correspond to SEQ ID NOs: 88, 89, and 90 for targeting CD151 (Table 4b), and SEQ ID NOs: 91, 92, and 93 for targeting CD81 (Table 4b). Two sgRNAs were used for targeting ACE2 and LRRC15 (SEQ ID NOs: 103, 104, 105, 106; Table 8).

Table 12. Summary of Methylation Change Relative to Control for Multitarget Bidirectional Epigenetic Regulation Using ExpOFF and CasPhiS Systems

[0350] Altogether, the data shown demonstrated that it is possible to specifically induce epigenetic silencing of the CD151 molecules in Hek293.2sus cells using transient transfection methods using diverse orthologous Cas systems optimized to promote DMA methylation and transcriptional repression. Additionally, when combined with TET1. data demonstrated that it is possible to activate gene expression in ACE2 and LRRC15 genes when combined with the potent transcriptional chimeric activator VPR. Combining both systems, we demonstrate that it is possible to simultaneously activate and repress different genomic locations while avoiding cross-reactivity, achieving efficient upregulation of ACE2 and LRRC15 while repressing CD81 and CD 151.

[0351] Furthermore, all the measured changes in expression were a direct result of underlying changes in DNA methylation, as determined by PCR bisulfite sequencing.

[0352] These findings collectively show' that with the help of orthogonal epigenetic programmable Cas systems, long-lasting, two-way epigenetic alterations targeting multiple sites can be effectively achieved.

Example 11: Assessing the impact of various treatments on the methylome of CD8+ T cell

[0353] This example shows a methodology to assess the impact of various treatments on the methylome of CD8+ T cells.

[0354] Methylome sequencing via nanopore sequencing was performed from sorted naive, central memory (CM), effector memory (EM), and effector CD8+ T cell subsets. CD8 + T cells treated with vehicle, rapamycin, a GSK-3beta inhibitor (TWS119), or a hypomethylation agent (decitabine) were also subjected to sequencing. With the data from sequencing, reference DMR from effector and naive cells were created by first merging the sequencing data files (e.g., beta files) from effector and naive cells. DMR files were then generated between the merged effector and naive data files (e.g., beta files) and the DMR files were consolidated for epigenetic map generation. DMR configuration required fisher exact test comprising of 1 ) p-va.lue < dmrThreshold (0.01) 2) max base pair (bP) spanned by CpGs < bpWin (TOO bp) (fisherFixed DMR.r) 3) minimum number of CpGs in a region of interest (ROI) > minROIbpc (3). All DMRs within a 5000 base pair window were combined and then centered in the 5000 base pair window'. Table 15 show's the number of CpGs contained in the DMRs between various subsets (e.g., naive, CM, EM, and effector) and treated T-cells (treatment with vehicle, rapamycin, TWS 119, and decitabine).

Table 15. Number of CpGs contained in the DMRs between various subsets and treated T- cells

[0355} Furthermore, computational analysis was used to generate fragment files from the consolidated files for each region of interest (ROI), using the following configurations: 1) no moving average to eliminate averaging over ROI CpGs that are few' in number 2) limit to 20 fragments per sample 3) for each DMR, compute the percentage of fragments from each label (e g, cell groups; treatment groups: rapamycin TWS 119, decitabine) that appear in each cluster, 4) generate a label-cluster association score, where the percentage of fragments in a given D MR was calculated in different clusters. As shown in Table 16, for effector cells, 55% of fragments in this DMR were in Cluster 1, while 45% of fragments were in Cluster 2.

Table 16. Label-Cluster Association Score

[0356] Taking the label-cluster association score, how well a certain label (e.g, cell groups, treatment groups) associates with the remaining labels was calculated. For example, to calculate how well rapamycin treated cells associations or clusters with the effector cells, cluster probabilities for effector cells were multiplied by the Rapamycin-cluster probability and then summed (e.g., 0.15*(0.55) + 0.45*(0 85) ^:::0.465). The calculated association score of how well the rapamycin-treated cells associated with each label (e.g , effector cells, naive cells, vehicle- treated cells) is shown in Table 17. This was repeated for each DMR, resulting in a matrix of association scores versus DMR for each label. Table 17. Association Score

[0357] Analyzing ail association scores for Rapamycin-treated ceils versus the other labels for all naive-effector DMRs (with > 1 cluster) revealed that the Rapamycin labei associated most closely with the vehicle and naive populations. This indicated that there was little difference between the vehicle and treatment group, and that both groups were also more similar to the naive methylome than the effector methylome baseline,

[0358] Despite minimal differences at the whole genome level, specific DMRs were also analyzed with the DMR-level association scores to identify DMRs where the Rapamycin label may have a unique epigenetic state. To do so, DMRs with low association scores tor other non- Rapamycin labels were searched. Methylation maps of GSE1 gene and IL2RB gene showed that Rapamycin label had a separate epigenetic state compared to other labels.

[0359] Additionally, while vehicle and Rapamycin labels mostly clustered with the naive population, in some cases Rapamycin-treated cells clustered primarily with the effector population, while the naive and vehicle population clustered separately in a DMR in the DHX9 gene.

[0360] Further, DMRs where Rapamycin clustered closely with the naive population but distinct from the effector and vehicle population was searched. 1FNG-AS1 was one example of such case.

[0361] Similarly, association scores were calculated and analyzed for TWS119 versus the other labels. The differentially methylated regions in TWS 119 and Rapamycin-treated cells were found to be distinct with minimal overlap in specific DMRs. Histogram of all the association scores for TWS 119 versus the other labels for all naive-effector DMRs showed that the TWS 119 label associated most closely with the vehicle and naive populations. This data indicated that there are little differences between the vehicle and treatment groups, and further, that both groups are more similar to the naive methylome than the effector methylome baseline. Epigenetic maps of DMR in various genes (e.g, BCL1 IB, AKAP13, AXIN1, SEPTIN 9) also showed similar patterns.

Example 12: Epigenetic maps of Thl7 versus Treg DMRs

[0362] Similar to the methodology described in Example 12, DMR and epigenetic maps were generated for sorted 11117 and Treg cells, and then analyzed to obtain label-cluster association scores The label-cluster association was filtered to get region of interests (ROIs) with Thl7 Purity Score > 0.7 Treg Label Association Scores < 0.3 to balance the selection of ROIs/DMRs that have high average purity in a cluster (e g, most of the fragments for a label fall in a single cluster) and low association (e.g, most of the fragments for a label fall in different clusters from one another). Next, Homer transcription factor motif analysis was performed on DMRs that were extracted from the filtered ROIs to look for enriched transcription factor motifs or footprints.

[0363] Of the 318 DMRs that were generated from Till 7 and Treg sequencing data, only 5 DMRs showed a Thl7 Purity Score > 0.7 Treg Label Association Scores < 0.3. Table 18 summarizes the purity score and association score of the five DMRs.

Table 18. Purity and Association scores of Thl7 and Treg DMRs.

[0364] For each DMR, top 15 motifs based on m-score were filtered out. Tables 19-23 show's the 15 motifs for each DMR (e.g, CCND2, CD247, ENOX2, YBEY, ARX). Column A represents the ROI/DMR, column B represents genic annotation for associated ROI/'DM R, and columns c-Q represent the top 15 enriched transcription factor motifs based on the Homer m- score. [0365] It should be understood from the foregoing that, while particular implementations of the disclosed methods and systems have been illustrated and described, various modifications can be made thereto and are contemplated herein. It is also not intended that the disclosure be limited by the specific examples provided within the specification. While the disclosure has been described with reference to the aforementioned specification, the descriptions and illustrations of the preferable embodiments herein are not meant to be construed in a limiting sense.

Furthermore, it shall be understood that all aspects of the disclosure are not limited to the specific depictions, configurations or relative proportions set forth herein which depend upon a variety of conditions and variables. Various modifications in form and detail of the embodiments of the disclosure will be apparent to a person skilled in the art. It is therefore contemplated that the disclosure shall also cover any such modifications, variations and equivalents.

Example 13: Construction of the Epigenome from DNA Fragments of Blood Samples

[0366] Method where no biopsies are required to construct the epigenome of an individual’s cells or tissues is developed, as shown in FIG. 33. As shown in the top arm of FIG. 33, various samples, gathered without biopsy, can be collected. cfDNA or ceils in these samples are profiled to extract epigenetic signatures as well as assigned to a tissue of origin. This can provide a current view of the epigenetic status of various tissues in the body.

[0367] Thus, rather than obtaining biopsies tissue samples (e.g., liver), an individual’s blood was drawn to map methylation (CpG) sites in the genome. Blood samples from 23 healthy individuals were obtained. Whole blood is collected in Streak or EDTA tubes (e.g., 10 mL). Next plasma is extracted by spinning the whole blood tubes at 1500xg for 10 minutes at 20°C at an acceleration and deceleration at 20% of maximum The plasma layer is aseptically pipetted into a labeled 15 ml conical tube without disturbing the buffy coat and red blood ceil layer. The plasma is spun at 16000xg for 10 minutes at 20°C at an acceleration and deceleration at 20% of maximum. 1.0 mL of the double spun plasma is aseptically pipeted into labeled 1.0 mL Matrix cryoviais without disturbing the pellet. The aliquots for either stored at -80°C for later use, or cfDNA is extracted from the plasma using a standard kit (e.g., Beckman Apostle MiniMax high efficiency cfDNA isolation kit or QIAmp circulating nucleic acid kit) Sequencing libraries for individual are prepared from the cell-free DNA and then sequenced using illumina sequencing. Molecular deconvolution of the sequencing data from the cell free DNA library are performed. [0368] As shown in the bottom arm of FIG. 33, in some instances, this method can be applied to iPSC-derived tissues or cell types to profile the epigenome PMBCs collected from a blood draw can be reprogrammed into iPSC and subsequently differentiated into various tissues of interest.

These tissues can then be profiled as described herein to extract epigenetic signatures. A differential analysis of the epigenetic signatures of both arms shown in FIG. 33 may provide insight into how the epigenome for a specific tissue changes relative to a common baseline (e.g., iPSC-derived epigenetic signature).

Table 21. Top 15 motifs for ENOX2 DMR

Table 22. Top 15 motifs for ¥BE¥ DMR

Table 23. Top 15 motifs for ARX DMR

ENUMERATED EMBODIMENTS 1. A method of identifying a target genomic site for epigenetic editing, comprising: (a) providing a first epigenetic map of a target cell in an initial cellular state, wherein the first epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the target cell; (b) providing a second epigenetic map of a desired cell in a desired cellular state, wherein the second epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the desired cell; (c) comparing the first epigenetic map and the second epigenetic map, thereby detecting a first differential; and (d) identifying a target genomic site in the plurality of genomic sites using the first differential, wherein (i) the target genomic site is in an initial epigenetic state in the target cell, and (ii) the target genomic site is in a desired epigenetic state in the desired cell, wherein the initial epigenetic state and the desired epigenetic state are different epigenetic states. 2. The method of embodiment 1, wherein the epigenetic map provides a methylation state, a 5’ hydroxymethylation state, a chromatin accessibility state, or a histone modification state. 3. The method of embodiment 1, wherein the initial epigenetic state is an unmethylated state and the desired epigenetic state is a methylated state. 4. The method of embodiment 1, wherein the initial epigenetic state is a methylated state, and the desired epigenetic state is an unmethylated state. 5. The method of embodiment 1, wherein the initial epigenetic state is an acetylated state, and the desired epigenetic state is an unacetylated state. 6. The method of embodiment 1, wherein the initial epigenetic state is an unacetylated state and the desired epigenetic state is an acetylated state. 7. The method of any one of embodiments 1-6, wherein the initial cellular state is a diseased state, and the desired cellular state is a healthier state relative to the initial cellular state. 8. The method of any one of embodiments 1-7, wherein the initial cellular state is an exhausted state, and the desired cellular state is a rejuvenated state relative to the initial cellular state. 9. The method of any one of embodiments 1-8, wherein the desired cellular state is a younger state relative to the initial cellular state. 10. The method of any one of embodiments 1-9, wherein the desired cellular state is a less differentiated state relative to the initial cellular state. 11. The method of any one of embodiments 1-10, wherein the desired cellular state comprises a higher level of stemness relative to the desired cellular state. 12. The method of any one of embodiments 1-11, wherein the desired cell in the desired cellular state comprises a desired cellular functional state. 13. The method of any one of embodiments 1-12, wherein a cell in the desired cellular functional state comprises a desired phenotype. 14. The method of any one of embodiments 1-13, wherein the plurality of genomic sites comprises a whole genome of the target cell. 15. The method of any one of embodiment 1-14, wherein the first epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites at single nucleotide resolution. 16. The method of any one of embodiment 1-14, wherein the second epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites at single nucleotide resolution. 17. The method of any one of the preceding embodiments, further comprising generating the first epigenetic map. 18. The method of any one of the preceding embodiments, further comprising generating the second epigenetic map. 19. The method of any one of the preceding embodiments, further comprising: providing a third epigenetic map of an off-target cell, wherein the third epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the off-target cell; and wherein (d) further comprises detecting an epigenetic state of the target genomic site in the off-target cell, wherein the epigenetic state of the target genomic site in the off-target cell and the desired epigenetic state are the same epigenetic state. 20. The method of embodiments 19, further comprising comparing the third epigenetic map with a fourth epigenetic map of a cell in the initial cellular state, thereby detecting a second differential and using the second differential to identify the target genomic site in the plurality of genomic sites. 21. The method of embodiments 19 or 20, wherein the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the first cell type and the second cell type are of different cell types. 22. The method of any one of embodiments 19-21, wherein the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the off-target cell is produced by modifying an initial cell of the first cell type using a drug. 23. The method of embodiment 22, wherein the drug is capable of epigenetic editing. 24. The method of embodiment 22 or 23, wherein the drug is a small molecule inhibitor. 25. The method of embodiment 24, wherein the small molecule inhibitor is selected from rapamycin, a GSK-3 beta inhibitor, or a hypomethylation agent. 26. The method of embodiment 22 or 23, wherein the drug is fusion polypeptide or a nucleic acid encoding the fusion polypeptide. 27. The method of embodiment 26, wherein the fusion polypeptide comprises a nucleic acid binding moiety. 28. The method of embodiment 27, wherein the nucleic acid binding moiety comprises a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a zinc finger domain, a TAL domain, a tetR domain, a meganuclease, or an oligonucleotide. 29. The method of any one of embodiments 26-28, wherein the fusion polypeptide comprises an effector moiety. 30. The method of embodiment 29, wherein the effector moiety comprises a DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1,MET1, DRM2, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e., LSD1), KDM1B (i.e., LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1, KAT2A, KAT3A, KAT3B, or KAT13C, or a functional equivalent. 31. The method of any one of embodiments 19-30, wherein the target cell is from a target tissue and the off-target cell is from an off-target tissue, wherein the target tissue and the off-target tissue are different tissues. 32. The method of any one of embodiments 1-31, wherein the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an olfactory cell, an auditory cell, or a kidney cell. 33. The method of any one of embodiments 1-32, wherein the target cell is a liver hepatocyte. 34. The method of any one of embodiments 1-33, wherein the off-target cell is a pancreatic acinar cell or a gastric epithelial cell. 35. The method of any one of embodiments 19-34, further comprising generating the third epigenetic map. 36. The method of any one of embodiments 19-35, further comprising generating the fourth epigenetic map. 37. The method of any one of embodiments 1-36, further comprising: providing an initial epigenetic map of a target cell in the initial cellular state, wherein the initial epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the target cell; providing a plurality of epigenetic maps of a plurality of off-target cells, wherein the plurality of epigenetic maps provides an epigenetic state of each genomic site of the plurality of genomic sites in each off-target cell in the plurality of off-target cells; and comparing the initial epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells, thereby detecting a third differential between the third epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells; wherein (d) further comprises using the third differential to identify the target genomic site in the plurality of genomic sites, wherein the target genomic site is in the desired epigenetic state in each off-target cell in the plurality of off-target cells. 38. The method of embodiment 37, wherein the first epigenetic map and the initial epigenetic map is the same epigenetic map. 39. The method of embodiment 37 or 38, wherein the target cell is of a first cell type, and each off-target cell of the plurality of off-target cells is of a cell type that is different from the first cell type. 40. The method of any one of embodiments 37-39, wherein the plurality of off-target cells comprises at least two off-target cells of different cell types. 41. The method of any one of embodiments 37-40, wherein the target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and the off-target tissues are different tissues. 42. The method of any one of embodiments 37-41, wherein the target cell is a liver hepatocyte. 43. The method of any one of embodiments 37-42, wherein the plurality of off-target cells comprises a pancreatic acinar cell or a gastric epithelial cell. 44. The method of any one of embodiments 37-43, wherein the plurality of off-target cells comprises a pancreatic acinar cell and a gastric epithelial cell. 45. The method of any one of embodiments 19-44, further comprising generating the third epigenetic map. 46. The method of any one of embodiments 37-45, further comprising generating the plurality of epigenetic maps of the plurality of off-target cells. 47. The method of modifying a target cell, comprising: (a) identifying a target genomic site for epigenetic editing according to the method of any one of embodiments 1-46, (b) providing a target cell in the initial cellular state, wherein the provided target cell comprises the target genomic site in the initial epigenetic state; and (c) contacting the provided target cell with an epigenetic effector, wherein the epigenetic effector modifies the target genomic site from the initial epigenetic state to the desired epigenetic state, thereby producing a modified cell, wherein the modified cell is in a modified cellular state. 48. The method of embodiment 47, wherein the modified cellular state is functionally more similar to the desired cellular state than the initial cellular state is to the desired cellular state. 49. The method of embodiment 47 or 48, further comprising profiling a function of the modified cell. 50. The method of any one of embodiments 47-49, wherein the modified cell exhibits a modified phenotype that is different from an initial phenotype of the target cell. 51. The method of embodiment 47-50, where the modified phenotype is more similar to a desired phenotype of the desired cell in the desired cellular state than the initial phenotype is to the desired phenotype. 52. The method of any one of embodiments 47-51, further comprising profiling a phenotype of the modified cell. 53. The method of any one of embodiments 47-52, wherein modifying the target genomic site from the initial epigenetic state to the desired epigenetic state turns on expression of a gene. 54. The method of any one of embodiments 47-53, wherein modifying the target genomic site from the initial epigenetic state to the desired epigenetic state turns off expression of a gene. 55. The method of any one of embodiments 47-54, wherein the epigenetic effector comprises: (i) an effector moiety; (ii) a first CRISPR/Cas domain; and (ii) a guide RNA complexed with the first CRISPR/Cas domain, wherein the guide RNA targets the epigenetic effector to the target genomic site. 56. A method of screening a guide RNA for epigenetic editing, comprising: (a) modifying an initial target cell according to the method of any one of embodiments 47-55, thereby producing a modified cell; (b) generating a fifth epigenetic map of the modified cell, wherein the fifth epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the modified cell; (c) comparing the fifth epigenetic map with a sixth epigenetic map, wherein the sixth epigenetic map is generated from a cell that is not treated with the epigenetic effector, thereby generating a fourth differential; (d) using the fourth differential to detect an off-target modification, wherein the off- target modification comprises a changed epigenetic state at an off-target genomic site in the modified cell, wherein the changed epigenetic state is different from an initial epigenetic state of the off-target genomic site in the initial target cell. 57. The method of embodiment 56, wherein the first epigenetic map and the sixth epigenetic map are the same epigenetic map. 58. A method of screening a guide RNA for epigenetic editing, comprising: (a) introducing a CRISPR/Cas epigenetic effector and a first guide RNA to a first cell in an initial cellular state, wherein the first guide RNA is configured to bind to a first CRISPR/Cas domain in the CRISPR/Cas epigenetic effector and comprises a nucleic acid sequence complementary to a target genomic site, and wherein the CRISPR/Cas epigenetic effector introduces an on-target epigenetic edit to the target genomic site and an off-target epigenetic edit to an off-target genomic site and produces a modified cell; (b) profiling the modified cell using epigenetic profiling to generate a first epigenetic map of the modified cell; and (c) comparing the first epigenetic map and a second epigenetic map of a second cell that has not been modified by introduction of the first guide RNA to generate a differential; and (d) using the differential to identify the off-target genomic site. 59. A blocking guide RNA, comprising a nucleic acid sequence that is complementary to the off-target genomic site identified by the method of embodiment 58, wherein the blocking guide RNA is configured to bind to a second CRISPR/Cas domain, wherein the second CRISPR/Cas domain and the first CRISPR/Cas domain do not cross-react. 60. The method of embodiment 58, further comprising: (i) introducing a second guide RNA and a second CRISPR/Cas domain to an additional cell in the initial cellular state, wherein the second CRISPR/Cas domain forms a complex with the second guide RNA and binds to the off-target genomic site, thereby blocking the off-target genomic site from epigenetic editing; and (ii) introducing the CRISPR/Cas epigenetic effector to the additional cell, wherein the CRISPR/Cas epigenetic effector introduces an on-target epigenetic edit to the target genomic site; wherein the first CRISPR/Cas domain and the second CRISPR/Cas domain do not cross-react. 61. A method of identifying a target genomic site for epigenetic editing, comprising: (a) providing a target cellular epigenetic map of a target cell, wherein the target cellular epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the target cell; (b) providing an off-target cellular epigenetic map of an off-target cell, wherein the off- target cellular epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the off-target cell; (c) comparing the target cellular epigenetic map and the off-target cellular epigenetic map, thereby detecting a differential; and (d) using the differential to identify a target genomic site in the plurality of genomic sites, wherein (i) the target genomic site is a first epigenetic state in the target cell, and (ii) the target genomic site is in a second epigenetic state in the off-target cell, wherein the first epigenetic state and the second epigenetic state are different epigenetic states. 62. The method of embodiment 61, wherein the target cell is of a first cell type, and the off- target cell is of a second cell type, wherein the first cell type and the second cell type are different cell types. 63. The method of embodiment 61 or 62, wherein the target cell is from a target tissue and the off-target cell is from an off-target tissue, wherein the target tissue and the off-target tissue are different tissues. 64. The method of any one of embodiments 61-63, wherein the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an olfactory cell, an auditory cell, or a kidney cell. 65. The method of any one of embodiments 61-64, wherein the target cell is a liver hepatocyte. 66. The method of any one of embodiments 61-65, wherein the off-target cell is a pancreatic acinar cell or a gastric epithelial cell. 67. The method of any one of embodiments 61-66, further comprising generating the target cellular epigenetic map. 68. The method of any one of embodiments 61-67, further comprising generating the off- target cellular epigenetic map. 69. The method of any one of embodiments 61-68, comprising: (i) providing a plurality of off-target cellular epigenetic maps, wherein each off-target cellular epigenetic map of the plurality of off-target cellular epigenetic maps provides an epigenetic state of each genomic site of the plurality of genomic sites in a distinct off- target cell in a plurality of off-target cells; (ii) comparing the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps, thereby detecting a differential between the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps; and (iii) rising the differential to identify the target genomic site in the plurality of genomic sites, wherein the target genomic site is in the second epigenetic state in each off-target cell in tire plurality of off-target cells.

70. The method of embodiment 69, wherein the target cell is of a first cell type, and each off- target cell of the plurality of off-target cells is of a cell type that is different from the first cell type.

71. The method of embodiment 69 or 70, wherein the plurality of off-target cells comprises at least two off-target cells of different cell types.

72. The method of any one of embodiments 69-71, wherein the target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and the off-target tissues are different tissues.

73. Hie method of any one of embodiments 69-72, wherein the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g,, osteoblast, osteocyte, osteoclast, osteoprogenitor cell), or a brain cell (e.g., neuron, astrocyte, glial cell).

74. The method of any one of embodiments 69-73, wherein the target cell is a liver hepatocyte.

75. The method of any one of embodiments 69-74, wherein the plurality of off-target cells comprises a pancreatic acinar cell or a gastric epithelial cell.

76. Hie method of any one of embodiments 69-75, wherein the plurality of off-target cells composes a pancreatic acinar cell and a gastric epithelial cell.

77. The method of any one of embodiments 69-76, further comprising generating the plurality of off-target cellular epigenetic maps.

Partial reprogramming embodiments

78. A method of reprogramming a cell, comprising: selecting one or more off-target genomic sites; contacting the cell with a blocking reagent that specifically binds to the one or more selected off-target genomic sites; and contacting the cell with one or more epigenetic effectors that modify one or more epigenetic markers, wherein the blocking reagent inhibits modification of the selected one or more off-target genomic sites. 79. A method of reprogramming a cell, comprising: selecting one or more epigenetic cellular identity markers; contacting the cell with a blocking reagent that specifically binds to the one or more selected epigenetic cellular identity markers; and contacting the cell with one or more cellular reprogramming factors that modify one or more epigenetic markers, wherein the blocking reagent inhibits modification of the selected one or more epigenetic cellular identity markers. 80. The method of embodiment 79, wherein the one or more cellular reprogramming factors comprises one or more cellular reprogramming factors that target one or more target epigenetic markers. 81. The method of embodiment 79 or 80, wherein the one or more cellular reprogramming factors comprises one or more non-targeted cellular reprogramming factors. 82. The method of reprogramming a cell, comprising: selecting one or more epigenetic cellular identity markers; selecting one or more target sites, wherein the one or more selected targe sites excludes the one or more epigenetic cellular identity markers; and contacting the cell with one or more epigenetic effectors targeted to the one or more selected target sites. 83. The method of reprogramming a cell, comprising: selecting one or more epigenetic cellular identity markers; selecting one or more target epigenetic markers, wherein the one or more selected targe sites excludes the one or more epigenetic cellular identity markers; and contacting the cell with one or more cellular reprogramming factors targeted to the one or more selected target epigenetic markers. 84. The method of embodiment 78, wherein the one or more selected off-target genomic sites comprises a cellular identity marker. 85. The method of embodiment 78 or 84, wherein the one or more epigenetic effectors target one or more target sites. 86. The method of any one of embodiments 78, 84, or 85, wherein the one or more epigenetic effectors comprises one or more non-targeted cellular reprogramming factors. 87. The method of any one of embodiments 78-86, further comprising contacting the cell with a blocking reagent that specifically binds to the one or more selected epigenetic cellular identity markers, wherein the blocking reagent inhibits modification of the selected one or more epigenetic cellular identity markers. 88. The method of any one of embodiments 78-87, wherein the one or more epigenetic effectors that target the one or more target epigenetic markers comprises an epigenetic effector moiety or a moiety that recruits an epigenetic modification enzyme. 89. The method of any one of embodiments 78-88, wherein the one or more target epigenetic markers are associated with a biological age or a disease state. 90. The method of any one of embodiments 78-89, wherein the one or more epigenetic effectors that target the one or more target sites are targeted using a nuclease-deficient targeted DNA binding domain that is bound or fused to at least one of the one or more epigenetic effectors that target the one or more target sites. 91. The method of any one of embodiments 78-90, wherein the one or more cellular reprogramming factors that target the one or more target epigenetic markers are targeted using a nuclease-deficient targeted DNA binding domain that is bound or fused to at least one of the one or more cellular reprogramming factors that target the one or more target epigenetic markers. 92. The method of any one of embodiments 78-91 , wherein the one or more epigenetic effectors that target the one or more target sites are targeted using a CRISPR-based editing platform. 93. The method of any one of embodiments 78-92, wherein the one or more cellular reprogramming factors that target the one or more target sites are targeted using a CRISPR-based editing platform. 94. The method of embodiment 92 or 93, wherein the CRISPR-based editing platform comprises one or more single guide RNA (sgRNA) molecules that targets one or more target sites. 95. The method of any one of embodiments 92-94, wherein the CRISPR-based editing platform comprises a dead Cas9 endonuclease. 96. The method of embodiment 90 or 91, wherein the nuclease-deficient targeted DNA binding domain comprises an OMEGA domain, a Fanzor domain, a transcription activator-like (TAL) effector DNA-binding domain, a zinc finger nucleic acid binding moiety. 97. The method of any one of embodiments 78-96, wherein the cellular identity of the cell is maintained. 98. The method of any one of embodiments 78-97, wherein the cell is a fibroblast, a keratinocyte, a peripheral mononuclear blood cell, a hepatocyte, or an epithelial cell. 99. The method of any one of embodiments 78-98, wherein the cell is a neural cell, a blood cell, an immune cell, a hepatocyte, a lung cell, a pancreatic beta-cell, a cardiomyocyte, or an oligodendrocyte. 100. The method of any one of embodiments 78-99, wherein the one or more off-target genomic sites and/or the one or more target sites comprises one or more CpG sites and/or one or more histones. 101. The method of any one of embodiments 78-100, wherein the one or more off-target genomic sites and/or the one or more target epigenetic markers comprises one or more CpG sites and/or one or more histones. 102. The method of any one of embodiments 78-101, wherein the one or more target sites are modified by methylation, demethylation, acetylation, or deacetylation. 103. The method of any one of embodiments 78-102, wherein the one or more target epigenetic markers are modified by methylation, demethylation, acetylation, or deacetylation. 104. The method of any one of embodiments 78-103, wherein the one or more cellular reprogramming factors comprises KRAB, VPR, p65 VP64, HSF1, p300, DNMT3A, TET1, EZH2, G9a SUV39H1, HDAC3, LSD1, PRDM9, DOT1L, FOG1, BAF, PYL1, ABI1, CIBN, ADAR2, METTL3, METTL14, ALKBH5, or FTO, or an active fragment thereof. 105. The method of any one of embodiments 78-104, wherein the blocking reagent comprises a nuclease-deficient targeted DNA binding domain. 106. The method of any one of embodiments 78-105, wherein the blocking reagent comprises a nuclease-deficient targeted DNA binding domain that does not comprise an epigenetic effector moiety. 107. The method of any one of embodiments 78-106, wherein the blocking reagent is targeted using a CRISPR-based editing platform, and the CRISPR-based editing platform of the blocking reagent comprises one or more single guide RNA (sgRNA) molecules that targets one or more off-target genomic sites. 108. The method of any one of embodiment 78-107, wherein the CRISPR-based editing platform of the blocking reagent comprises a dead Cas9 endonuclease. 109. The method of embodiment 105 or 106, wherein the nuclease-deficient targeted DNA binding domain comprises an OMEGA domain, a Fanzor domain, a transcription activator-like (TAL) effector nucleic acid binding domain or a zinc finger nucleic acid binding domain. 110. The method of any one of embodiments 78-109, wherein the cell is simultaneously contacted with the blocking reagent and the one or more epigenetic effectors. 111. The method of any one of embodiments 78-109, wherein the cell is simultaneously contacted with the blocking reagent and the one or more reprogramming factors. 112. The method of any one of embodiments 78-109, wherein the method comprises contacting the cell with the blocking reagent prior to contacting the cell with the one or more epigenetic effectors. 113. The method of any one of embodiments 78-109, wherein the method comprises contacting the cell with the blocking reagent prior to contacting the cell with the one or more cellular reprogramming factors. 114. The method of any one of embodiments 78-113, further comprising culturing the cell after contacting the cell with the blocking reagent and/or the one or more epigenetic effectors. 115. The method of any one of embodiments 78-114, further comprising at least reversing cellular identity of the cell. 1 16. The method of any one of embodiments 81-115, wherein the one or more non-targeted cellular reprogramming factors comprises contacting the cell with one or more transcription factors.

117. The method of embodiment 116, wherein the one or more transcription factors comprises one or more Yamanaka factors.

1 18. The method of any one of any one of embodiments 81-117, wherein the one or more non-targeted cellular reprogramming factors comprises a high potassium medium.

119. The method of embodiment 115, wherein at least reversing cellular identity of the cell comprises generating an induced pluripotent step cell (iPSC) from the cell.

120. The method of any one of embodiments 78-120, wherein the cell is obtained from an individual ,

Epigenetic effector embodiments

121. An epigenetic effector from any of preceding embodiments.

122. The epigenetic effector of any of preceding embodiments, wherein the epigenetic modulator comprises:

(i) a first effector moiety; and

(ii) a nucleic acid binding moiety,

123. The epigenetic modulator of any of preceding embodiments, wherein the first effector moiety is selected from a DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMTl, MQEMETl, DRM2, CMT2, CMT3. TETl, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e, G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e, LSD1), KDM1B (i.e, LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KA' 11, KAT2A, KAT3A, KAT3B, or KAT13C, or a functional equivalent.

124. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety is capable of phosphorylation or ubiquitination.

125. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety is capable of DNA methylation.

126. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety is a DNA methyltransferase or a functional equivalent thereof. 127. The epigenetic modulator of any preceding embodiments, wherein the DNA methyltransferase may be selected from m6A methyltransferase, an m4C methyltransferase, and an m5C methyltransferase. 128. The epigenetic modulator of any preceding embodiments, wherein the DNA methyltransferase may be selected from DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1,MET1, DRM2, CMT2, CMT3, or a functional equivalent thereof. 129. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety is capable of DNA demethylation. 130. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety is selected from TET1, TET2, and TET3 or a functional equivalent thereof. 131. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety may be or comprise a transcription repressor moiety. 132. The epigenetic modulator of any preceding embodiments, wherein the first effector moiety is or may comprise a protein selected from KRAB, MeCP2, HP1, RBBP4, REST, FOG1, SUZ12, or a functional equivalent. 133. The epigenetic modulator of any preceding embodiments, further comprising a linker. 134. The linker of any preceding embodiments, wherein the linker is a non-cleavable linker. 135. The linker of any preceding embodiments, wherein the linker is a cleavable linker. 136. The linker of any preceding embodiments, wherein the linker is a peptide linker. 137. The epigenetic modulator of any preceding embodiments, wherein the epigenetic modulator does not comprise a linker. 138. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety is fused to the effector moiety. 139. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety is located 5’ of the effector moiety. 140. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety is located 3’ of the effector moiety. 141. The epigenetic modulator of any preceding embodiments, wherein the 3’ end of nucleic acid binding moiety is connected to the 5’ end of the effector moiety. 142. The epigenetic modulator of any preceding embodiments, wherein the 5’ end of nucleic acid binding moiety is connected to the 3’ end of the effector moiety. 143. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety comprises a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a zinc finger domain, a TAL domain, a tetR domain, a meganuclease, or an oligonucleotide. 144. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety comprises a CRISPR/Cas domain. 145. The epigenetic modulator of any of preceding embodiments, wherein the CRISPR/Cas domain may comprise a CRISPR/Cas protein. 146. The epigenetic modulator of any of preceding embodiments, wherein the CRISPR/Cas protein may be selected from a type I, type II, type III, type IV, type V Cas protein, and type VI Cas protein. 147. The epigenetic modulator of any of preceding embodiments, wherein the CRISPR/Cas protein may be catalytically inactive. 148. The epigenetic modulator of any of preceding embodiments, wherein the CRISPR/Cas protein may be selected from Cas1, Cas1B, Cas2, Cas3, Cas4, Cas5, Cas5d, Cas5t, Cas5h, Cas5a, Cas6, Cas7, Cas8, Cas8a, Cas8b, Cas8c, Cas9, Cas10, Cas10d, Cas12a/Cpf1, Cas12b/C2c1, Cas12c/C2c3, Cas12d/CasY, Cas12e/CasX, Cas12g, Cas12h, Cas12i, Csy1 , Csy2, Csy3, Csy4, Cse1, Cse2, Cse3, Cse4, Cse5e, Csc1, Csc2, Csa5, Csn1, Csn2, Csm1, Csm2, Csm3, Csm4, Csm5, Csm6, Cmr1, Cmr3, Cmr4, Cmr5, Cmr6, Csb1, Csb2, Csb3, Csx17, Csx14, Csx10, Csx16, CsaX, Csx3, Csx1, Csx1S, Csx11, Csf1, Csf2, CsO, Csf4, Csd1, Csd2, Cst1, Cst2, Csh1, Csh2, Csa1, Csa2, Csa3, Csa4, Csa5, AsCas12a, Cas13a, Cas13b, Cas13c, Cas13d, Cas13X, Cas13Y, LbCas12a, HypaCas9, a Type I Cas effector protein, a Type II Cas effector protein, a Type III Cas effector protein, a Type IV Cas effector protein, a Type V Cas effector protein, a Type VI Cas effector protein, CARF, DinG, Cpf1, Cas12b/C2c1, Cas12c/C2c3, Cas12b/C2c1, Cas ^, and functional fragments and derivatives thereof. 149. The epigenetic modulator of any preceding embodiments, wherein the CRISPR/Cas protein may be or comprise a Cas9 ortholog. 150. The epigenetic modulator of any preceding embodiments, wherein the Cas9 ortholog may be selected from SpCas9, SaCas9, ScCas9, StCas9, NmCas9, VRERCas9, VERCas9, xCas9, espCas91.0, espCas1.1, Cas9HF1, hypaCas9, evoCas9, HiFiCas9, and CjCas9. 151. The epigenetic modulator of any preceding embodiments, wherein the Cas9 is a Cas9 nuclease. 152. The epigenetic modulator of any preceding embodiments, wherein the CRISPR/Cas protein may be or comprise a Cas12 ortholog. 153. The epigenetic modulator of any preceding embodiments, wherein the Cas12 ortholog may be selected from Cpf1, FnCas12a, LbCas12a, AsCas12a, LbCas12a, TsCas12a, SaCas12a, Pb2Cas12a, PgCas12a, MiCas12a, Mb2Cas12a, Mb3Cas12a, Lb4Cas12a, Lb5Cas12a, FbCas12a, CrbCas12a, CpbCas12a, CMaCas12a, BsCas12a, BfCas12a, BoCas12a, Cas12j, or Cas12c. 154. The epigenetic modulator of any preceding embodiments, wherein the CRISPR/Cas protein may be derived from a bacteria or has one or more components derived from a bacteria, and wherein the one or more components may optionally be derived from different bacteria. 155. The epigenetic modulator of any preceding embodiments, wherein the bacteria origin of the CRISPR/Cas protein of the epigenetic modulator may be selected from Streptococcus pyogenes, Streptococcus thermophilus, Streptococcus sp., Staphylococcus aureus, Nocardiopsis dassonvillei, Streptomyces pristinae spiralis, Streptomyces viridochromo genes, Streptomyces viridochromogenes, Streptosporangium roseum, Streptosporangium roseum, AlicyclobacHlus acidocaldarius, Bacillus pseudomycoides, Bacillus selenitireducens, Bacillus niameyensis, Bacillus okhensis, Capnocytophaga canis, Chryseobacterium gallinarum, Coriobacterium_glomerans_PW2, Dechloromonas denitrificans, Enterococcus cecorum, Enterococcus faecium, Enterococcus italicus, Eubacterium dolichum, Eubacterium sp., Eggerthella sp. YY7918, Exiguobacterium sibiricum, Flavobacterium frigidarium, Facklamia hominis, Finegoldia_magna_ATCC_29328, Kingella kingae, Lactobacillus_rhamnosus_LOCK900, Lactobacillus delbrueckii, Lactobacillus salivarius, Lactobacillus sp., Microscilla marina, Mycoplasma_gallisepticum_CA06, Neisseria meningitidis, Ornithobacterium rhinotracheale, Burkholderiales bacterium, Polaromonas naphthalenivorans, Polaromonas sp., Pediococcus acidilactici, Prevotella histicola, Parabacteroides sp., Streptococcus_agalactiae_NEM316, Streptococcus_dysgalactiae_subsp._equisimilis_AC-2713, Streptococcus equinus, Streptococcus gallolyticus, Streptococcus gordonii, Streptococcus mutans GS-5, Streptococcus macedonicus, Streptococcus ratti, Streptococcus_salivarius_JIM8777, Streptococcus sinensis, Streptococcus suis D9, Streptococcus thermophilus LMG 18311, Tissierellia bacterium KA00581, Treponema denticola ATCC 35405, Treponema putidum, Turicibacter sp., Veillonella parvula ATCC 17745, Weeksella virosa, Streptococcus equi, Streptococcus agalactiae, Lactobacillus animalis KCTC 3501, Listeria monocytogenes, Lachnospiraceae bacterium ND2006, Acidaminococcus sp. BV3L6, Helcococcus kunzii, Prevotella ihumii, Prevotella bryantii B14, Biggievirus strain Mos11, Compost_meta_-_Ga0079224_100045232_-_CRISPR- associated_protein,_Csn1_family_CDS_translation_Compost_meta, Geyser- Hotspring_Yellowstone_Ga0078972_1022257_-_CRISPR- associated_protein,_Csn1_family_CDS_translation_Community_metagenome, Geyser- Hotspring_Yellowstone_Ga0078972_1010018_-_CRISPR- associated_protein,_Csn1_family_CDS_translation_Community_metagenome, Crocosphaera watsonii, Cyanothece sp., Microcystis aeruginosa, Pseudomonas aeruginosa, Synechococcus sp., Acetohalobium arabaticum, Ammonifex degensii, Caldicelulosiruptor becscii, Candidatus Desulforudis, Clostridium botulinum, Clostridium difficile, Clostridium Tyrobutyricum, Clostridium beijerinckii, Clostridium perfringens, Clostridium autoethanogenum, Finegoldia magna, Natranaerobius thermophilus, Methanococcus maripaludis, Pelotomaculum thermopropionicum, Acidithiobacillus caldus, Lactobacillus crispatus, Acidithiobacillus ferrooxidans, Acidaminococcus intestine RyC-MR95, Allochromatium vinosum, Marinobacter sp., Nitrosococcus halophilus, Nitrosococcus watsoni, Pseudoalteromonas haloplanktis, Ktedonobacter racemifer, Methanohalobium evestigatum, Streptococcus thermophilus, Lactococcus lactis, Staphylococcus epidermidis Anabaena variabilis, Nodularia spumigena, Nostoc sp., Arthrospira maxima, Arthrospira platensis, Arthrospira sp., Lyngbya sp., Microcoleus chthonoplastes, Oscillatoria sp., Petrotoga mobilis, Thermosipho africanus, Clostridium acetobutylicum , Synechococcus elongatus UTEX 2973, Actinoplanes sp., B. subtilis, Corynebacterium glutamicum, Streptomyces sp., Clostridium difficile, Clostridium saccharoperbutylacetonicum N1–4, Acaryochloris marina, Leptotrichia shahii, and Francisella novicida. 156. The epigenetic modulator of any preceding embodiments, wherein the CRISPR/Cas protein may be derived from a virus or has one or more components derived from a virus, and wherein the one or more components may optionally be derived from different virus. 57. Tiie epigenetic modulator of any preceding embodiments, wherein the viral origin of the CRISPR/Cas protein of each of the epigenetic effectors may be selected from bacteriophage s . 58. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety of the epigenetic modulator may comprise a zinc finger domain. 59. The epigenetic modulator of any preceding embodiments, wherein the zinc finger domain may comprise or consist essentially of or consist of 1-10, 1-9, 1-8, 1-7, 1-6, 1-5, 1-4, 1-3, 1-2, 2-10, 2-9, 2-8, 2-7, 2-6, 2-5, 2-4, 2-3, 3-10, 3-9, 3-8, 3-7, 3-6, 3-5, 3-4, 4- 10, 4-9, 4-8, 4-7, 4-6, 4-5, 5-10, 5-9, 5-8, 5-7, 5-6, 6-10, 6-9, 6-8, 6-7, 7-10, 7-9, 7-8, 8- 10, 8-9, or 9-10 zinc fingers. 60. The epigenetic modulator of any preceding embodiments, wherein the nucleic acid binding moiety of the epigenetic modulator may comprise a TAT, domain. 61 . The epigenetic modulator of any preceding embodiments, wherein the TAL domain comprises at least 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, or 40 central repeats. 62. The epigenetic modulator of any preceding embodiments, wherein the effector moiety may be a durable effector moiety. 63. The epigenetic modulator of any preceding embodiments, wherein the effector moiety may be a transient effector moiety. 64. The epigenetic modulator of any preceding embodiments, wherein toe effector moiety may be capable of effecting methylation profile of a DNA or histone. 65. The epigenetic modulator of any preceding embodimen ts, wherein the effector moiety may be capable of increasing or decreasing a target gene expression. 66. The epigenetic modulator of any preceding embodiments, wherein the effector moiety may be capable of increasing or decreasing a second gene expression that is not the target j2,snc. 67. The epigenetic modulator of any preceding embodimen ts, wherein the target gene and the second gene interact in a genetic pathway. 68. The epigenetic modulator of any preceding embodiments, wherein the target gene is located upstream of the second gene in the genetic pathway. 169. The epigenetic modulator of any preceding embodiments, wherein the epigenetic modulator comprises a second effector moiety. 170. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety selected from DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1,MET1, DRM2, CMT2, CMT3, TET1, TET2, and TET3 , SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e., LSD1), KDM1B (i.e., LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1, KAT2A, KAT3A, KAT3B, KAT13C , HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6, HDAC7, HDAC8, HDAC9, HDAC10, HDAC11, SIRT1, SIRT2, SIRT3, SIRT4, SIRT5, SIRT6, SIRT7, SIRT8, SIRT9, KRAB, MeCP2, HP1, RBBP4, REST, FOG1, SUZ12, or a functional equivalent thereof. 171. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety is capable of DNA methylation. 172. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety is a DNA methyltransferase or a functional equivalent thereof. 173. The epigenetic modulator of any preceding embodiments, wherein the DNA methyltransferase may be selected from m6A methyltransferase, an m4C methyltransferase, and an m5C methyltransferase. 174. The epigenetic modulator of any preceding embodiments, wherein the DNA methyltransferase may be selected from DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1,MET1, DRM2, CMT2, CMT3, or a functional equivalent thereof. 175. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety is capable of DNA demethylation. 176. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety is selected from TET1, TET2, and TET3, or a functional equivalent thereof. 177. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety may be or comprise a transcription repressor moiety. 178. The epigenetic modulator of any preceding embodiments, wherein the second effector moiety is or may comprise a protein selected from KRAB, MeCP2, HP1, RBBP4, REST, FOG1, SUZ12, or a functional equivalent. 179. The epigenetic modulator of any preceding embodiments, wherein the first and the second effector moiety are identical. 180. The epigenetic modulator of any preceding embodiments, wherein the first and the second effector moiety are not identical. 181. The epigenetic modulator of any preceding embodiments, further comprising a second linker. 182. The second linker of any preceding embodiments, wherein the second linker is a non- cleavable linker. 183. The second linker of any preceding embodiments, wherein the second linker is a cleavable linker. 184. The second linker of any preceding embodiments, wherein the second linker is a peptide linker. 185. The epigenetic modulator of any preceding embodiments, wherein the first linker is situated between the first effector moiety and the nucleic acid binding moiety, and the second linker is situated between the nucleic acid binding moiety and the second effector moiety. 186. The epigenetic modulator of any preceding embodiments, further comprising one or more nuclear localization signal (NLS). 187. The epigenetic modulator of any preceding embodiments, wherein the NLS is selected from SV40, EGL-13, Tus-protein, polyoma large T-AG, Hepatitis D virus antigen, Rev protein, murine p53, or a nucleoplasmin. 188. A polynucleotide comprising a sequence encoding an epigenetic modulator of any preceding embodiments. 189. The polynucleotide of any preceding embodiments, wherein the polynucleotide is a RNA, e.g., an mRNA. 190. The epigenetic modulator of any preceding embodiments, further comprising a guide RNA. 191. The method of any preceding embodiments, wherein a guide RNA is complexed with the epigenetic modulator, wherein the guide RNA targets the epigenetic modulator to each genomic site of the plurality of target genomic sites in the target cell. 192. The plurality of target genomic sites of any preceding embodiments, wherein the plurality of target genomic sites is a DNA sequence segment. 193. The plurality of target genomic sites of any preceding embodiments, wherein the plurality of target genomic sites is an RNA sequence segment, e.g., a mRNA sequence segment. 194. The plurality of target genomic sites of any preceding embodiments, wherein the mRNA may be expressed from the genome of an organism. 195. The plurality of target genomic sites of any preceding embodiments, wherein the organism may be a prokaryote, e.g., a bacterium. 196. The plurality of target genomic sites of any preceding embodiments, wherein the organism may be a eukaryote. 197. The plurality of target genomic sites of any preceding embodiments, wherein the eukaryote may be a vertebrate. 198. The plurality of target genomic sites of any preceding embodiments, wherein the vertebrate may be a mammal. 199. The plurality of target genomic sites of any preceding embodiments, wherein the mammal may be a non-human mammal, e.g., a mouse, a primate. 200. The plurality of target genomic sites of any preceding embodiments, wherein the mammal may be a human. 201. The plurality of target genomic sites of any preceding embodiments, wherein the plurality of target genomic sites is located in a target cell. 202. The plurality of target genomic sites of any preceding embodiments, wherein the target cell is selected from a fibroblast cell, a liver cell, a cardiac cell, a CNS cell, a PNS cell, a kidney cell, a lung cell, a hematopoietic cell, a pancreatic beta cell, a bone cell, a skeletal muscle cell, a skin cell, an immune cell, a follicular cell, a vascular cell, a neural cell, an osteoblast cell, an osteoclast cell, and an endothelial cell. 203. The plurality of target genomic sites of any preceding embodiments, wherein the target cell is a liver hepatocyte. 204. The plurality of target genomic sites of any preceding embodiments, wherein the target cell is an immune cell, e.g., a T cell. 205. The plurality of target genomic sites of any preceding embodiments, wherein the T cell is CD4+ T cell. 206. The plurality of target genomic sites of any preceding embodiments, wherein the T cell is CD8+ T cell. 207. The plurality of target genomic sites of any preceding embodiments, wherein the target gene is a transcription factor. 208. The plurality of target genomic sites of any preceding embodiments, wherein the transcription factor is selected from AP-1, bHLEH40, RUNX1, FOXN3, ELK1, HIC1, SP1, NF-kB, BATF, JUNE, IRF4, NFAT, STAT5, STAT3, Fra, Fos, ATF, RUNX2, bHLEH41, CLOCK, BMAL, NPASS, Max,ELK, Fli, Eomes, GATA1, Prop1, ZNF189, ROR, ZNF415, RUNT, T-Bet, MADs, HOX, and ZNF317.2a5. 209. The plurality of target genomic sites of any preceding embodiments, wherein the plurality of target genomic sites may be associated with a germline gene, e.g., a misregulated germline gene, e.g., a misregulated germline gene associated with a developmental defect or disorder. 210. The plurality of target genomic sites of any preceding embodiments, wherein the target cell expresses CD151. 211. The plurality of target genomic sites of any preceding embodiments, wherein the plurality of target genomic sites may be associated with a disease or a disorder. 212. The plurality of target genomic sites of any preceding embodiments, wherein the disease is selected from a cancer, an immune or autoimmune disorder, a pulmonary disorder, a neurodegenerative disorder, a cardiovascular disorder, a fibrotic disorder, an eye or skin disorder, an osteoarthritic disorder, a kidney disorder, or a metabolic disorder. 213. The plurality of target genomic sites of any preceding embodiments, wherein the plurality of target genomic sites may be associated with a genetic pathway involved in cellular regeneration. 214. A system comprising: (a) a computer system programmed to: (b) analyze a methylation state of each genomic site of a plurality of genomic sites located in the target cell; and

(c) select a plurality of target genomic sites located in the target ceil for contacting with an epigenetic effector to change the methylation state of each genomic site of a plurality of target genomic sites located in die target cell.

Claims

CLAIMS 1. A method of identifying a target genomic site for epigenetic editing, comprising: (a) providing a first epigenetic map of a target cell in an initial cellular state, wherein the first epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the target cell; (b) providing a second epigenetic map of a desired cell in a desired cellular state, wherein the second epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the desired cell; (c) comparing the first epigenetic map and the second epigenetic map, thereby detecting a first differential; and (d) identifying a target genomic site in the plurality of genomic sites using the first differential, wherein (i) the target genomic site is in an initial epigenetic state in the target cell, and (ii) the target genomic site is in a desired epigenetic state in the desired cell, wherein the initial epigenetic state and the desired epigenetic state are different epigenetic states.

2. The method of claim 1, wherein the first epigenetic map and the second epigenetic map provide a methylation state.

3. The method of claim 1, wherein the first epigenetic map and the second epigenetic map provide a 5’ hydroxymethylation state, a chromatin accessibility state, or a histone modification state.

4. The method of claim 1, wherein the initial epigenetic state is an unmethylated state and the desired epigenetic state is a methylated state.

5. The method of claim 1, wherein the initial epigenetic state is a methylated state, and the desired epigenetic state is an unmethylated state.

6. The method of claim 1, wherein the initial epigenetic state is an acetylated state, and the desired epigenetic state is an unacetylated state.

7. The method of claim 1, wherein the initial epigenetic state is an unacetylated state and the desired epigenetic state is an acetylated state.

8. The method of any one of claims 1-7, wherein the initial cellular state is a diseased state, and the desired cellular state is a healthier state relative to the initial cellular state.

9. The method of any one of claims 1-7, wherein the initial cellular state is an exhausted state, and the desired cellular state is a rejuvenated state relative to the initial cellular state.

10. The method of any one of claims 1-7, wherein the desired cellular state is a younger state relative to the initial cellular state.

11. The method of any one of claims 1-7, wherein the desired cellular state is a less differentiated state relative to the initial cellular state.

12. The method of any one of claims 1-7, wherein the desired cellular state comprises a higher level of stemness relative to the desired cellular state.

13. The method of any one of claims 1-12, wherein the desired cell in the desired cellular state comprises a desired cellular functional state.

14. The method of any one of claims 1-13, wherein a cell in the desired cellular state comprises a desired phenotype.

15. The method of any one of claims 1-14, wherein the plurality of genomic sites comprises a whole genome of the target cell.

16. The method of any one of claims 1-15, further comprising generating the first epigenetic map.

17. The method of any one of claims 1-16, further comprising generating the second epigenetic map.

18. The method of any one of claims 1-17, further comprising: providing a third epigenetic map of an off-target cell, wherein the third epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the off-target cell; and wherein (d) further comprises detecting an epigenetic state of the target genomic site in the off-target cell, wherein the epigenetic state of the target genomic site in the off-target cell and the desired epigenetic state are the same epigenetic state.

19. The method of claim 18, further comprising comparing the third epigenetic map with a fourth epigenetic map of a cell in the initial cellular state, thereby detecting a second differential and using the second differential to identify the target genomic site in the plurality of genomic sites.

20. The method of claim 18 or 19, wherein the target cell is of a first cell type, and the off- target cell is of a second cell type, wherein the first cell type and the second cell type are of different cell types.

21. The method of any one of claims 18-20, wherein the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the off-target cell is produced by modifying an initial cell of the first cell type using a drug.

22. The method of claim 21, wherein the drug is capable of epigenetic editing.

23. The method of claim 21 or 22, wherein the drug is a small molecule inhibitor.

24. The method of claim 23 wherein the small molecule inhibitor is selected from rapamycin, a GSK-3 beta inhibitor, or a hypomethylation agent.

25. The method of claim 21 or 22, wherein the drug is fusion polypeptide or a nucleic acid encoding the fusion polypeptide.

26. The method of claim 25, wherein the fusion polypeptide comprises a nucleic acid binding moiety.

27. The method of claim 26, wherein the nucleic acid binding moiety comprises a CRISPR/Cas domain, an OMEGA domain, a Fanzor domain, a zinc finger domain, a TAL domain, a tetR domain, a meganuclease, or an oligonucleotide.

28. The method of any one of claims 25-27, wherein the fusion polypeptide comprises an effector moiety.

29. The method of claim 28, wherein the effector moiety comprises a DNMT1, DNMT3A1, DNMT3A2, DNMT3B1, DNMT3B2, DNMT3B3, DNMT3B4, DNMT3B5, DNMT3B6, DNMT3L, TRDMT1, MQ1,MET1, DRM2, CMT2, CMT3, TET1, TET2, TET3, SETDB1, SETDB2, EHMT2 (i.e., G9A), EHMT1 (i.e., GLP), SUV39H1, EZH2, EZH1, SUV39H2, SETD8, SUV420H1, SUV420H2, KDM1A (i.e., LSD1), KDM1B (i.e., LSD2), KDM2A, KDM2B, KDM5A, KDM5B, KDM5C, KDM5D, KDM4B, NO66, KAT1, KAT2A, KAT3A, KAT3B, or KAT13C, or a functional equivalent.

30. The method of any one of claims 18-29, wherein the target cell is from a target tissue and the off-target cell is from an off-target tissue, wherein the target tissue and the off-target tissue are different tissues.

31. The method of any one of claims 1-30, wherein the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an olfactory cell, an auditory cell, or a kidney cell.

32. The method of claim 31, wherein the target cell is a liver hepatocyte.

33. The method of any one of claims 18-32, wherein the off-target cell is a pancreatic acinar cell or a gastric epithelial cell.

34. The method of any one of claims 18-33, further comprising generating the third epigenetic map.

35. The method of any one of claims 19-34, further comprising generating the fourth epigenetic map.

36. The method of any one of claims 1-35, further comprising: providing an initial epigenetic map of a target cell in the initial cellular state, wherein the initial epigenetic map provides an epigenetic state of each genomic site of the plurality of genomic sites in the target cell; providing a plurality of epigenetic maps of a plurality of off-target cells, wherein the plurality of epigenetic maps provides an epigenetic state of each genomic site of the plurality of genomic sites in each off-target cell in the plurality of off-target cells; and comparing the initial epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells, thereby detecting a third differential between the initial epigenetic map and the plurality of epigenetic maps of the plurality of off-target cells; wherein (d) further comprises using the third differential to identify the target genomic site in the plurality of genomic sites, wherein the target genomic site is in the desired epigenetic state in each off-target cell in the plurality of off-target cells.

37. The method of claim 36 wherein the first epigenetic map and the initial epigenetic map are the same epigenetic map.

38. The method of claim 36 or 37, wherein the target cell is of a first cell type, and each off- target cell of the plurality of off-target cells is of a cell type that is different from the first cell type.

39. The method of any one of claims 36-38, wherein the plurality of off-target cells comprises at least two off-target cells of different cell types.

40. The method of any one of claims 36-39, wherein the target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and the off-target tissues are different tissues.

41. The method of any one of claims 36-40, wherein the target cell is a liver hepatocyte.

42. The method of any one of claims 36-41, wherein the plurality of off-target cells comprises a pancreatic acinar cell or a gastric epithelial cell.

43. The method of any one of claims 36-42, wherein the plurality of off-target cells comprises a pancreatic acinar cell and a gastric epithelial cell.

44. The method of any one of claims 36-43, further comprising generating the plurality of epigenetic maps of the plurality of off-target cells.

45. The method of modifying a target cell, comprising: (a) identifying a target genomic site for epigenetic editing according to the method of any one of claims 1-44, (b) providing a target cell in the initial cellular state, wherein the provided target cell comprises the target genomic site in the initial epigenetic state; and (c) contacting the provided target cell with an epigenetic effector, wherein the epigenetic effector modifies the target genomic site from the initial epigenetic state to the desired epigenetic state, thereby producing a modified cell, wherein the modified cell is in a modified cellular state.

46. The method of claim 45, wherein the modified cellular state is functionally more similar to the desired cellular state than the initial cellular state is to the desired cellular state.

47. The method of claim 45 or 46, further comprising profiling a function of the modified cell.

48. The method of any one of claims 45-47, wherein the modified cell exhibits a modified phenotype that is different from an initial phenotype of the target cell.

49. The method of claims 45-48, where the modified phenotype is more similar to a desired phenotype of the desired cell in the desired cellular state than the initial phenotype is to the desired phenotype.

50. The method of any one of claims 45-49, further comprising profiling a phenotype of the modified cell.

51. The method of any one of claims 45-50, wherein modifying the target genomic site from the initial epigenetic state to the desired epigenetic state turns on expression of a gene.

52. The method of any one of claims 45-51, wherein modifying the target genomic site from the initial epigenetic state to the desired epigenetic state turns off expression of a gene.

53. The method of any one of claims 45-52, wherein the epigenetic effector comprises: (i) an effector moiety; (ii) a first CRISPR/Cas domain; and (ii) a guide RNA complexed with the first CRISPR/Cas domain, wherein the guide RNA targets the epigenetic effector to the target genomic site.

54. A method of screening a guide RNA for epigenetic editing, comprising: (a) modifying an initial target cell according to the method of any one of claims 45-53, thereby producing a modified cell; (b) generating a fifth epigenetic map of the modified cell, wherein the fifth epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the modified cell; (c) comparing the fifth epigenetic map with a sixth epigenetic map, wherein the sixth epigenetic map is generated from a cell that is not treated with the epigenetic effector, thereby generating a fourth differential; (d) using the fourth differential to detect an off-target modification, wherein the off- target modification comprises a changed epigenetic state at an off-target genomic site in the modified cell, wherein the changed epigenetic state is different from an initial epigenetic state of the off-target genomic site in the initial target cell.

55. The method of claim 54, wherein the first epigenetic map and the sixth epigenetic map are the same epigenetic map.

56. A method of screening a guide RNA for epigenetic editing, comprising: (a) introducing a CRISPR/Cas epigenetic effector and a first guide RNA to a first cell in an initial cellular state, wherein the first guide RNA is configured to bind to a first CRISPR/Cas domain in the CRISPR/Cas epigenetic effector and comprises a nucleic acid sequence complementary to a target genomic site, and wherein the CRISPR/Cas epigenetic effector introduces an on-target epigenetic edit to the target genomic site and an off-target epigenetic edit to an off-target genomic site and produces a modified cell; (b) profiling the modified cell using epigenetic profiling to generate a first epigenetic map of the modified cell; and (c) comparing the first epigenetic map and a second epigenetic map of a second cell that has not been modified by introduction of the first guide RNA to generate a differential; and (d) using the differential to identify the off-target genomic site.

57. The method of claim 56, further comprising: (i) introducing a second guide RNA and a second CRISPR/Cas domain to an additional cell in the initial cellular state, wherein the second CRISPR/Cas domain forms a complex with the second guide RNA and binds to the off-target genomic site, thereby blocking the off-target genomic site from epigenetic editing; and (ii) introducing the CRISPR/Cas epigenetic effector to the additional cell, wherein the CRISPR/Cas epigenetic effector introduces an on-target epigenetic edit to the target genomic site; wherein the first CRISPR/Cas domain and the second CRISPR/Cas domain do not cross-react.

58. A method of identifying a target genomic site for epigenetic editing, comprising: (a) providing a target cellular epigenetic map of a target cell, wherein the target cellular epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the target cell; (b) providing an off-target cellular epigenetic map of an off-target cell, wherein the off- target cellular epigenetic map provides an epigenetic state of each genomic site of a plurality of genomic sites in the off-target cell; (c) comparing the target cellular epigenetic map and the off-target cellular epigenetic map, thereby detecting a differential; and (d) using the differential to identify a target genomic site in the plurality of genomic sites, wherein (i) the target genomic site is a first epigenetic state in the target cell, and (ii) the target genomic site is in a second epigenetic state in the off-target cell, wherein the first epigenetic state and the second epigenetic state are different epigenetic states.

59. The method of claim 58, wherein the target cell is of a first cell type, and the off-target cell is of a second cell type, wherein the first cell type and the second cell type are different cell types.

60. The method of claim 58 or 59, wherein the target cell is from a target tissue and the off- target cell is from an off-target tissue, wherein the target tissue and the off-target tissue are different tissues.

61. The method of any one of claims 58-60, wherein the target cell is a liver hepatocyte.

62. The method of any one of claims 58-61, wherein the off-target cell is a pancreatic acinar cell or a gastric epithelial cell.

63. The method of any one of claims 58-62, further comprising generating the target cellular epigenetic map.

64. The method of any one of claims 58-63, further comprising generating the off-target cellular epigenetic map.

65. The method of any one of claims 58-64, further comprising: (i) providing a plurality of off-target cellular epigenetic maps, wherein each off-target cellular epigenetic map of the plurality of off-target cellular epigenetic maps provides an epigenetic state of each genomic site of the plurality of genomic sites in a distinct off- target cell in a plurality of off-target cells; (ii) comparing the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps, thereby detecting a differential between the target cellular epigenetic map and the plurality of off-target cellular epigenetic maps; and (iii) using the differential to identify the target genomic site in the plurality of genomic sites, wherein the target genomic site is in the second epigenetic state in each off-target cell in the plurality of off-target cells.

66. The method of claim 65, wherein the target cell is of a first cell type, and each off-target cell of the plurality of off-target cells is of a cell type that is different from the first cell type.

67. The method of claim 65 or 66, wherein the plurality of off-target cells comprises at least two off-target cells of different cell types.

68. The method of any one of claims 65-67, wherein the target cell is from a target tissue and the plurality of off-target cells is from off-target tissues, wherein the target tissue and the off-target tissues are different tissues.

69. The method of any one of claims 65-68, wherein the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell (e.g., osteoblast, osteocyte, osteoclast, osteoprogenitor cell), a brain cell (e.g., neuron, astrocyte, glial cell), an optic cell, an olfactory cell, an auditory cell, or a kidney cell.

70. The method of any one of claims 65-69, wherein the target cell is selected from a bone cell, a blood cell, a muscle cell, a liver cell, a skin cell, an immune cell, a pancreatic cell, a nerve cell, a gastric cell, a cardiac cell, a gonad cell, or a fat cell, a bone cell, or a brain cell.

71. The method of any one of claims 65-70, wherein the target cell is a liver hepatocyte.

72. The method of any one of claims 65-71, wherein the plurality of off-target cells comprises a pancreatic acinar cell or a gastric epithelial cell.

73. The method of any one of claims 65-72, wherein the plurality of off-target cells comprises a pancreatic acinar cell and a gastric epithelial cell.

74. The method of any one of claims 65-73, further comprising generating the plurality of off-target cellular epigenetic maps.