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WO2025222124A1 - Profilage transcriptionnel à haute résolution spatiale par séquençage indexé - Google Patents

Profilage transcriptionnel à haute résolution spatiale par séquençage indexé

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Publication number
WO2025222124A1
WO2025222124A1 PCT/US2025/025375 US2025025375W WO2025222124A1 WO 2025222124 A1 WO2025222124 A1 WO 2025222124A1 US 2025025375 W US2025025375 W US 2025025375W WO 2025222124 A1 WO2025222124 A1 WO 2025222124A1
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beads
bead
young
receiver
cell
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Junyue CAO
Wei Zhou
Abdulraouf ABDULRAOUF
Weirong JIANG
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Rockefeller University
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Rockefeller University
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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
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    • C12Q1/6809—Methods for determination or identification of nucleic acids involving differential detection
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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
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    • C12Q1/6813—Hybridisation assays
    • C12Q1/6834—Enzymatic or biochemical coupling of nucleic acids to a solid phase
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    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6869—Methods for sequencing
    • C12Q1/6874—Methods for sequencing involving nucleic acid arrays, e.g. sequencing by hybridisation
    • G—PHYSICS
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/58—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving labelled substances

Definitions

  • oligonucleotide capture arrays face limitations in their throughput and the ability to cover extensive areas: prior indexing methods (e.g., 10X Genomics Visium (St ⁇ hl et al., 2016, Science 353, 78–82), DBiT-seq (Liu et al., 2020, Cell 183, 1665–1681.e18)), use predefined DNA barcodes at specific positions, whereas posterior indexing methods, such as slide-seq (Rodriques et al., 2019, Science 363, 1463–1467; Stickels et al., 2021, Nat. Biotechnol.39, 313– 319), HDST (Vickovic et al., 2019, Nat.
  • the invention addresses this unmet need in the art.
  • a sender bead comprising an acrylamide-based gel bead with a plurality of attached oligonucleotides wherein each attached oligonucleotide comprises: a) a photocleavable linker; b) a primer sequence; c) a barcode sequence; d) a unique molecular identifier sequence; and e) a capture sequence for binding to a receiver bead.
  • the invention relates to a receiver bead comprising an acrylamide-based gel bead with a plurality of attached oligonucleotides wherein each attached oligonucleotide comprises: a) a primer sequence; b) a barcode sequence; c) a unique molecular identifier sequence; and d) a capture sequence for binding to i) a target molecule of interest; ii) an oligonucleotide released upon photocleavage of the photocleavable linker from the sender bead, or iii) a combination of i) and ii).
  • the invention relates to an assay system for generating a spatial map of one or more target molecule across a sample comprising a combination of sender beads and receiver beads. [0011] In some embodiments, the assay generates a transcriptional map of mRNA molecules across the sample. [0012] In some embodiments, the capture sequence of the sender bead comprises a poly- A region, and the capture sequence of the receiver bead comprises a poly-T region. [0013] In some embodiments, the invention relates to a method, comprising: 3
  • the method further comprises a step of permeabilizing the tissue sample prior to applying the tissue sample to the slide or surface containing the sender and receiver beads. [0015] In some embodiments, the method further comprises a step of taking an image of the tissue sample.
  • the method further comprises the steps: i) generating a sequencing library from the oligonucleotides attached to the recovered receiver beads; j) sequencing the sequencing library to produce barcoded DNA reads; k) generating a matrix of bead connections based on the UMI sequences and barcodes of the sender beads and receiver beads; l) generating a spatial map of the target molecules using the barcodes on the sequencing reads of the target molecules and the matrix of bead connections. [0017] In some embodiments, the method further comprises identifying the anatomical location of the target molecules by correlating the spatial map to the sample image. BRIEF DESCRIPTION OF THE DRAWINGS 4
  • Figure 1A and Figure 1B depict an overview of IRIS methodology.
  • Figure 1A depicts the experimental scheme and illustrates how IRIS utilizes barcoded gel beads (receiving beads) to capture nearby mRNA expression. Each receiving bead also captures barcoded oligos from adjacent sending beads.
  • Figure 1B depicts the computational scheme and describes the derivation of two matrices from each IRIS experiment.
  • Figure 2A through Figure 2C depict a validation of IRIS for profiling mouse brain coronal sections.
  • Figure 2A depicts an application of IRIS on a mouse brain coronal section, showcasing a UMAP clustering of receiving beads based on their gene expression, with color coding representing different annotated regions.
  • Figure 2B depicts an image reconstruction of all receiving beads derived from bead-bead connections, with coloring corresponding to the annotated regions based on gene expression shown in Figure 2A.
  • Figure 2C depicts an image reconstruction of all receiving beads derived from bead-bead connections, but each bead is colored according to the expression of known region-specific gene markers.
  • Figure 3A and Figure 3B depict data demonstrating an IRIS analysis of region- specific gene expression and cellular proportions in aging.
  • Figure 3A depicts a boxplot illustrating changes in region-specific gene expression between adult and aged mouse brains. Gene expression is normalized to total transcript per bead, log-transformed, and scaled.
  • Figure 3B depicts a dot plot displaying the log2-transformed enrichment fold of Disease-Associated Microglia (DAM) across various brain regions.
  • DAM Disease-Associated Microglia
  • Figure 4A through Figure 4L depicts an overview and validation of the IRISeq Platform.
  • Figure 4A depicts a schematic illustrating the IRISeq experimental pipeline utilizing barcoded gel beads (‘receiver beads’) to capture mRNA expression from nearby cells, along with barcoded oligos from adjacent ‘sender beads’ for spatial localization.
  • Figure 4B depicts a pie chart detailing the reagent cost breakdown for profiling a tissue section using a 0.6 cm x 0.6 cm 5
  • Figure 4C depicts a diagram showing the generation of gene count and bead-bead connection matrices from IRISeq data to identify region-specific gene expression and infer bead spatial locations for image reconstruction.
  • Figure 4D provides a depiction of a small-scale IRISeq experiment using a 0.6 cm x 0.6 cm bead array to profile a mouse brain hemisection.
  • Figure 4E depicts box plots displaying the distribution of unique transcripts and genes detected per receiver bead in the small-scale experiment.
  • Figure 4F depicts a UMAP plot showing the spatial distribution of receiver beads based on interactions with sender beads, colored by the number of unique transcripts per bead.
  • Figure 4G depicts data demonstrating that the gene expression data of receiver beads was integrated with spatial transcriptome data from 10x Visium (Sziraki et al., 2023, Nat. Genet.55, 2104–2116).
  • the UMAP plot shows the integrated gene expression clusters, with each bead colored by annotated brain regions.
  • Figure 4H depicts a UMAP plot visualizing the spatial distribution of receiver beads, with each bead colored by annotated brain regions.
  • Figure 4I provides a depiction of a large-area IRISeq experiment using a 1.5 cm x 1.5 cm bead array to profile two entire brain sections.
  • Figure 4J depicts a UMAP plot of receiver beads from the large-area IRISeq experiment, colored by the number of unique transcripts detected per bead.
  • Figure 4K and Figure 4L depict UMAP plots displaying gene expression clusters (Figure 4K) and reconstructed spatial distributions (Figure 4L) of receiver beads from the large-area experiment, colored by annotated brain regions.
  • Figure 5A and Figure 5B depicts bead generation and barcoding in IRISeq.
  • Fiture 5A depicts a schematic illustrating the generation of barcoded hydrogel beads (‘sender beads’ and ‘receiver beads’) through combinatorial indexing.
  • Figure 5B depicts a diagram showing the dual interaction between sender and receiver beads for capturing RNA from tissue samples and indexing spatial locations on the array.
  • Figure 6 depicts an exemplary IRISeq computational pipeline.
  • Figure 7A through Figure 7F depict data demonstrating the IRISeq quality control and performance comparison.
  • Figure 7A depicts (top panel) the distribution of unique bead-bead interactions per receiver bead.
  • the bottom panel shows the distribution of connected sender beads per receiver bead, with the median indicated by a dashed line in both panels.
  • FIG. 7C depicts UMAP plots that compare the spatial distribution of receiver beads from a small-scale IRISeq experiment (left) with 10x Visium data (right), colored by the expression of region- specific markers Ttr (ventricle region, top) and Hpca (hippocampus region, bottom).
  • Figure 7C depicts a UMAP plot showing the integrated gene expression profiles from IRISeq receiver beads and 10x Visium spots, colored by assay type.
  • Figure 7D depicts a UMAP plot illustrating spatial distribution colored by annotated brain regions, similar to Figure 4G.
  • Figure 7E depicts a UMAP plot showing the reconstructed spatial distribution of receiver beads from IRISeq, with beads colored according to the number of unique interaction oligos with a selected sender bead, validating the spatial reconstruction pipeline.
  • Figure 7F depicts histograms depicting Euclidean distances (in Figure 7E) between pairs of receiver beads connected to the same sender bead (left) versus distances between randomly selected receiver beads (right).
  • Figure 8A through Figure 8F depict data demonstrating the IRISeq enables spatial transcriptomic profilings at high resolution.
  • Figure 8A depicts a comparison of fluorescence intensities of DNA probes on 5 ⁇ m dendrimer-coated beads versus 5 ⁇ m non-coated beads.
  • Figure 8B depicts a bead recovery comparison between IRISeq and Slide-seq, plotted as bead frequency versus log(nCount_RNA).
  • Figure 8C depicts box plots displaying the distribution of unique transcripts and genes detected per receiver bead in two separate experiments with 10 ⁇ m beads (left) and 5 ⁇ m beads (right).
  • Figure 8D depicts UMAP plots showing the spatial distribution of 10 ⁇ m receiver beads in IRISeq experiment described in Figure 9E–9G, colored by expression of region-specific marker genes.
  • Figure 8E depicts UMAP plots showing the spatial distribution of 10 ⁇ m receiver beads in in IRISeq experiment described in Figure 9B–9D, colored by expression of region-specific marker genes.
  • Figure 8F depicts UMI density and detected gene features visualized on the reconstructed 5 ⁇ m bead array.
  • Figure 9A through Figure 9G depict data demonstrating the high-resolution spatial transcriptomics profiling enabled by IRISeq Platform.
  • Figure 9A depicts a schematic illustrating the dendrimer-based strategy for generating high-DNA-density beads. Functionalized beads are incubated with fourth- or fifth-generation PAMAM dendrimers, increasing each functional group by 64-fold or 128-fold, respectively. DNA primers are then conjugated to the beads, followed by split-pool bead barcoding.
  • Figure 9B depicts the spatial profiling of the mouse hindbrain region, showing UMI density distributions and anatomical boundaries.
  • Figure 9C depicts gene expression UMAP overlaid on the spatial reconstruction, highlighting clusters 7
  • Figure 9D depicts the visualization of Calb1, a Purkinje cell marker, demonstrating its specificity to the Purkinje cell layer.
  • Figure 9E depicts an analysis of a mouse brain tissue section encompassing the hippocampal region, with UMI density mapped onto the spatially reconstructed array.
  • Figure 9F depicts the fene expression UMAP overlaid on the spatial reconstruction, revealing clusters aligned with known anatomical features.
  • Figure 9G depicts an expression plot of C1ql2, a marker specific to the dentate gyrus.
  • Figure 10A through Figure 10J depict data demonstrating the spatial transcriptomic analysis of mouse brain aging using IRISeq.
  • Figure 10A depicts a schematic of IRISeq profiling across various brain regions, including the frontal isocortex, dorsal cortex, hippocampus, thalamus, hypothalamus, and additional associated regions. "Section 1" and “Section 2" are for the frontal and middle part of the cortex and “Section 3" is near the dorsal part of the cortex.
  • Figure 10B depicts a barplot showing the number of spatially barcoded receiver beads recovered per mouse individual.
  • Figure 10C and Figure 10D depict boxplots showing the number of unique transcripts (Figure 10C) and unique bead-bead interactions (Figure 10D) detected per receiver bead, aggregated across all brain sections for each mouse individual.
  • Figure 10E depicts UMAP plots showing the gene expression clusters of receiver beads integrating IRISeq data with published spatial transcriptomics datasets (Lang Kunststoffe et al., 2023, Nature 624, 333–342; Ortiz et al., 2020, Sci Adv 6, eabb3446), colored by annotated brain regions.
  • Figure 10F depicts an image reconstruction of all receiver beads derived from bead-bead connections, with coloring corresponding to the annotated regions based on gene expression shown in ( Figure 10E).
  • Figure 10G and Figure 10H depict image reconstructions of all receiver beads derived from bead-bead connections, but each bead is colored according to the expression of region-specific gene markers (Figure 10G) or cell type weight (Figure 10H) representing cell type abundance by RTCD analysis (Cable et al., 2022, Nat. Biotechnol.40, 517–526).
  • Figure 10I depicts a heatmap showing the gene expression specificity across regions, with expression data aggregated, normalized, and scaled for each region.
  • Figure 10J depicts a cell type distribution across regions, showing sub-cluster IDs from the previous single-cell study (Sziraki et al., 2023, Nat. Genet.55, 2104–2116).
  • Cell type weight is calculated using RCTD (Cable et al., 2022, Nat. Biotechnol.40, 517–526), integrating published single-cell data (Sziraki et al., 2023, Nat. Genet.55, 2104–2116) with IRISeq data, and then regional subtype proportions are aggregated, normalized, and scaled.
  • RCTD Click et al.
  • SiO Spinal et al.
  • IRISeq IRISeq
  • DGN Dentate Gyrus Neurons.
  • CtxPN1 Cortical Projection Neurons 1.
  • Endo Endothelial Cells.
  • Astro Astrocytes.
  • IMN Interbrain and Midbrain Neurons.
  • VLMC Vascular Leptomeningeal Cells.
  • Oligo Oligodendrocytes.
  • OBN Olfactory Bulb Neurons.
  • StrN Striatal Neurons.
  • HabN Habenula Neurons.
  • Epen Ependymal Cells.
  • ChPec Choroid Plexus Epithelial Cells.
  • Micro Microglia.
  • Figure 11A and Figure 11B depict data demonstrating the IRISeq region annotation and published datasets comparison.
  • Figure 11A depicts UMAPs by gene expression comparing IRISeq data with published spatial transcriptomics datasets (Ortiz et al., 2020, Sci Adv 6, eabb3446).
  • the left panels show the gene expression profiles colored by techniques (IRISeq, ‘ST’ for spatial transcriptomics, ‘Visium’ for 10X Visium), while the right panels color the beads by gene expression clusters specific to each brain region.
  • Figure 11A depicts (left panels) UMAPs showing the reconstructed spatial distribution of receiver beads from IRISeq, colored by gene expression clusters.
  • the right panels display the spatial distribution of transcriptome profiles from published datasets (Sziraki et al., 2023, Nat.
  • Figure 12A and Figure 12B depict data demonstrating the Comparison of cell subtype distributions between IRISeq and 10X Visium.
  • Figure 12A depicts UMAP plots showing the reconstructed spatial distribution of receiver beads from IRISeq, colored by cell type weight.
  • FIG. 12A depicts corresponding UMAP plots showing the spatial distribution of transcriptomes generated using 10X Visium (Sziraki et al., 2023, Nat. Genet.55, 2104–2116), also colored by cell type weight for the same cell types as in panel ( Figure 12A).
  • Figure 13A through Figure 13D depict data demonstrating the age-associated changes in region-specific gene expression programs.
  • Figure 13A provides bar charts depicting the number of genes differentially expressed (DE) between adult and aged animals across various brain regions, categorized as upregulated (red) and downregulated (blue). DE genes are defined by more than three-fold changes between the ages with an FDR-adjusted p-value ⁇ 0.05. 9
  • Figure 13B depicts a heatmap showing the log2-transformed fold changes in normalized gene expression between aged and adult animals for DE genes across different brain regions, distinguishing shared changes (left) from region-specific changes (right).
  • Figure 13C depicts barplots showing the scaled expression and standard error of gene modules related to interferon response across brain regions in both adult (blue) and aged (red) conditions. Gene inclusion for each module is detailed in panel ( Figure 13B). Expression values for each pathway were calculated by aggregating and normalizing pathway-related gene expressions, followed by log transformation and scaling.
  • Figure 13D provides reconstructed spatial maps display the expression levels of gene modules associated with the complement and interferon response pathways in adults (top) and aged animals (bottom) for Sections 2 (left) and 3 (right).
  • Figure 14A through Figure 14F depict data demonstrating the region-specific gene expression changes in aging.
  • Figure 14A depicts a barplot displaying the distribution of down-regulated (top) and up-regulated (bottom) DE genes across regions, highlighting genes consistently altered in more than ten brain regions, grouped by pathway.
  • Figure 14B depicts a volcano plot showing differentially expressed genes in the ventricles of Section 3 when comparing aged versus adult samples, with significant changes highlighted in red.
  • Figure 14C depicts scatter plots comparing the alterations in differentially expressed genes between ventricle regions from Sections 2 and 3, including a linear regression line. Only DE genes that are identified in both sections are shown.
  • Figure 14D depicts representative heatmaps of neuronal- related downregulated genes (left) and downregulated genes involved in smooth muscles (right).
  • Figure 14E depicts representative heatmaps of interferon-related upregulated genes (left) and globally upregulated immune-related genes (right).
  • Figure 14F depicts representative aging- associated genes displaying similar upregulation or downregulation patterns in the 10X Visium adult and aging dataset.
  • Figure 15 depicts cell type-specific expression patterns of interferon-related genes during aging. Shown are aggregated and normalized counts of interferon pathway-related genes showing enrichment in ependymal cells.
  • Figure 16A through Figure 16J depict data demonstrating the age-associated changes in region-specific cell type abundance and cell-cell interactions.
  • Figure 16A depicts an overview of the approach used to identify region-specific cellular depletion or expansion associated with aging, and to analyze cell-cell interaction dynamics.
  • Figure 16B depicts a scatter 10
  • FIG. 16C depicts a heatmap showing the fold change in key aging-associated cell types across different brain regions.
  • Figure 16D depicts an illustration demonstrating both global (Sziraki et al.) and region-specific changes (IRISeq) in various cell populations with aging. Significant changes are highlighted to show how specific cell types respond to aging in different brain regions, providing insights into the cellular dynamics associated with the aging process.
  • Figure 16E depicts spatial plots depicting DAM microglia, and DAM microglia-associated gene localization in the white matter regions of Secion-3.
  • Figure 16F depicts a volcano plot showing significant enrichment and depletion of cell-cell interaction changes in aged versus adult white matter, across two anatomically distinct white matter regions in sections 2 and 3, highlighting significantly changed cell-cell interactions in aging.
  • Figure 16G depicts representative spatial maps depicting white matter regions in two sections from the adult and aged brain. The top panels show representative maps of white matter regions from adult brains and the bottom panels from aged brains. The middle panels display beads indicating colocalization of reactive oligodendrocytes and DAM. The last panels show beads with both reactive oligodendrocytes and activated astrocytes.
  • Figure 16H depicts a histogram illustrating the null distribution of beads with both cell types assuming random distribution, with a dashed line marking the observed number.
  • Figure 16I depicts volcano plots comparing gene expression in beads with or without DAM in the white matter of Section 3, highlighting the top differentially expressed genes.
  • Figure 17A through Figure 17F depict data demonstrating the region-specific alterations of cellular abundance in brain aging.
  • Figure 17A depicts RCTD output probability score for DAM microglia (Non-binarized) across different regions.
  • Figure 17B depicts RCTD probability score for DAM microglia and reactive oligodendrocytes (Non-binarized) across two section-3 adult and aging reconstructed spatial sections.
  • Figure 17C depicts a display of the distribution of DAM, reactive oligodendrocytes, and activated astrocytes, colored by their relative abundance from RTCD analysis that integrates Visium data (Sziraki et al., 2023, Nat. Genet.55, 2104–2116) with the single-cell transcriptome atlas, shown for both adult and aged samples.
  • Figure 17D depicts a display of the distribution of interactions among reactive oligodendrocytes and DAM, reactive oligodendrocytes and activated astrocytes, and DAM and 11
  • FIG. 17E depicts a histogram illustrating the null distribution of beads with both reactive oligodendrocytes and activated astrocytes assuming random distribution, with a dashed line marking the observed number.
  • Figure 17F depicts a heatmap showing the normalized gene expression in DAM, reactive oligodendrocytes, activated astrocytes, and the corresponding main cell types.
  • Figure 18A through Figure 18G depict data demonstrating that IRISeq Reveals Lymphocyte-Dependent Shifts in Aging-Associated Interferon Gene Signatures in Immune- Deficient Brains.
  • Figure 18A and Figure 18B depict the study design and UMAP analysis.
  • Figure 18A depicts a schematic of the study design, showing the number of replicates per genotype, anatomical locations in coronal sections (top panel), and corresponding regional annotations (bottom panel).
  • Figure 18B depicts UMAP visualization of gene expression (top panels) and bead-based expression overlap between mutant and wild-type (WT) mouse brains (bottom panel).
  • Figure 18C depicts spatial reconstruction and clustering: Spatially reconstructed brain sections with clustered regions mapped.
  • Figure 18D depicts differential gene expression analysis: Number of genes upregulated or downregulated across different identified regions (Mutants vs. WT).
  • Figure 18E depicts a volcano plot: Log2 fold-change (Log2FC) of genes, highlighting key upregulated and downregulated genes in both mutants. Red-marked genes indicate shared downregulated genes between both mutants.
  • Figure 18F depicts interferon gene expression patterns: Heatmap showing interferon gene expression levels in mutants compared to WT, alongside a bar plot representing aggregated gene expression levels normalized across different regions.
  • Figure 18G depicts spatial expression of interferon genes: Aggregated interferon gene expression mapped onto spatially reconstructed arrays, with ventricles highlighted to indicate anatomical landmarks.
  • Figure 19A through Figure 19C depict data demonstrating an IRISeq immunodeficiency brain quality control analysis.
  • Figure 19A depicts the number of beads across sections, and replicates.
  • Figure 19B depicts the number of UMI’s per receiver bead across replicates.
  • Figure 19C provides a heatmap depicting upregulated genes across both mutants.
  • Figure 20A through Figure 20O depict data demonstrating identification of cell- type-specific gene expression and population changes in immune-deficient brains.
  • Figure 20A depicts a scatter plot of the number of cells profiled per sample across brain regions, colored by 12
  • Figure 20B depicts a UMAP projection of all brain cells, colored by annotated major cell types.
  • Figure 20C depicts a differential expression (DE) analysis identifying cell-type- specific DE genes in each mutant compared to wild-type. The scatter plot demonstrates a strong concordance of DE genes between the two mutants.
  • Figure 20D depicts a dot plot showing significantly enriched pathways among the upregulated and downregulated DE genes shared by both mutants.
  • Figure 20E depicts a scatter plot illustrating the high consistency of immune cell- specific DE genes across both mutants.
  • Figure 20F depicts a UMAP plot of immune cells, colored by annotated immune cell subtypes.
  • Figure 20G depicts a heatmap of the relative expression of cell-type–specific marker genes across immune subtypes.
  • Figure 20H depicts density plots of mutant-depleted (top) and mutant-enriched (bottom) immune cell states identified by Milo.
  • Figure 20I depicts a UMAP plot, (as in Figure 20F), colored by normalized expression of Dhcr7 (top) and Tmtc2 (bottom).
  • Figure 20J depicts a scatter plot showing the consistent changes in cell populations for both mutants in the hippocampal section (section 3), with top- changed cell types labeled.
  • Figure 20K depicts a box plot illustrating the decreased proportion of ependymal cells using data from a published brain aging atlas.
  • Figure 20L depicts a bar plot showing the deconvoluted proportion of ependymal cells across different brain regions in the IRISeq spatial dataset, with error bars representing standard error.
  • Figure 20M depicts a bar plot of the normalized aggregated expression of interferon response genes (Oasl2, Ifit3b, Ift3, Isg15, Bst2, Rtp4) across genotypes, with error bars representing standard error.
  • Figure 20N depicts a volcano plot highlighting differentially expressed genes in immune-deficient brains.
  • Figure 20O depicts a bar plot showing enriched pathways among the downregulated genes in ependymal cells from immune-deficient brains.
  • Figure 21A and Figure 21B depict data demonstrating the quality metrics for single-cell analysis of immune-deficient mouse brains.
  • Figure 21A depicts box plots illustrating the distribution of unique molecular identifiers (UMIs) per cell in each sampled brain region (Section-1, Section-2, Section-3, and other regions).
  • Figure 21B depicts UMAP projections of single-cell transcriptomes, as in Figure 20B, with cells colored by genotype (WT, Rag1, Prkdc) on the left and by sampled brain regions on the right.
  • Figure 22 depicts data demonstrating the cross-reference of cell type annotations from this study with predicted cell classes from the Allen Brain Atlas. Each column represents a 13
  • Figure 23 depicts data demonstrating the cross-reference of cell type annotations from this study with predicted cell types from the Allen Brain Atlas. Each column represents a cell type annotated in the dataset, and each row corresponds to a cell type defined in the Allen Brain Atlas.
  • the heatmap color scale (ranging from 0 to 1) indicates the fraction of cells in each annotated type that were predicted to belong to each Allen cell type.
  • Figure 24 depicts data demonstrating the cross-reference of cell type annotations from this study with predicted cell types from the Brain aging atlas. Each column represents a cell type annotated in the dataset, and each row corresponds to a cell type defined in the brain aging atlas. The heatmap color scale (ranging from 0 to 1) indicates the fraction of cells in each annotated type that were predicted to belong to each cell type in the brain aging atlas. Rows and columns are hierarchically clustered to highlight similarities across annotations. [0043] Figure 25A and Figure 25B depict data demonstrating ependymal cell state and population changes in immune-deficient brains.
  • Figure 25A depicts a box plot comparing the proportion of ependymal cells in the hippocampal section (Section-3) of wild-type and immune- deficient (Rag1, Prkdc) brains, colored by genotype.
  • Figure 25B depicts bar plots showing normalized expression levels of Sspo, C3, and Ube2w in ependymal cells (Section-3) across genotypes. Error bars represent standard error.
  • Figure 26 shows an example of a photocleavable linker that can be incorporated into the oligonucleotides of the sender beads.
  • the present invention relates generally to a novel method, IRIS (Imaging Reconstruction using Indexed Sequencing), that enables spatial reconstruction solely through sequencing and without the need for a priori or a posteriori indexing processes.
  • IRIS Imaging Reconstruction using Indexed Sequencing
  • the core principle of IRIS is that neighboring beads in physical space exhibit the same connection 14
  • Ranges throughout this disclosure, various aspects of the invention can be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range.
  • the invention provides new methods for high-spatial- resolution, unbiased, transcriptional mapping in intact tissues, which does not require sophisticated imaging but can instead capitalize on the power of high-throughput Next 15
  • the optimized IRIS (Imaging Reconstruction using Indexed Sequencing) protocol follows the steps outlined in Figure 1A: (i) Bead Preparation: Oligo-barcoded beads are prepared in two types - 'receiver beads' coated with PolyT sequences to capture nearby cellular mRNA and 'sender beads' with a photocleavable linker, a unique barcode, and a PolyA sequence. (ii) Tissue Transfer and mRNA Capture: These beads are mixed together on a glass slide to form a monolayer. Frozen tissue sections are transferred onto the semi wet beads with hybridization buffer surface via cryosectioning.
  • the composition comprises at least one set of barcoded sender beads, wherein each sender bead comprises a plurality of nucleic acid molecules comprising a) a photocleavable linker, b) a primer sequence between the photocleavable linker sequence and the barcode sequence for sequencing library preparation, c) a bead-specific barcode sequence, d) a unique molecular identifier sequence (or UMI), and e) a capture sequence for binding to a receiver bead, wherein the photocleavable linker is positioned between the bead and the primer sequence such that cleavage of the linker results in the separation of the fragment of the nucleic acid molecule comprising the primer/barcode sequence/UMI/capture sequence from the sender bead.
  • each sender bead comprises a plurality of nucleic acid molecules comprising a) a photocleavable linker, b) a primer sequence between the photocleavable linker sequence and the barcode sequence for sequencing
  • the capture sequence comprises a poly-A sequence.
  • a barcode sequence is a unique sequence that can be used to distinguish a barcoded polynucleotide in a biological sample from other barcoded polynucleotides in the same biological sample.
  • the concept of “barcodes” and appending barcodes to nucleic acids and other proteinaceous and non-proteinaceous materials is known to one of ordinary skill in the art (see, e.g., Liszczak G et al. Angew Chem Int Ed Engl.2019 Mar 22;58(13):4144-4162). 16
  • a barcode sequence may have a length of 5 to 50 nucleotides (e.g., 5 to 40, 5 to 30, 5 to 20, 5 to 10, 10 to 50, 10 to 40, 10 to 30, or 10 to 20 nucleotides). In some embodiments, a barcode sequence may have a length of 5, 10, 15, 20, 25, 30, 35, 40, 45, or 50 nucleotides. Longer barcode sequences are also contemplated herein.
  • the polynucleotides of the sender bead set are coded with a specific set of barcode sequences and UMIs, while the polynucleotides of the receiver beads are coded with a different set of barcode sequences and UMIs.
  • Photocleavage of the sender bead set and capture of the released fragments by receiver beads in close proximity to the sender beads, and subsequent amplification, library preparation and sequencing of captured target molecules in combination with the amplification products generated from the sender/receiver capture provides proximity data for the receiver beads which can be used to generate a spatial map of the captured target molecules.
  • the length of a UMI may vary.
  • a UMI sequence may have a length of 5 to 50 nucleotides (e.g., 5 to 40, 5 to 30, 5 to 20, 5 to 10, 10 to 50, 10 to 40, 10 to 30, or 10 to 20 nucleotides). In some embodiments, a UMI sequence may have a length of 5, 10, 15, 20, 25, 30, 35, 40, 45, or 50 nucleotides. Longer UMI sequences are also contemplated herein.
  • the photocleavable linker is a photo-sensitive chemical bond (e.g., a chemical bond that dissociates when exposed to light such as ultraviolet light).
  • Cleaving capture probes in an area on the array that is outside of a biological sample can increase the sensitivity and/or efficiency of an assay by preventing analytes and/or probes from being captured on an area of the array outside of where the biological sample is disposed (e.g., not covered by the biological sample).
  • a photocleavable linker When a photocleavable linker is present, the cleavage reaction is triggered by light, and can be highly selective to the linker and consequently biorthogonal.
  • wavelength absorption for the photocleavable linker is located in the near-UV range of the spectrum.
  • the absorption wavelength of the photocleavable linker is from about 100 nm to about 600 nm, from about 250 nm to about 400 nm, from about 300 nm to about 350 nm, or from about 310 nm to about 365 nm. In some embodiments, the absorption wavelength of the photocleavable linker is about 100 nm, about 150 nm, about 200 nm, about 225 nm, about 250 nm, about 275 nm, about 300 nm, about 312 nm, about 325 nm, about 330 nm, about 340 nm, about 345 nm, about 17
  • Non-limiting examples of a photo-sensitive chemical bond that can be used in a photocleavable linker include those described in Leriche et al.
  • photocleavable linkers that comprise photosensitive chemical bonds include, but are not limited to, bromodeoxyuridine (BrdU), 3-amino-3-(2-nitrophenyl)propionic acid (ANP), orthonitrobenzyl (ONB), phenacyl ester derivatives, 8-quinolinyl benzenesulfonate, dicoumarin, 6-bromo-7-alkixycoumarin-4-ylmethoxy carbonyl, a bimane-based linker, and a bis- arylhydrazone based linker.
  • the photocleavable linker comprises the structure shown in Figure 26.
  • the composition comprises at least one set of barcoded receiver beads, wherein each receiver bead comprises a plurality of nucleic acid molecules comprising a) a primer sequence between the bead and the barcode sequence for sequencing library preparation, b) a bead-specific barcode sequence, c) a unique molecular identifier sequence (or UMI), and d) a capture sequence for binding to a target molecule of interest (e.g. DNA, RNA, mRNA, miR, etc.).
  • the capture sequence for binding to a target molecule of interest is also used to capture nucleic acid molecule fragments released from the sender beads following cleavage of the linker.
  • the receiver bead further comprises an additional capture sequence for binding to nucleic acid molecule fragments released from the sender beads following cleavage of the linker.
  • the capture sequence comprises a poly-T sequence.
  • the capture sequence comprises a plurality of random nucleotide sequences. 18
  • the present disclosure provides a method for generating and using a set of sender and receiver microbeads to perform expression profiling of tissue samples, with high resolution.
  • the method can include the steps of (a) attaching different nucleic acid probes to beads that are then captured upon a solid support to produce randomly located probe-possessing sender and receiver beads on the solid support, wherein the different nucleic acid probes each includes a barcode sequence, a UMI sequence or a combination thereof, and wherein each of the randomly located beads includes a different barcode sequence, UMI sequence or combination thereof from other randomly located beads on the solid support; (b) contacting a biological specimen with the solid support that has the randomly located sender and receiver beads; (c) hybridizing the probes presented by the randomly located receiver beads to (i) target nucleic acids from portions of the biological specimen that are proximal to the randomly located receiver beads and (ii) to probes presented by any randomly located sender beads that are proximal to the randomly located receiver
  • any of a variety of solid supports can be used in a method, composition or apparatus of the present disclosure.
  • Particularly useful solid supports are those used for nucleic acid arrays. Examples include glass, modified glass, functionalized glass, inorganic glasses, microspheres (e.g. inert and/or magnetic particles), plastics, polysaccharides, nylon, nitrocellulose, ceramics, resins, silica, silica-based materials, carbon, metals, an optical fiber or optical fiber bundles, polymers and multiwell (e.g. microtiter) plates.
  • a solid support can be within or part of a vessel such as a well, tube, channel, cuvette, Petri plate, bottle or the like.
  • the vessel is a well in a multiwell plate or microtiter plate. 19
  • a solid support can include a gel coating. Attachment, e.g., of nucleic acids to a solid support via a gel is exemplified by flow cells available commercially from Illumina Inc. (San Diego, Calif.) or described in US Pat. App. Pub. Nos. 2011/0059865 A1, 2014/0079923 A1, or 2015/0005447 A1; or PCT Publ. No. WO 2008/093098, each of which is incorporated herein by reference.
  • Exemplary gels that can be used in the methods and apparatus set forth herein include, but are not limited to, those having a colloidal structure, such as agarose; polymer mesh structure, such as gelatin; or cross-linked polymer structure, such as polyacrylamide, SFA (see, for example, US Pat. App. Pub. No. 2011/0059865 A1, which is incorporated herein by reference) or PAZAM (see, for example, US Pat. App. Publ. Nos.2014/0079923 A1, or 2015/0005447 A1, each of which is incorporated herein by reference).
  • a solid support can be configured as an array of features to which beads can be attached. The features can be present in any of a variety of desired formats.
  • the features can be wells, pits, channels, ridges, raised regions, pegs, posts or the like.
  • wells of a substrate can include gel material (with or without beads) as set forth in US Pat. App. Publ. No.2014/0243224 A1, which is incorporated herein by reference.
  • Features can appear on a solid support as a grid of spots or patches.
  • the features can be located in a repeating pattern or in an irregular, non-repeating pattern.
  • repeating patterns can include hexagonal patterns, rectilinear patterns, grid patterns, patterns having reflective symmetry, patterns having rotational symmetry, or the like. Asymmetric patterns can also be useful.
  • the pitch of an array can be the same between different pairs of nearest neighbor features or the pitch can vary between different pairs of nearest neighbor features.
  • features on a solid support can each have an area that is larger than about 100 nm 2 , 250 nm 2 , 500 nm 2 , 1 ⁇ m 2 , 2.5 ⁇ m 2 , 5 ⁇ m 2 , 10 ⁇ m 2 or 50 ⁇ m 2 .
  • features can each have an area that is smaller than about 50 ⁇ m 2 , 25 ⁇ m 2 , 10 ⁇ m 2 , 5 ⁇ m 2 , 1 ⁇ m 2 , 500 nm 2 , or 100 nm 2 .
  • the preceding ranges can describe the apparent area of a bead or other particle on a solid support when viewed or imaged from above. 20
  • Beads employ a collection of beads or other particles, to which oligonucleotides are attached.
  • Suitable bead compositions include those used in peptide, nucleic acid and organic moiety synthesis, including, but not limited to, plastics, ceramics, glass, polystyrene, methylstyrene, acrylic polymers, paramagnetic materials, thoriasol, carbon graphite, titanium dioxide, latex or cross-linked dextrans such as Sepharose, cellulose, nylon, cross-linked micelles and Teflon may all be used. “Microsphere Detection Guide” from Bangs Laboratories, Fishers Ind.
  • the beads need not be spherical; irregular particles may be used.
  • the beads may be porous, thus increasing the surface area of the bead available for either capture probe attachment or tag attachment.
  • the bead sizes can range from nanometers, for example, 100 nm, to millimeters, for example, 1 mm, with beads from about 0.2 ⁇ m to about 200 ⁇ m commonly employed, and from about 5 to about 20 ⁇ m being within the range currently exemplified, although in some embodiments smaller or larger beads may be used.
  • the particles can be randomly arrayed upon the surface of a solid support (e.g., a glass slide).
  • the instant methods can employ an array of beads, wherein different nucleic acid probes are attached to different beads in the array.
  • each bead can be attached to a different nucleic acid probe and the beads can be randomly distributed on the solid support in order to effectively attach the different nucleic acid probes to the solid support.
  • the solid support can include wells having dimensions that accommodate no more than a single bead. In such a configuration, the beads may be attached to the wells due to forces resulting from the fit of the beads in the wells.
  • Nucleic acid probes that are attached to beads can include barcode sequences.
  • a population of the beads can be configured such that each bead is attached to a barcode and many different beads each with a different barcode are present in the population.
  • randomly distributing the beads to a solid support will result in randomly locating the nucleic acid probe-presenting beads (and their respective barcode sequences) on the solid support.
  • redundancy-comprising population of beads on a solid support especially one that has a capacity that is greater than the number of unique barcodes in the bead population—will tend to result in redundancy of barcodes on the solid support, which will tend to reduce image resolution in the context of the instant disclosure (i.e., where the precise location of a barcoded bead cannot be resolved due to redundancy of barcode use within an arrayed population of beads, it is contemplated that such redundant locations will simply be eliminated during data analysis.
  • a bead or other nucleic acid-presenting solid support of the instant disclosure can include, or can be made by the methods set forth herein to attach, a plurality of different nucleic 22
  • a bead or other nucleic acid-presenting solid support can include at least 10, 100, 1 ⁇ 10 3 , 1 ⁇ 10 4 , 1 ⁇ 10 5 , 1 ⁇ 10 6 , 1 ⁇ 10 7 , 1 ⁇ 10 8 , 1 ⁇ 10 9 or more different probes.
  • a bead or other nucleic acid-presenting solid support can include at most 1 ⁇ 10 9 , 1 ⁇ 10 , 1 ⁇ 10 , 1 ⁇ 10 , 1 ⁇ 10 , 1 ⁇ 10 , 100, or fewer different probes. It will be understood that each of the different probes can be present in several copies, for example, when the probes have been amplified to form a cluster.
  • the above ranges can describe the number of different nucleic acid clusters on a bead or other nucleic acid-presenting solid support of the instant disclosure. It will also be understood that the above ranges can describe the number of different barcodes, target capture sequences, or other sequence elements set forth herein as being unique (or sufficiently unique) to particular nucleic acid probes. Alternatively or additionally, the ranges can describe the number of extended probes or modified probes created on a bead or other nucleic acid-presenting solid support of the instant disclosure using a method set forth herein. [0073] Features may be present on a bead or other solid support of the instant disclosure prior to contacting the bead or other solid support with nucleic acid probes.
  • the primers can be attached at the features, whereas interstitial areas outside of the features substantially lack any of the primers.
  • Nucleic acid probes can be captured at preformed features on a bead or other solid support, and optionally amplified on the bead or other solid support, e.g., using methods set forth in U.S. Pat. Nos.8,895,249 and 8,778,849 and/or U.S. Patent Publication No.2014/0243224 A1, each of which is incorporated herein by reference.
  • a bead or other solid support may have a lawn of primers or may otherwise lack features.
  • a feature can be formed by virtue of attachment of a nucleic acid probe on the bead or other solid support.
  • the captured nucleic acid probe can be amplified on the bead or other solid support such that the resulting cluster becomes a feature.
  • attachment is exemplified above as capture between a primer and a complementary portion of a probe, it will be understood that capture moieties other than primers can be present at pre-formed features or as a lawn.
  • Other exemplary capture moieties include, but are not limited to, chemical moieties capable of reacting with a nucleic acid probe to create a covalent bond or receptors capable of binding non-covalently to a ligand on a nucleic acid probe.
  • a step of attaching nucleic acid probes to a bead or other solid support can be 23
  • the probes have random access to the surface (whether the surface has pre-formed features configured to attach the probes or a uniform surface configured for attachment). Accordingly, the probes can be randomly located on the bead or other solid support. [0075] The total number and variety of different probes that end up attached to a surface can be selected for a particular application or use.
  • the number of different probe species can exceed the occupancy of the bead or other solid support for probes.
  • the number and variety of different probes that attach to the bead or other solid support can be equivalent to the probe occupancy of the bead or other solid support.
  • the number and variety of different probe species on the bead or other solid support can be less than the occupancy (i.e. there will be redundancy of probe species such that the bead or other solid support may contain multiple features having the same probe species).
  • Such redundancy can be achieved, for example, by contacting the bead or other solid support with a fluidic mixture that contains a number and variety of probe species that is substantially lower than the probe occupancy of the bead or other solid support.
  • Attachment of the nucleic acid probes can be mediated by hybridization of the nucleic acid probes to complementary primers that are attached to the bead or other solid support, chemical bond formation between a reactive moiety on the nucleic acid probe and the bead or other solid support (examples are set forth in U.S. Pat. Nos.8,895,249 and 8,778,849, and in U.S.
  • nucleic acid probe can have a universal sequence that complements surface-attached primers or the different probes can have a common moiety that mediates attachment to the surface.
  • each of the different probes (or a subpopulation of different probes) can have a unique (or sufficiently unique) sequence that complements a unique (or sufficiently unique) primer on the bead or other solid support or they can have a unique (or sufficiently unique) moiety that interacts with one or more different reactive moiety on the bead or other solid support.
  • the unique (or sufficiently unique) primers or unique (or sufficiently unique) moieties can, optionally, be attached at predefined locations in order to selectively capture particular probes, or particular types of probes, at the respective predefined locations.
  • One or more features on a bead or other solid support can each include a single molecule of a particular probe.
  • the features can be configured, in some embodiments, to accommodate no more than a single nucleic acid probe molecule. However, whether or not the feature can accommodate more than one nucleic acid probe molecule, the feature may nonetheless include no more than a single nucleic acid probe molecule.
  • an individual feature can include a plurality of nucleic acid probe molecules, for example, an ensemble of nucleic acid probe molecules having the same sequence as each other.
  • the ensemble can be produced by amplification from a single nucleic acid probe template to produce amplicons, for example, as a cluster attached to the surface.
  • a method set forth herein can use any of a variety of amplification techniques. Exemplary techniques that can be used include, but are not limited to, polymerase chain reaction (PCR), rolling circle amplification (RCA), multiple displacement amplification (MDA), or random prime amplification (RPA).
  • the amplification can be carried out in solution, for example, when features of an array are capable of containing amplicons in a volume having a desired capacity.
  • an amplification technique used in a method of the present disclosure will be carried out on solid phase.
  • one or more primer species e.g. universal primers for one or more universal primer binding site present in a nucleic acid probe
  • one or both of the primers used for amplification can be attached to a bead or other solid support (e.g. via a gel). Formats that utilize two species of primers attached to a bead or other solid support are often 25
  • bridge amplification because double stranded amplicons form a bridge-like structure between the two surface attached primers that flank the template sequence that has been copied.
  • Exemplary reagents and conditions that can be used for bridge amplification are described, for example, in U.S. Pat. Nos.5,641,658; 7,115,400; and 8,895,249; and/or U.S. Patent Publication Nos.2002/0055100 A1, 2004/0096853 A1, 2004/0002090 A1, 2007/0128624 A1 and 2008/0009420 A1, each of which is incorporated herein by reference.
  • Solid-phase PCR amplification can also be carried out with one of the amplification primers attached to a bead or other solid support and the second primer in solution.
  • An exemplary format that uses a combination of a surface attached primer and soluble primer is the format used in emulsion PCR as described, for example, in Dressman et al., Proc. Natl. Acad. Sci. USA 100:8817-8822 (2003), WO 05/010145, or U.S. Patent Publication Nos.2005/0130173 A1 or 2005/0064460 A1, each of which is incorporated herein by reference.
  • Nucleic acid probes that are used in a method set forth herein or present in an apparatus or composition of the present disclosure can include barcode sequences, and for embodiments that include a plurality of different nucleic acid probes, each of the probes can include a different barcode sequence from other probes in the plurality.
  • Barcode sequences can be any of a variety of lengths.
  • Longer sequences can generally accommodate a larger number and variety of barcodes for a population. Generally, all probes in a plurality will have the same length barcode (albeit with different sequences), but it is also possible to use different length barcodes for different probes.
  • a barcode sequence can be at least 2, 4, 6, 8, 10, 12, 15, 20 or more nucleotides in length.
  • a method of the present disclosure can include a step of performing a nucleic acid detection reaction on a bead or other solid support to determine barcode sequences of nucleic acid probes that are located on the bead or other solid support.
  • the probes are randomly located on the bead or other solid support and the nucleic acid detection reaction provides information to locate each of the different probes.
  • Exemplary nucleic acid detection methods include, but are not limited to nucleic acid sequencing of a probe, hybridization of 26
  • a method of the present disclosure can include a step of contacting a biological specimen (e.g., a tissue sample) with a bead or other solid support that has nucleic acid probes attached thereto.
  • a biological specimen e.g., a tissue sample
  • the nucleic acid probes are randomly located on the bead or other solid support.
  • Bead-Attached Oligonucleotides [0085] Certain aspects of the instant disclosure employ a nucleotide- or oligonucleotide- adorned bead, where the bead-attached oligonucleotide includes one or more of the following: a linker; an identical sequence for use as a sequencing priming site; a uniform or near-uniform nucleotide or oligonucleotide sequence; a Unique Molecular Identifier which differs for each priming site; an oligonucleotide redundant sequence for capturing polyadenylated mRNAs and priming reverse transcription (i.e., a poly-T sequence); and at least one oligonucleotide barcode which provides an substrate for spatial identification of an individual bead's position within a bead array.
  • Exemplified bead-attached oligonucleotides of the instant disclosure include an oligonucleotide spatial barcode designed to be unique to each bead within a bead array (or at least wherein the majority of such barcodes are unique to a bead within a bead array—e.g., it is expressly contemplated here and elsewhere herein that a bead array possessing only a small fraction of beads (e.g., even up to 10%, 20%, 30% or 40% or more of total beads) having non- unique spatial barcodes (e.g., attributable to a relative lack of degeneracy within the bead population, e.g., due to a probabilistically determinable lack of sequence degeneracy calculated as possible within the bead population, as then compared to the number of sites across which the bead population is ultimately distributed and/or due to an artifact such as non-randomness of bead association occurring during pool-and-split rounds
  • oligonucleotides of the instant disclosure also include a poly-dT sequence; a Unique Molecular Identifier (UMI); a barcode; a common sequence (“PCR priming site”) to enable PCR amplification, and a linker.
  • Exemplified sender bead-attached oligonucleotides of the instant disclosure also include a poly-dA sequence; a Unique Molecular Identifier (UMI); a barcode; a common sequence (“PCR priming site”) to enable PCR amplification, and a photocleavable linker.
  • mRNAs present in the sample bind to poly-dT-presenting bead-attached oligonucleotides on the receiver beads.
  • the mRNAs are reverse-transcribed into cDNAs.
  • the barcoded cDNAs can then be amplified in pools for high- throughput mRNA-seq.
  • the poly-dA presenting bead-attached oligonucleotides on the sender beads bind to poly-dT-presenting bead-attached oligonucleotides on the receiver beads. Photocleavage of the linker releases the bead bound oligonucleotides from the sender beads.
  • the pool of microparticles (here, microbeads) is repeatedly split into four equally sized oligonucleotide synthesis reactions, to which one of the four DNA bases is added, and then pooled together after each cycle for multiple (e.g., at least 12) cycles.
  • the barcode synthesized on any individual bead reflects that bead's unique (or sufficiently unique) path through the series of synthesis reactions.
  • the result is a pool of microparticles, each possessing a unique barcode sequences.
  • Extension of the split-pool process for additional cycles can provide for production of an even greater numbers of possible barcode sequences for use in the compositions and methods of the instant disclosure.
  • any beads that turn out to be redundant in barcode within the array could be performed, e.g., during data analysis.
  • UMI unique molecular identifier
  • the linker of a sender bead- attached oligonucleotide is a chemically-cleavable, straight-chain polymer.
  • the linker is a photolabile optionally substituted hydrocarbon polymer.
  • the linker of a receiver bead-attached oligonucleotide is a non-cleavable, straight-chain polymer. In some embodiments, the linker is a non-cleavable, optionally substituted hydrocarbon polymer. In certain embodiments, the linker is a polyethylene glycol (PEG) linker.
  • the oligonucleotide probe used in a composition or method set forth herein can include a target capture moiety. In particular embodiments, the target capture moiety is a target capture sequence. The target capture sequence is generally complementary to a target sequence such that target capture occurs by formation of a probe-target hybrid complex.
  • the target capture sequence for the receiver bead comprises a poly-dT sequence. In some embodiments, the target capture sequence for the sender bead comprises a poly-dA sequence.
  • a plurality of different nucleic acid probes can include different target capture sequences that hybridize to different target nucleic acid sequences from a biological specimen. Different target capture sequences can be used to selectively bind to one or more desired target nucleic acids from a biological specimen.
  • target nucleic acids can be captured and analyzed in a method set forth herein including, but not limited to, messenger RNA (mRNA), copy DNA (cDNA), genomic DNA (gDNA), ribosomal RNA (rRNA) or transfer RNA (tRNA).
  • mRNA messenger RNA
  • cDNA copy DNA
  • gDNA genomic DNA
  • rRNA ribosomal RNA
  • tRNA transfer RNA
  • a method set forth herein can include a step of hybridizing nucleic acid probes, that are on a supported bead array, to target nucleic acids that are from portions of the biological specimen that are proximal to the probes.
  • a target nucleic acid will flow or diffuse from a region of the biological specimen to an area of the probe-presenting bead array that is in proximity with that region of the specimen.
  • the target nucleic acid will interact with nucleic acid probes that are proximal to the region of the specimen from which the target nucleic acid was released.
  • a target-probe hybrid complex can form where the target nucleic acid encounters a complementary target capture sequence on a nucleic acid probe.
  • the location of the target-probe hybrid complex will generally correlate with the region of the biological specimen from where the target nucleic acid was derived.
  • the beads will include a plurality of nucleic acid probes, the biological specimen will release a plurality of target nucleic acids and a plurality of target-probe hybrids will be formed on the beads.
  • the sequences of the target nucleic acids and their locations on the bead array will provide spatial information about the nucleic acid content of the biological specimen.
  • a method of the present disclosure can include a step of extending bead-attached probes to which target nucleic acids are hybridized.
  • the probes include barcode sequences
  • the resulting extended probes will include the barcode sequences and sequences from the target nucleic acids (albeit in complementary form).
  • the extended probes are thus spatially tagged versions of the target nucleic acids from the biological specimen or the sender oligonucleotides.
  • the sequences of the extended probes identify a) what nucleic acids are in the biological specimen and b) where in the receiver bead was in proximity to any sender beads. It will be understood that other sequence elements that are present in the nucleic acid probes can also be included in the extended probes. Such elements include, for example, primer binding sites, cleavage sites, other tag sequences (e.g. sample identification tags), capture 30
  • nucleic acid binding proteins or nucleic acid enzymes, or the like.
  • Extension of probes can be carried out using methods exemplified herein or otherwise known in the art for amplification of nucleic acids or sequencing of nucleic acids.
  • one or more nucleotides can be added to the 3′ end of a nucleic acid, for example, via polymerase catalysis (e.g. DNA polymerase, RNA polymerase or reverse transcriptase). Chemical or enzymatic methods can be used to add one or more nucleotide to the 3′ or 5′ end of a nucleic acid.
  • One or more oligonucleotides can be added to the 3′ or 5′ end of a nucleic acid, for example, via chemical or enzymatic (e.g. ligase catalysis) methods.
  • a nucleic acid can be extended in a template directed manner, whereby the product of extension is complementary to a template nucleic acid that is hybridized to the nucleic acid that is extended.
  • a DNA primer is extended by a reverse transcriptase using an RNA template, thereby producing a cDNA.
  • an extended probe made in a method set forth herein can be a reverse transcribed DNA molecule.
  • an extended probe can include at least, 1, 2, 5, 10, 25, 50, 100, 200, 500, 1000 or more nucleotides that are copied from a target nucleic acid.
  • the length of the extension product can be controlled, for example, using reversibly terminated nucleotides in the extension reaction and running a limited number of extension cycles. The cycles can be run as exemplified for SBS techniques and the use of labeled nucleotides is not necessary.
  • an extended probe produced in a method set forth herein can include no more than 1000, 500, 200, 100, 50, 25, 10, 5, 2 or 1 nucleotides that are copied from a target nucleic acid.
  • extended probes can be any length within or outside of the ranges set forth above.
  • probes used in a method, composition or apparatus set forth herein need not be nucleic acids. Other molecules can be used such as proteins, carbohydrates, small molecules, particles or the like. Probes can be a combination of a nucleic acid component (e.g. having a barcode, primer binding site, cleavage site and/or other sequence element set forth herein) and another moiety (e.g. a moiety that captures or modifies a target nucleic acid).
  • a method set forth herein can further include a step of acquiring an image of a 31
  • the solid support can be in any of a variety of states set forth herein.
  • the bead array can include attached nucleic acid probes or clusters derived from attached nucleic acid probes.
  • the number of bead-attached oligonucleotides present upon an individual bead can vary across a wide range, e.g., from tens to thousands, or millions, or more.
  • oligonucleotides of the instant disclosure can possess any number of other art- recognized features while remaining within the scope of the instant disclosure.
  • a capture material is employed to associate a bead array with a solid support (e.g., a glass slide).
  • a liquid capture material such as liquid tape can be applied as a liquid, which then dries to a vinyl polymer that resists dirt, dust, chemicals, and moisture, ensuring that applied beads are attached to a capture material-coated slide in a dry condition. It is contemplated that beads of the instant disclosure can be applied to a capture material-coated solid support, either immediately upon deposit of capture material to the solid support, or following an initial drying period for the capture material.
  • Capture materials of the instant disclosure can be applied by any of a number of methods, including brushed onto the solid support, sprayed onto the solid support, or the like, or via submersion of the solid support in the capture material.
  • a brush top applicator can allow coverage without gaps and can enable access to tight spaces, which offers advantages in certain embodiments over forms of capture material (i.e., tape) that are applied in a non-liquid state.
  • Other capture materials are also contemplated, including any art-recognized glue or other reagent that is (a) spreadable and/or depositable upon a solid surface (e.g., upon a slide, 32
  • a slide that allows for light transmission through the slide, e.g., a microscope slide
  • elastomers which are generally defined as polymers that possess viscoelasticity (i.e., both viscosity and elasticity), very weak inter-molecular forces, and generally low Young's modulus and high failure strain compared with other materials
  • elastomers e.g., neoprene
  • silicone elastomers elastomers
  • tissue section is employed.
  • the tissue can be derived from a multicellular organism.
  • Exemplary multicellular organisms include, but are not limited to a mammal, plant, algae, nematode, insect, fish, reptile, amphibian, fungi or Plasmodium falciparum.
  • Exemplary species are set forth previously herein or known in the art.
  • the tissue can be freshly excised from an organism or it may have been previously preserved for example by freezing, embedding in a material such as paraffin (e.g.
  • a tissue section can be cryosectioned, using techniques and compositions as described herein and as known in the art.
  • a tissue can be permeabilized and the cells of the tissue lysed. Any of a variety of art-recognized lysis treatments can be used.
  • Target nucleic acids that are released from a tissue that is permeabilized can be captured by nucleic acid probes, as described herein and as known in the art.
  • the methods comprise delivering to a biological tissue permeabilization reagents (e.g., detergents such as Triton-X 100 or Tween-20).
  • a tissue can be prepared in any convenient or desired way for its use in a method, composition or apparatus herein. Fresh, frozen, fixed or unfixed tissues can be used. A tissue can be fixed or embedded using methods described herein or known in the art. [0107] A tissue sample for use herein, can be fixed by deep freezing at temperature suitable to maintain or preserve the integrity of the tissue structure, e.g. less than ⁇ 20° C. In another example, a tissue can be prepared using formalin-fixation and paraffin embedding (FFPE) methods which are known in the art. Other fixatives and/or embedding materials can be 33
  • a fixed or embedded tissue sample can be sectioned, i.e. thinly sliced, using known methods.
  • a tissue sample can be sectioned using a chilled microtome or cryostat, set at a temperature suitable to maintain both the structural integrity of the tissue sample and the chemical properties of the nucleic acids in the sample.
  • additional fixatives include alcohol fixation (e.g., methanol fixation, ethanol fixation), glutaraldehyde fixation and paraformaldehyde fixation.
  • a tissue sample will be treated to remove embedding material (e.g. to remove paraffin or formalin) from the sample prior to release, capture or modification of nucleic acids.
  • Treatment can occur prior to contacting the tissue sample with a solid support-captured bead array as set forth herein or the treatment can occur while the tissue sample is on the solid support-captured bead array.
  • an appropriate solvent e.g. xylene and ethanol washes.
  • Treatment can occur prior to contacting the tissue sample with a solid support-captured bead array as set forth herein or the treatment can occur while the tissue sample is on the solid support-captured bead array.
  • Exemplary methods for manipulating tissues for use with solid supports to which nucleic acids are attached are set forth in US Pat. App. Publ. No.2014/0066318 A1, which is incorporated herein by reference.
  • the thickness of a tissue sample or other biological specimen that is contacted with a bead array in a method, composition or apparatus set forth herein can be any suitable thickness desired.
  • the thickness will be at least 0.1 ⁇ m, 0.25 ⁇ m, 0.5 ⁇ m, 0.75 ⁇ m, 1 ⁇ m, 5 ⁇ m, 10 ⁇ m, 50 ⁇ m, 100 ⁇ m or thicker.
  • the thickness of a tissue sample that is contacted with bead array will be no more than 100 ⁇ m, 50 ⁇ m, 10 ⁇ m, 5 ⁇ m, 1 ⁇ m, 0.5 ⁇ m, 0.25 ⁇ m, 0.1 ⁇ m or thinner.
  • a sample is a biological sample.
  • Non-limiting examples of biological samples include tissues and cells.
  • the biological sample may be adult tissue, embryonic tissue, or fetal tissue, for example.
  • a biological sample is from a human or other animal.
  • a biological sample may be obtained from a murine (e.g., mouse or rat), feline (e.g., cat), canine (e.g., dog), equine (e.g., horse), bovine (e.g., cow), leporine (e.g., rabbit), porcine (e.g., pig), hircine (e.g., goat), ursine (e.g., bear), or piscine (e.g., fish).
  • a particularly relevant source for a tissue sample is a human being.
  • the sample can be derived from an organ, including for example, an organ of the central nervous system such as brain, brainstem, cerebellum, spinal cord, cranial nerve, or spinal nerve; an organ of the 34
  • musculoskeletal system such as muscle, bone, tendon or ligament
  • an organ of the digestive system such as salivary gland, pharynx, esophagus, stomach, small intestine, large intestine, liver, gallbladder or pancreas
  • an organ of the respiratory system such as larynx, trachea, bronchi, lungs or diaphragm
  • an organ of the urinary system such as kidney, ureter, bladder or urethra
  • a reproductive organ such as ovary, fallopian tube, uterus, vagina, placenta, testicle, epididymis, vas deferens, seminal vesicle, prostate, penis or scrotum
  • an organ of the endocrine system such as pituitary gland, pineal gland, thyroid gland, parathyroid gland, or adrenal gland
  • an organ of the circulatory system such as heart, artery, vein or capillary
  • an organ of the lymphatic system such as lymph
  • a tissue sample is obtained from a bodily fluid or excreta such as blood, lymph, tears, sweat, saliva, semen, vaginal secretion, ear wax, fecal matter or urine.
  • a sample from a human can be considered (or suspected) healthy or diseased when used. In some cases, two samples can be used: a first being considered diseased and a second being considered as healthy (e.g. for use as a healthy control). Any of a variety of conditions can be evaluated, including but not limited to, an autoimmune disease, cancer, cystic fibrosis, aneuploidy, pathogenic infection, psychological condition, hepatitis, diabetes, sexually transmitted disease, heart disease, stroke, cardiovascular disease, multiple sclerosis or muscular dystrophy.
  • Certain contemplated conditions include genetic conditions or conditions associated with pathogens having identifiable genetic signatures.
  • Target molecules [0114]
  • the instant compositions and methods can be applied to obtain spatially-resolvable abundance data for a wide range of macromolecules, including not only poly-A-tailed RNAs/transcripts, but also, e.g., non-poly-A-tailed RNAs (e.g., tRNAs, miRNAs, etc.; optionally specifically captured using sequence-specific oligonucleotide sequences), and DNAs (including, e.g., capture via gene- specific oligonucleotides, loaded transposases, etc.), and proteins (including, e.g., DNA- barcoded antibodies, optionally where a DNA barcode effectively tags a capture antibody for 35
  • the range of target molecules expressly contemplated for capture using the compositions and methods of the instant disclosure includes all forms of RNA (including, e.g., transcripts, tRNAs, rRNAs, miRNAs, etc.), DNAs (including, e.g., genomic DNAs, barcode DNAs, etc.) and proteins (including, e.g., antibodies that are tagged for binding and detection and/or other forms of protein, optionally including proteins captured by antibodies).
  • the cDNA library is modified to include a barcode or tag prior to sequencing.
  • a tag may include, for example, a primer binding site for sequencing.
  • a tag can include a nucleotide sequence having a length of at least 1 nucleotide, at least 2 nucleotides, at least 3 nucleotides, at least 4 nucleotides, at least 5 nucleotides, at least 10 nucleotides, at least 15 nucleotides, at least 20 nucleotides, at least 25 nucleotides, at least 30 nucleotides, at least 35 nucleotides, at least 40 nucleotides, at least 45 nucleotides, at least 50 nucleotides, or 50 nucleotides or greater, or a length within a range of any two of the foregoing lengths.
  • tagging is performed by tagmentation.
  • “tagmentation” can refer to the insertion of transposons into target nucleic acids such that the transposon cleaves the target nucleic acids, and adds adaptor sequences to the ends of the cleaved target nucleic acids.
  • Example methods of tagmentation are disclosed in U.S. Pat. Nos. 9,115,396; 9,080,211 ; 9,040,256; U.S. patent application publication 2014/0194324, each of which is incorporated herein by reference in its entirety.
  • Transposon based technology can be utilized for fragmenting DNA, for example, as exemplified in the workflow for NEXTERATM XT and FLEX DNA sample preparation kits (Illumina, Inc.), wherein target nucleic acids, such as genomic DNA, are treated with transposome complexes that simultaneously fragment and tag (tagmentation) the target, thereby creating a population of fragmented nucleic acid molecules tagged with unique adaptor sequences at the ends of the fragments.
  • a transposition reaction is a reaction wherein one or more transposons are inserted into target nucleic acids at random sites or almost random sites. Components in a 36
  • transposition reaction include a transposase (or other enzyme capable of fragmenting and tagging a nucleic acid as described herein, such as an integrase) and a transposon element that includes a double-stranded transposon end sequence that binds to the transposase (or other enzyme as described herein), and an adaptor sequence attached to one of the two transposon end sequences.
  • a transposase or other enzyme capable of fragmenting and tagging a nucleic acid as described herein, such as an integrase
  • transposon element that includes a double-stranded transposon end sequence that binds to the transposase (or other enzyme as described herein)
  • an adaptor sequence attached to one of the two transposon end sequences.
  • One strand of the double-stranded transposon end sequence is transferred to one strand of the target nucleic acid and the complementary transposon end sequence strand is not (a non- transferred transposon sequence).
  • the adaptor sequence can include one or more functional sequences or components (e.g., primer sequences, universal sequences, spacer regions, or index tag sequences) as needed or desired.
  • Sequencing Methods [0118] Some of the methods and compositions provided herein employ methods of sequencing nucleic acids. A number of DNA sequencing techniques are known in the art, including fluorescence-based sequencing methodologies (See, e.g., Birren et al, Genome Analysis Analyzing DNA, 1, Cold Spring Harbor, N.Y., which is incorporated herein by reference in its entirety). In some embodiments, automated sequencing techniques understood in that art are utilized.
  • parallel sequencing of partitioned amplicons can be utilized (PCT Publication No WO2006084132, which is incorporated herein by reference in its entirety).
  • DNA sequencing is achieved by parallel oligonucleotide extension (See, e.g., U.S. Pat. Nos.5,750,341; 6,306,597, which are incorporated herein by reference in their entireties). Additional examples of sequencing techniques include the Church polony technology (Mitra et al, 2003, Analytical Biochemistry 320, 55-65; Shendure et al, 2005 Science 309, 1728-1732; U.S. Pat.
  • NGS Next-generation sequencing methods can be employed in certain aspects of the instant disclosure to obtain a high volume of sequence information (such as are particularly required to perform deep sequencing of bead-associated RNAs following capture of RNAs) in a highly efficient and cost-effective manner.
  • NGS methods share the common feature of massively parallel, high-throughput strategies, with the goal of lower costs in comparison to older sequencing methods (see, e.g., Voelkerding et al, Clinical Chem., 55: 641-658, 2009; MacLean et al, Nature Rev. Microbiol, 7-287-296; which are incorporated herein by reference in their entireties).
  • NGS methods can be broadly divided into those that typically use template amplification and those that do not.
  • Amplification-utilizing methods include pyrosequencing commercialized by Roche as the 454 technology platforms (e.g., GS 20 and GS FLX), the Solexa platform commercialized by Illumina, and the Supported Oligonucleotide Ligation and Detection (SOLiDTM) platform commercialized by Applied Biosystems.
  • Non-amplification approaches also known as single—molecule sequencing, are exemplified by the HeliScope platform commercialized by Helicos Biosciences, SMRT sequencing commercialized by Pacific Biosciences, and emerging platforms marketed by VisiGen and Oxford Nanopore Technologies Ltd. [0120]
  • pyrosequencing U.S. Pat.
  • template DNA is fragmented, end-repaired, ligated to adaptors, and clonally amplified in-situ by capturing single template molecules with beads bearing oligonucleotides complementary to the adaptors.
  • Each bead bearing a single template type is compartmentalized into a water-in-oil microvesicle, and the template is clonally amplified using a technique referred to as emulsion PCR.
  • the emulsion is disrupted after amplification and beads are deposited into individual wells of a picotitre plate functioning as a flow cell during the sequencing reactions.
  • each of the four dNTP reagents occurs in the flow cell in the presence of sequencing enzymes and luminescent reporter such as luciferase.
  • luminescent reporter such as luciferase.
  • the resulting production of ATP causes a burst of luminescence within the well, which is recorded using a CCD camera. It is possible to achieve read lengths greater than or equal to 400 bases, and 10 6 sequence reads can be achieved, resulting in up to 500 million base pairs (Mb) of sequence.
  • Mb million base pairs
  • sequencing data are produced in the form of shorter-length reads.
  • single-stranded fragmented DNA is end-repaired to generate 5′-phosphorylated blunt ends, followed by Klenow-mediated addition of a single A base to the 3′ end of the fragments.
  • Klenow-mediated addition facilitates addition of T-overhang adaptor oligonucleotides, which are subsequently used to capture the template-adaptor molecules on the surface of a flow cell that is studded with oligonucleotide anchors.
  • the anchor is used as a PCR primer, but because of the length of the template and its proximity to other nearby anchor oligonucleotides, extension by PCR results in the “arching over” of the molecule to hybridize with an adjacent anchor oligonucleotide to form a bridge structure on the surface of the flow cell. These loops of DNA are denatured and cleaved. Forward strands are then sequenced with reversible dye terminators. The sequence of incorporated nucleotides is determined by detection of post-incorporation fluorescence, with each fluorophore and block removed prior to the next cycle of dNTP addition.
  • Sequence read length ranges from 36 nucleotides to over 50 nucleotides, with overall output exceeding 1 billion nucleotide pairs per analytical run.
  • Sequencing nucleic acid molecules using SOLiD technology can initially involve fragmentation of the template, ligation to oligonucleotide adaptors, attachment to beads, and clonal amplification by emulsion PCR.
  • beads bearing template are immobilized on a derivatized surface of a glass flow-cell, and a primer complementary to the adaptor oligonucleotide is annealed.
  • a primer complementary to the adaptor oligonucleotide is annealed.
  • this primer is instead used to provide a 5′ phosphate group for ligation to interrogation probes containing two probe-specific bases followed by 6 degenerate bases and one of four fluorescent labels.
  • interrogation probes have 16 possible combinations of the two bases at the 3′ end of each probe, and one of four fluors at the 5′ end. Fluor color, and thus identity of each probe, corresponds to specified color-space coding schemes.
  • nanopore sequencing is employed (see, e.g., Astier et al, J. Am. Chem. Soc.2006 Feb.8; 128(5): 1705-10, which is incorporated by reference).
  • the theory behind nanopore sequencing has to do with what occurs when a nanopore is immersed in a conducting fluid and a potential (voltage) is applied across it. Under these conditions a slight electric current due to conduction of ions through the nanopore can be observed, and the amount of current is exceedingly sensitive to the size of the nanopore.
  • the Ion Torrent technology is a method of DNA sequencing based on the detection of hydrogen ions that are released during the polymerization of DNA (see, e.g., Science 327(5970): 1190 (2010); U.S. Pat. Appl. Pub.
  • a microwell contains a template DNA strand to be sequenced. Beneath the layer of microwells is a hypersensitive ISFET ion sensor. All layers are contained within a CMOS semiconductor chip, similar to that used in the electronics industry. When a dNTP is incorporated into the growing complementary strand a hydrogen ion is released, which triggers a hypersensitive ion sensor. If homopolymer repeats are present in the template sequence, multiple dNTP molecules will be incorporated in a single cycle.
  • the per base accuracy of the Ion Torrent sequencer is approximately 99.6% for 50 base reads, with approximately 100 Mb generated per run.
  • the read-length is 100 base pairs.
  • the accuracy for homopolymer repeats of 5 repeats in length is approximately 98%.
  • the benefits of ion semiconductor sequencing are rapid sequencing speed and low upfront and operating costs.
  • Computational Analysis of Receiver:Sender Bead Connections [0125] Following the sequencing process, computational analysis is performed. In some embodiments, the data from sequencing of the molecules released from the sender beads 40
  • Each bead connection includes unique molecular identifiers (UMIs) which help in identifying and quantifying individual connection molecules.
  • UMIs unique molecular identifiers
  • R1 which contains the barcode for the receiver
  • R2 which contains the barcodes for the sender bead.
  • the reads are mapped to a list of barcodes with 1 base pair error, including the UMI sequence. Duplicated reads are then filtered, and a file is generated with receiver bead, UMI, and sender bead barcode, where each line represents a unique molecular connection between a receiver bead and a sender bead.
  • filtering is performed to ensure each connection between two beads has a minimum of 10 UMIs, ensuring a sufficient level of data for analysis.
  • a matrix is generated where each row represents a receiver bead, and each column represents a sender bead. The values in the matrix correspond to the number of UMIs for each receiver-sender connection.
  • principle component analysis PCA
  • an elbow plot is generated to determine the optimal number of principal components. The elbow plot helps identify the point at which the explained variance begins to level off, indicating the most significant components.
  • the PCA matrix of receiver and sender connections is subjected to Uniform Manifold Approximation and Projection (UMAP) to obtain a square-shaped projection, similar to the bead array that was generated.
  • UMAP is performer using a minimum distance of 0.2 and approximately 20 neighbors.
  • the UMAP Coordinates for each receiver bead are extracted and are used for subsequent mapping of receiver spatial location.
  • Computational Analysis of Captured Target Molecules [0130] After the sequencing process, the data is obtained in the form of two sets of FASTQ files: R1 and R2.
  • R1 FASTQ files contain the barcode sequences for receiver beads along with their associated Unique Molecular Identifiers (UMIs).
  • UMIs Unique Molecular Identifiers
  • R2 FASTQ files contain the sequence data for the captured target molecules.
  • RNA molecules contain sequence data for tagmented cDNA sequences of captured RNA molecules.
  • the barcode sequences from R1 are mapped to a list of bead barcodes with a tolerance of 1 base pair error.
  • the identified bead barcode is then added as an identifier (ID) for the corresponding sequences in R2.
  • ID identifier
  • New Read2 files are generated where the name of each sequence in R2 contains the corresponding Read1 barcode. Additionally, any PolyA tails present at the end of the sequences are trimmed to ensure accurate mapping and analysis.
  • the filtered and trimmed reads are then mapped to the reference genome using a tool such as STAR9 (Spliced Transcripts Alignment to a Reference).
  • This step involves aligning the sequences from R2 to the genomic sequences to identify their locations and potential splice sites.
  • duplicate reads are identified and removed to eliminate redundant data and ensure accuracy in downstream analysis.
  • This process generates new SAM (Sequence Alignment/Map) files containing the mapped reads with duplicates removed.
  • transcript or gene count matrices are generated for each associated Bead1. This involves counting the number of reads aligned to each gene for every Bead1, providing quantitative information about gene expression levels.
  • the data obtained in the form of bead by gene expression matrices undergo one or more preprocessing steps.
  • At least one dimensionality reduction technique such as principal component analysis (PCA) or non-linear methods like t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) is applied to reduce the high-dimensional gene expression data into lower-dimensional representations. This facilitates the visualization and clustering of cells based on their transcriptional profiles.
  • PCA principal component analysis
  • t-SNE stochastic neighbor embedding
  • UMAP uniform manifold approximation and projection
  • clustering algorithms are utilized to group receiver bead with similar gene expression profiles into clusters. These clusters represent distinct cell populations within the sample. Additionally, cells within each cluster are annotated based on known cell type markers or differential gene expression analysis, providing insights into the identity and heterogeneity of the cell populations. 42
  • each receiver bead location is mapped in a spatial context, providing information about its spatial distribution within the sample.
  • a spatial map is generated from the combination of the receiver:sender bead interaction matrix with the gene expression matrix.
  • the spatial locations of a receiver bead is assigned to a spatial location based on associations with proximal sender beads using the receiver bead:sender bead matrix and all associated RNA sequence (expression) data associated with the receiver bead is also assigned to that position.
  • High resolution maps representing the extent of capture of individual or grouped RNAs/transcripts across the various spatial positions of the arrays can then be generated using the underlying RNA sequence information (which was at least originally bead-associated).
  • Spatial expression maps or images i.e., pixel coloring and/or intensities
  • the spatial expression map can be overlaid on an image of the sample. Images can be obtained using detection devices known in the art. Examples include microscopes configured for light, bright field, dark field, phase contrast, fluorescence, reflection, interference, or confocal imaging. A biological specimen can be stained prior to imaging to provide contrast between different regions or cells. In some embodiments, more than one stain can be used to image different aspects of the specimen (e.g. different regions of a tissue, different cells, specific subcellular components or the like). In other embodiments, a biological specimen can be imaged without staining. [0141] A method set forth herein can include a step of correlating locations in an image of a biological specimen with a spatial expression map generated according to the methods of the invention. Accordingly, characteristics of the biological specimen that are identifiable in the image can be correlated with the nucleic acids that are found to be present in their proximity. Any of a variety of morphological characteristics can be used in such a correlation, including for 43
  • a solid support upon which a biological specimen is imaged can include fiducial markers to facilitate determination of the orientation of the specimen or the image thereof in relation to probes that are attached to the solid support.
  • Exemplary fiducials include, but are not limited to beads (with or without fluorescent moieties or moieties such as nucleic acids to which labeled probes can be bound), fluorescent molecules attached at known or determinable features, or structures that combine morphological shapes with fluorescent moieties. Exemplary fiducials are set forth in US Pat. App. Publ. No.2002/0150909 A1 or U.S. patent application Ser. No. 14/530,299, each of which is incorporated herein by reference. One or more fiducials are preferably visible while obtaining an image of a biological specimen.
  • the solid support includes at least 2, 3, 4, 5, 10, 25, 50, 100 or more fiducial markers.
  • the fiducials can be provided in a pattern, for example, along an outer edge of a solid support or perimeter of a location where a biological specimen resides.
  • one or more fiducials are detected using the same imaging conditions used to visualize a biological specimen. However if desired separate images can be obtained (e.g. one image of the biological specimen and another image of the fiducials) and the images can be aligned to each other.
  • Kits [0143] The instant disclosure also provides kits containing agents of this disclosure for use in the methods of the present disclosure. Kits of the instant disclosure may include one or more containers comprising a plurality of sender beads, a plurality of receiver beads, or a combination thereof of this disclosure.
  • kits further include instructions for use in accordance with the methods of this disclosure.
  • these instructions comprise a description of a protocol for preparing the sender and receiver beads for spatial transcriptomics (e.g., mixing the sender and receiver beads), contacting a sample with a combination of sender and receiver beads, photocleavage of the sender beads and preparaing a sequencing library for spatial transcriptomic analysis.
  • kits of the instant disclosure are typically written instructions on a label or package insert (e.g., a paper sheet included in the kit), but machine- readable instructions (e.g., instructions accessible on a website or using electronic media) are also acceptable.
  • the kits of this disclosure are in suitable packaging. Suitable packaging includes, but is not limited to, vials, bottles, jars, flexible packaging (e.g., sealed Mylar or plastic bags), and the like.
  • Kits may optionally provide additional components such as buffers, tissue fixation reagents, reverse transcription reagents, ligation reagents, polymerase chain reaction reagents, template switching reagents, and sequencing reagents.
  • the kit comprises a container and a label or package insert(s) on or associated with the container.
  • Methods of Use are methods of use of the transcriptional profiles generated using the methods of the invention to determine the transcriptional levels in cell populations in a biological sample and to identify novel biomarkers or transcriptional changes associated with disease or disorders or developmental stages.
  • the level of one or more transcript in a cell population in a biological sample from a specific developmental stage or disease or disorder is determined to be statistically different than the level of the transcript in a cell population in a biological sample in a control sample.
  • the transcriptional profiles generated according to the disclosure can be used to determine the extent, severity, or stage of disease, to determine the right treatment approach (e.g., disease-specific therapy, surgical intervention), to select the appropriate dose for a medical treatment, to determine whether a patient is likely to respond to a particular medical or surgical treatment, to monitor response to treatment, or to monitor disease progression.
  • the method of the invention involves a step of comparing the level of at least one transcript in a cell population in a biological sample obtained from a subject to the level of the transcript in the same cell population in a comparator control (i.e., positive control, negative control, historical norm, baseline level or reference value).
  • a comparator control i.e., positive control, negative control, historical norm, baseline level or reference value
  • population in a comparator control is indicative of a disease or disorder associated with the increased level of the transcript, i.e., it is an indication that said subject is suffering from a disease or disorder associated with the presence of increased level of the transcript or has a predisposition to develop a disease or disorder associated with increased level of the transcript.
  • a decrease in the level of at least one transcript in a cell population in a biological sample from the subject under study relative to the level of the transcript in a cell population in a comparator control sample is indicative of a disease or disorder associated with the decreased level or absence of the transcript, i.e., it is an indication that said subject is suffering from a disease or disorder associated with the decreased level or absence of the transcript or has a predisposition to develop a disease or disorder associated with the decreased level or absence of the transcript.
  • Diagnostic Index [0148]
  • the present invention relates to the identification of a transcriptional profile and optionally one or more additional clinical features to generate diagnostic indexes for diagnosing a disease or disorder or risk of a disease or disorder.
  • the present invention features methods for identifying subjects who have or are at risk of developing a disease or disorder by detection of the transcriptional profile in a tissue sample from the subject and assessing the clinical factors disclosed herein. These factors, or otherwise health profile, are also useful for monitoring subjects undergoing treatments and therapies, and for selecting or modifying therapies and treatments to alternatives that would be efficacious in subjects determined by the methods of the invention to have a disease or disorder associated with the presence or absence of a rare cell population or an increased risk of developing a disease or disorder associated with the presence or absence of a rare cell population.
  • Exemplary diseases or disorders that can be evaluated or diagnosed using the assay system of the invention include, but are not limited to, an autoimmune disease or disorder, an inflammatory disease or disorder, a neurodegenerative disease or disorder, a disease or disorder associated with a pathogen and cancer.
  • Exemplary neurological diseases or disorders that can be evaluated using the assay system of the invention include, but are not limited to, Lewy body dementia, Alzheimer's disease or Alzheimer's Disease Related Dementias (ADRD). 46
  • the present invention provides an index of for use in patient monitoring or diagnostics.
  • the index is calculated as a function of multiple markers, biomarkers or factors that strongly correlate to a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population. These factors may include a combination of clinical factors, transcriptional changes and relative cell population levels.
  • the risk of developing a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population can be assessed by measuring one or more of the factors described herein, and comparing the presence and values of the factors to reference or control values.
  • Subjects identified as having a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population or an increased risk of a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population can optionally be selected to receive counseling, an increased frequency of monitoring, or treatment regimens, or administration of therapeutic compounds.
  • the factors of the present invention can thus be used to generate a health profile or signature of subjects: (i) who do not have and are not expected to develop a specific disease or disorder associated with a transcriptional change or altered cell population and/or (ii) who have or expected to develop a specific disease or disorder associated with a transcriptional change or altered cell population.
  • the health profile of a subject can be compared to a predetermined or reference profile to diagnose or identify subjects at risk for developing a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population, to monitor the response to a therapeutic treatment (e.g. an antibiotic or a chemotherapeutic agent), and to monitor the effectiveness of a treatment or preventative measure for a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population.
  • a therapeutic treatment e.g. an antibiotic or a chemotherapeutic agent
  • Data concerning the factors of the present invention can also be combined or correlated with other data or test results, such as, without limitation, measurements of clinical parameters or other algorithms for a specific disease or disorder associated with the presence or absence of a transcriptional change or altered cell population.
  • the health profile includes at least one additional factor. Exemplary additional factors that can be included in the health profile include, but are not 47
  • a scale can be arbitrarily partitioned into regions having scores such that a correct combination of the scores provides a diagnostic index having a certain degree of confidence.
  • the partitioning can be performed by conventional classification methodology including, but not limited to, histogram analysis, multivariable regression or other typical analysis or classification techniques.
  • Methods for Identifying Biomarkers [0155]
  • the systems and methods disclosed herein may be used in biomarker identification, for example for identifying tumor cells from a sample to diagnose cancer or metastasis or for identifying biomarkers to determine additional information about the prognosis or stage of a diagnosed cancer.
  • the systems and methods described herein may be particularly useful for characterizing cell populations, including, but not limited to rare pathogenic cell populations.
  • the transcriptional profiles generated are useful for diagnosing a disease or disorder in the subject, monitoring the progression of a disease or disorder in the subject, providing a disease prognosis, or evaluating the effects of a treatment provided to a subject.
  • the methods of the invention are used to identify a transcriptional profile associated with an abnormal cell population.
  • the abnormal cell population is associated with a disease or disorder.
  • the abnormal cell population is associated with cancer.
  • the abnormal cell population is associated with a neurological disease or disorder. 48
  • the disclosure provides a method of diagnosing, treating or preventing a disease or disorder associated with an altered level of a cell population.
  • the method comprises administering to the subject an effective amount of a pharmaceutical agent for the treatment of a disease or disorder identified as associated with an altered level of a specific cell population, including, but not limited to, diseases or disorders associated with the inflammatory process, pathogens, and cancers.
  • a pharmaceutical agent for the treatment of a disease or disorder identified as associated with an altered level of a specific cell population including, but not limited to, diseases or disorders associated with the inflammatory process, pathogens, and cancers.
  • Exemplary inflammatory diseases and disorder that can be diagnosed, treated or monitored for treatment include, but are not limited to, autoimmune diseases, inflammatory diseases, neurodegenerative diseases and disorders, diseases and disorders associated with pathogens and cancer.
  • the invention includes using a biomarker or panel of biomarkers as set forth in Table 12-Table 19 for diagnosing a disease or disorder.
  • the invention includes the use of a biomarker or panel of biomarkers as set forth in Table 12-Table 16 for the diagnosis of a disease or disorder associated with aging.
  • the invention includes the use of a biomarker or panel of biomarkers as set forth in Table 17-Table 18 for the diagnosis of a disease or disorder associated with immunodeficiency.
  • Example 1 Spatial Mapping of Mouse Brain Aging through Indexed Sequencing
  • IRIS Imaging Reconstruction using Indexed Sequencing
  • receiver beads that resemble beads array shape designed during the experiment. Dimensionality reduction was performed and clustering of gene expression matrix of RNA captured by receiver beads and then receiver beads were map onto the 2D spatial coordinates generated prior, with their associated gene expression clusters overlayed. With this pipeline, receiver beads gene expression clusters were observed mapping onto the 2D coordinates resembling whole mouse brain tissue architecture and whole mouse brain hemi-section globally reconstructed without any microscopy or equipment for spatial indexing, and solely based on dimensionality reduction analysis of interacting DNA barcodes. Detailed computational protocols are described below. Quality control of IRIS (Imaging Reconstruction using Indexed Sequencing) [0166] IRIS was applied to profile a coronal section of an adult mouse brain.
  • IRIS platform in aging study [0167] To confirm the effectiveness of IRIS in identifying gene expression changes and cellular states associated with aging, it was applied to profile coronal hippocampal sections from both adult and aged mouse brains, including six sections from each group. Following library preparation and sequencing, a differential gene expression analysis was conducted, revealing region-specific changes associated with aging ( Figure 3A). For example, a significant increase in the expression of C4b and Serpina3n was detected in the Subventricular Zone (SVZ) regions of the aged brain ( Figure 3B). This aligns with a previous analysis using 10X Visium (Sziraki et al., 2023, Nat.
  • IRIS interleukin-12
  • Cost-Effectiveness IRIS costs less than $100 per slide, over a ten-fold reduction compared to commercial platforms. This makes it a highly economical choice for large-scale spatial profiling.
  • Scalability Operating independently of specialized equipment, IRIS can process over ns of sections in a single experiment, enhancing scalability and suitability for large- scale settings.
  • Neighborhood Interaction-Based Reconstruction Unlike imaging-based methods, IRIS uses local neighborhood information for spatial mapping. This innovative approach is particularly valuable for mapping cellular interactions in larger tissues (e.g., human brains).
  • IRIS allows for adjustable mapping resolution (5-50 ⁇ m), which is crucial for revealing cellular interactions at different distances and scales, making it a versatile tool for diverse research applications.
  • Example 2 Detailed protocol for IRIS profiling [0169]
  • IRISeq Imaging Reconstruction using Indexed Sequencing
  • IRISeq employs similar principles as those of DNA Hi-C (1) and DNA microscopy (2), decoding the spatial locations of molecules by sequencing their interactions with nearby molecules.
  • the optimized IRISeq protocol comprises several key steps: (i) Bead Fabrication: Two types of oligo-barcoded beads are prepared: 'receiver beads' coated with PolyT sequences to 52
  • the photocleavable linker (iSpPC) is shown in Figure 26.
  • Bead Preparation [0171] Using a microfluidic device, acrylamide-based gel beads were generated with Acrydite modified DNA oligonucleotides (PN1) to serve as an attachment site for split-pool- based barcoding. A previous bead barcoding protocol (Delley et al., 2021, Sci Rep 11, 10857) was followed, with slight modifications.
  • Bead Fabrication 1. Prepare 10 ml of droplet generation oil with 0.6% v/v TEMED. Mix well in a 15 ml reservoir tube. (Note that the oil volume depends on the flow rates used and may require adjustments for different drop makers.) 2. Prepare the following three solutions: Note: PN1 primers are diluted in water. Table 2: Solution 1: Receiver Bead (PolyT) 54
  • Centrifugation and Oil Removal (1) Centrifuge the collection tubes at 100 g for 30 seconds. (2) Use a 200 ⁇ l pipette tip to remove the droplet generation oil from the bottom of the tubes. Repeat this step multiple times to ensure thorough removal. (3) Overlay the beads with 1 ml of TBSET and centrifuge at 3000 g for 30 seconds. (4) Remove any leftover droplet generation oil and the mineral oil overlay, along 56
  • Bead Collection and Washing (1) Place a 30 ⁇ m strainer on a 50 ml falcon tube and combine the beads from all tubes by transferring the bead emulsions to the strainer. (2) Flush the strainer with TBSET until only bead precipitates remain on top. (3) Transfer the strainer with beads precipitate on top to the top of a new tube, and flip over the strainer and flush the beads into the tube with TBSET. [0176] 4. Centrifugation, Resuspension, and Filtering: (1) Centrifuge the tube at 1500 g for 3 minutes. (2) Remove the supernatant and resuspend the pellet with 10 ml of TET. (3) Transfer the bead suspension to a 15 ml tube.
  • Receiver beads oligonucleotide conjugation 1. Take 750 ⁇ l of 1 ml beads for receiver beads conjugation 2. Split receiver beads into two, 5 ml tubes and dilute each down using 3 ml 1X PBS *Below amount is per 5 ml tube 3. Add 400 ⁇ l of 400 uM PN1-Amc6 (200 ⁇ l of 400 uM PN1-Amc6 also works well) 4. Add 40 ⁇ l 25 mM DSS solution for the first 10 minutes 5. Then add another 40 ⁇ l 25 mM DSS 6. Leave on a shaker for 3 hours 7.
  • Beads Barcoding 1. Calculate the volumes required based on the bead volume used (1 ml or 5 ml). Ensure that the PCR plate can hold the total volume. 2. Thaw all barcode plates with the added splints mixed in a 1:1 ratio, for a final concentration of 100 uM when combined with splits. [0183] Phosphorylation of Primers: 1. Prepare the T4 polynucleotide kinase (PNK) master mix for each plate. Table 4: T4 PNK master mix T4 lig buffer 10 1.00 x 600 ⁇ l . ⁇ ll of a PCR plate. 3.
  • PNK polynucleotide kinase
  • Table 5 Bead Resuspension Beads - - - 500 ⁇ l xtra single PN2. 5. Prepare the mixture including beads and T4 ligase buffer.
  • Table 6 Bead Wash Beads - - - 500 ⁇ l 1. Once primer phosphorylation is complete, remove the foil and distribute 20 ⁇ l beads to each well. 2. Store a 5 ⁇ l bead aliquot in a PCR tube, labeled "round 0" for quality control. 3. Prepare the T4 ligase master mix in 5 ml tubes and distribute 40 ⁇ l to each well. Mix by pipetting up and down. Use a multi-channel pipette and a reagent reservoir. Replace tips after each pipette cycle to avoid cross-contamination.
  • Table 7 T4 ligase master mix T4 ligase buffer 10 1 x 420 ⁇ l 4. Seal the plate and incubate at room temperature for 1 hour. Heat-inactivate the 61
  • mice were anesthetized with CO 2 and decapitated. The brain was rapidly dissected, frozen on crushed dry ice, and stored at ⁇ 80 °C until cryosectioning. Upon IRIS profiling, fresh frozen tissue was warmed to -20 C in a cryostat (Leica CM3050S) for 20 minutes before handling. The tissue was then mounted onto a cutting block with OCT and sliced at 10 ⁇ m thickness for RNA capture. [0195] IRIS-seq with the frozen bead array tissue RNA capture (Optimized protocol for both small and large areas profiling): 1. Cut a 0.6 cm x 0.6 cm (or 1.5cm x 1.5cm for large array) square-shaped area in 64
  • a 96-well plate plastic tape Tape the cut area onto a glass slide to define the square shape of the bead layer.
  • 2. Prepare a 15ul mixture of receiver beads and sender beads in a 3:1 ratio in hybridization buffer (Prepare 50 ul 3:1 mixture for 1.5 cm x 1.5 cm array size). Place 5ul bead mixture on the glass slide in the taped square-shaped area, making sure all area is covered with gel beads (Place ⁇ 30 ul of beads mix for 1.5 cm x 1.5 cm array, and add more beads accordingly to fill the square). Add 1 ⁇ l of Proteinase K to the bead mixture. Homogenize the beads using a pipette tip to facilitate the beads to form a monolayer.
  • IRIS-seq with the non-frozen bead array (Developmental version of the protocol for profiling 0.6cm x 0.6cm sections): 1. Cut a 0.6 cm x 0.6 cm (or 1.5cm x 1.5cm for large array) square-shaped area in a 96-well plate plastic tape. Tape the cut area onto a glass slide to define the square shape of the bead layer. 2. Prepare a 15ul mixture of receiver beads and sender beads in a 3:1 ratio in hybridization buffer.
  • the tissue was melted onto the slide by moving the glass slide off the stage and placing a finger on the bottom side of the glass. 5. Very carefully, the slide was removed from the cryostat and placed into a humidity glass slide chamber with liquid at bottom of chamber to keep tissue humid and not dry. 6. The array in the chambered slide with tissue on top was incubated at room temperature for 13 minutes. 7. Photocleavage of the beads array was performed for 2 minutes under UV light using (oYo-Link LED PX Device), an ice chilled metal plate is used to prevent tissue from becoming too dry during photocleaving. 8. A 10x genomic gasket chamber, with a 20 ⁇ m filter between the gasket and the beads array, was placed to stabilize tissue on the beads during reverse transcription.
  • RT reaction buffer (can be prepared in advance without RTase): 120 ⁇ L H 2 O 40 ⁇ L Maxima 5x RT Buffer 20 ⁇ L 10 mM dNTPs 5 ⁇ L RNase Inhibitor (ThermoFisher) 5 ⁇ L 100 uM Template Switch Oligo (TSO) 10 ⁇ L Maxima H- RTase Total volume 200 ⁇ l 2. Add 200 ⁇ l of RT mix to the beads (very gently to avoid bubbles on the filter for hybridization-based RNA capture). Reverse transcription is performed in the tube with beads for IRISeq with the frozen bead array and high resolution, or on the beads array for IRIS-seq with the non-frozen bead array. 3.
  • Tissue Lysis (IRISeq with non-frozen bead array only) 1. Prepare a working solution for tissue digestion by adding proteinase K to the tissue-clearing buffer stock solution at a 1:50 ratio: Working Solution: 196 ⁇ L Tissue lysis buffer 4 ⁇ L Proteinase K enzyme Note: The tissue lysis buffer (without proteinase K) can be made in advance and stored at room temperature for several months. 2. Add 200 ⁇ L of the tissue lysis mix to the beads in each tube, bringing the total volume to 400 ⁇ L. 3. Incubate the mixture at 37°C for 30 minutes. 4. Cut the filter and collect all beads as much as possible into a PCR tube. 67
  • Exonuclease I Treatment 1. Prepare Exonuclease I mix recipe (200 ⁇ L): 20 ⁇ L 10X Exo I Buffer 170 ⁇ L H2O 10 ⁇ L Exo I 2. Pellet and then wash the beads with 10 mM Tris-HCl, pH 7.5. 3. Pellet beads again and resuspend the beads in 200 ⁇ L Exonuclease I mix. Incubate the reaction at 37 °C for 50 minutes. 4. After Exonuclease I treatment is done, pellet the beads and remove supernatant. Wash beads twice with TE-TW. 5.
  • Second Strand Synthesis 1. Prepare second strand synthesis mix per puck: 133 ⁇ L ultrapure water 40 ⁇ L Maxima 5x RT Buffer 20 ⁇ L 10 mM dNTPs 2 ⁇ L 1 mM dN-SMRT oligo 5 ⁇ L Klenow Enzyme Total volume 200 ⁇ L 2. Pellet beads and resuspend the beads in 200 ⁇ L second strand synthesis mix.
  • cDNA Library Amplification 1. Resuspend the beads in 200 ⁇ l the TE-TW buffer and transfer them to new DNA Lo-bind tubes. 2. Repeat the washing step with the TE-TW buffer for three times. 3. Pellet the beads once more. 68
  • Receiver bead-sender bead Connections Library PCR and Gel Extraction 1. Wash the beads with TE-TW twice, then with water, and suspend them in 27 ⁇ L of H2O. 2. Prepare a PCR mix containing: o Beads suspended in 27 ⁇ L of H 2 O o 1.5 ⁇ L of 10 uM Truseq_indexed_P7_Read2 69 o 1.5 ⁇ L of 10 uM P5_Truseq_ Read1 o 30 ⁇ L of NEBnext master mix o Total volume: 60 ⁇ L 3.
  • Tn5 Tagmentation Prepare buffer -Dialysis buffer Recipe: 50 mM Tris-HCl pH 7.5, 800 mM NaCl, 0.2 mM EDTA, 10% glycerol 1.
  • Prepare the Nextera-P7/P5 Tn5 Mix 100 ⁇ L of Tn5 dialysis buffer with 2 ⁇ L of 100 mM DTT. 2.
  • Each bead connection includes unique molecular identifiers (UMIs) which help in identifying and quantifying individual connection molecules.
  • UMIs unique molecular identifiers
  • R1 which contains the barcode for Bead1
  • R2 which contains the barcodes for Read 2.
  • the reads are mapped to a whitelist of barcodes with 1 base pair error, including the UMI sequence.
  • Duplicated reads are then filtered, and a csv file is generated with bead1, UMI, and bead2 barcode, where each line represents a unique molecular connection between bead1 and bead2.
  • Filtering Bead Connections [0209] Filtering is performed to ensure each connection between two beads has a minimum of 10 UMIs, ensuring a sufficient level of data for analysis.
  • Matrix Generation [0210] After filtering, a matrix is generated where each row represents a Bead1 (receiver bead), and each column represents a Bead2 (sender bead). The values in the matrix correspond to the number of UMIs for each Bead1-Bead2 connection.
  • Principal Component Analysis PCA is applied to the matrix to reduce the dimensionality of the data while preserving its variance. Before running PCA, an elbow plot is generated to determine the optimal number of principal components.
  • UMAP Uniform Manifold Approximation and Projection
  • UMAP Coordinates for each Bead1 are extracted, and saved in csv files, and are used for subsequent mapping of Bead1 spatial location.
  • cDNA data processing Initial Data Preparation: [0213] After the sequencing process, the data is obtained in the form of two sets of FASTQ files: R1 and R2.
  • R1 FASTQ files contain the barcode sequences for Bead1 along with their associated Unique Molecular Identifiers (UMIs).
  • UMIs Unique Molecular Identifiers
  • R2 FASTQ files contain the tagmented cDNA sequences.
  • Barcode Mapping and Tagging [0214] The barcode sequences from R1 are mapped to a whitelist of bead barcodes with a tolerance of 1 base pair error.
  • the identified bead barcode is then added as an identifier (ID) for the corresponding sequences in R2.
  • ID identifier
  • Read2 File Generation and PolyA Trimming [0215] New Read2 files are generated where the name of each sequence in R2 contains the corresponding Read1 barcode. Additionally, any PolyA tails present at the end of the sequences are trimmed to ensure accurate mapping and analysis.
  • Read Mapping to Genome [0216] The filtered and trimmed reads are then mapped to the reference genome using a tool such as STAR9 (Spliced Transcripts Alignment to a Reference). This step involves aligning the sequences from R2 to the genomic sequences to identify their locations and potential splice sites.
  • Dimensionality Reduction and Embedding [0220] Dimensionality reduction techniques such as principal component analysis (PCA) or non-linear methods like t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) are applied to reduce the high-dimensional gene expression data into lower-dimensional representations. This facilitates the visualization and clustering of cells based on their transcriptional profiles.
  • PCA principal component analysis
  • t-SNE stochastic neighbor embedding
  • UMAP uniform manifold approximation and projection
  • Clustering and Annotation [0221] Clustering algorithms, such as those implemented in Seurat and Scanpy, are utilized to group beads1 with similar gene expression profiles into clusters. These clusters represent distinct cell populations within the sample.
  • each cluster is annotated based on known cell type markers or differential gene expression analysis, providing insights into the identity and heterogeneity of the cell populations.
  • Spatial Mapping of Bead Types [0222] Utilizing the UMAP spatial coordinates generated earlier from bead1 bead2 interaction matrices, each bead1 location is mapped in a spatial context, providing information about its spatial distribution within the sample.
  • Example 4 Unraveling Lymphocyte-Driven Mechanisms in Mouse Brain Aging with Optics- Free Spatial Genomics 75
  • IRISeq bypasses the need for imaging or pre-indexed arrays, allowing multiple sections to be processed in a single day at significantly reduced costs—approximately $30 per tissue section—without requiring complex equipment. Furthermore, its optics-free design is particularly suited for mapping large tissue areas exceeding 1cm2, which are traditionally limited by imaging speed and the constraints of pre-indexed arrays. Additionally, IRISeq offers adjustable resolution based on bead size (ranging from 5 to 50 ⁇ m), enhancing its flexibility and user-friendliness. These features make IRISeq a versatile and accessible tool for a wide range of applications, from basic research to clinical diagnostics. [0225] Using the IRISeq platform, age-related changes in gene expression and cellular dynamics were explored across twenty-five regions of the mouse brain.
  • IRISeq is a highly optimized platform for spatial transcriptomics, yet there are opportunities for further improvement.
  • the method does not provide isolated single- cell information.
  • nuclei hashing techniques that can extend its capabilities to direct spatial analysis at the single-cell level (Srivatsan et al., 2021, Science 373, 111–117).
  • IRISeq can be integrated with methods to profile proteins (Ben-Chetrit et al., 2023, Nat.
  • IRISeq demonstrates significant potential for detailed mapping of region-specific molecular signatures, cell population dynamics, and local cell-cell interactions across varied and complex biological landscapes. Its capacity to reconstruct images based solely on sequencing local DNA interactions allows for the profiling of tissues without size constraints and across varied resolutions. Looking ahead, the high-throughput, cost-effective nature of IRISeq positions it as a transformative tool for comprehensive spatial mapping of entire organs 77
  • mice C57BL/6 wild-type mice, B6.129S7-Rag1tm1Mom/J and B6.Cg-Prkdcscid/SzJ were acquired from the Jackson Laboratory and the National Institute on Aging colony at Charles River. All mice were housed under standard conditions, with groups matched for sex and age. Mice were socially housed. Brain Nuclei Extraction for EasySci [0230] The samples were processed by EasySci (Sziraki et al., 2023, Nat.
  • nuclei were concentrated by centrifugation at 500g for 5 minutes at 4°C.
  • the nuclei were washed 3 times in nuclei wash buffer (NWB), containing Nuclei buffer (NB, 10 mM Tris-HCl pH 7.5, 10 mM NaCl, 3 mM MgCl2 in RNase-free water) supplemented by 1% of 10% Tween-20 diluted in RNase-free water, 1% recombinant albumin (NEB, #B9200S), and 0.1% SUPERase•InTM RNase Inhibitor.
  • NWB nuclei wash buffer
  • nuclei were aliquoted into 2 cryovials containing 500 ⁇ L of nuclei resuspended in NWB containing 10% dimethyl sulfoxide and stored in slow freezers, cooling at 1°C per minute, at -80C overnight.
  • one aliquot of the nuclei from each sample was rapidly thawed in a 37 °C water bath and centrifuged at 500g for 5 minutes at 4°C. The supernatant was removed, and the nuclei were resuspended in freshly prepared NWB containing 0.005 mg/mL 78
  • DAPI Fluorescence-activated cell sorting
  • the nuclei were diluted to 500 nuclei/uL and distributed into new plates for second-strand synthesis and 1x AMPure XP SPRI purification (Beckman Coulter, #A63882). After elution of the cDNA, tagmentation with Tn5 transposase was performed followed by a 16-cycle PCR reaction. The resulting PCR products were then pooled and purified twice using 0.8X volume of AMPure XP SPRI. The library concentration and fragment size were measured using an Agilent TapeStation, and sequencing was carried out on an Illumina NovaSeq 6000 System with an S4 Flow Cell.
  • PCA Principal Component Analysis
  • UMAP Uniform Manifold Approximation and Projection
  • UMAP coordinates for each receiver bead were saved in CSV files for spatial mapping.
  • UMAP was run on a GPU with increased training epochs (from ⁇ 500 to ⁇ 10,000 or more) to handle the larger data matrix.
  • density-based spatial clustering of applications with noise (DBSCAN) was applied post-UMAP to remove several erroneously mapped beads (Bushra et al., 2024, PeerJ Comput Sci 10, e1921).
  • DBSCAN density-based spatial clustering of applications with noise
  • the first set of fastq files contains the barcode sequences for receiver beads along with their associated UMIs
  • the second set of fastq files contains the tagmented cDNA sequences.
  • the barcode sequences from R1.fastq are mapped to a whitelist of bead barcodes with a tolerance of one base pair error, and the identified bead barcode is added as an identifier for the corresponding sequences in R2.fastq.
  • New Read2 files are then generated, incorporating the corresponding Read1 barcodes in the sequence names, and any PolyA tails present at the end of the sequences are trimmed for accurate mapping and analysis.
  • the filtered and trimmed reads are mapped to the reference genome using STAR (Spliced Transcripts Alignment to a Reference) (Dobin et al., 2013, Bioinformatics 29, 15–21) to align the sequences from R2 to the genomic sequences, identifying their locations and potential splice sites.
  • Duplicate reads are identified and removed post-mapping to eliminate redundant data and ensure accuracy in downstream analysis, resulting in new SAM files containing the mapped reads with duplicates removed.
  • gene count matrices are generated from the processed SAM files for 80
  • the first step includes removing Beads with low UMI counts (Less than 600 for the mouse aging dataset).
  • the second step includes dividing the data set according to the anatomical sections by which tissue sections were cryosectioned. LIGER objects are constructed by first normalizing the number of UMIs 25 . Then 2000 highest variable features are selected for each tissue section, followed by scaling of gene expression features.
  • each anatomical data set with associated individual tissue sections is integrated by LIGER’s non-negative matrix factorization (iNMF) approach, followed by UMAP mapping. Louvain clustering is then performed on the normalized NMF factor loadings. Clusters with low UMI and non-specific gene features were iteratively removed to ensure data quality, followed by LIGER iNMF workflow to recluster and run UMAP again until no low-quality clusters were formed.
  • LIGER non-negative matrix factorization
  • beads within each cluster are annotated by utilizing differential gene expression analysis for each cluster, and associated cluster-specific genes to known cell type and/or brain regions, along with utilizing genes and/or cluster mapping onto spatial anatomical location.
  • Differential Expression Analysis for spatial IRISeq data, and EasySci single-cell RNA sequencing [0240]
  • DE differential expression
  • the likelihood ratio test was employed to identify aging differential expression for specific regions using Monocle2 (Qiu et al., 2017, Nat. Methods 14, 979–982).
  • DE genes were filtered based on the following cutoffs: q- value ⁇ 0.05, with fold change (FC) > 3 between the maximum and second expressed condition, and with transcripts per million (TPM) > 50 in the highest expressed condition.
  • RCTD cell type decomposition
  • IRISeq spatial expression data was integrated with a single-cell transcriptome dataset from an earlier study (Sziraki et al., 2023, Nat. Genet.55, 2104–2116) following parameters suited for ⁇ 50 ⁇ m-sized spots and excluded cell types not present in the microdissected sections.
  • Differential Abundance Analysis To perform cell abundance analysis across different regions, first, RTCD 82
  • maximum-likelihood cell type proportions are binarized by assigning them into one of five categories: values less than 0.05 were categorized as 0, values between 0.05 and 0.2 as 1, values between 0.2 and 0.6 as 2, values between 0.6 and 0.8 as 3, and values greater than 0.8 as 4.
  • This method allowed for transforming continuous proportion data into discrete categories, facilitating subsequent analysis and visualization.
  • a count matrix of receiver bead by cell subtypes is obtained.
  • Raw counts of cell subtypes were converted into normalized counts per million (CPM).
  • CPM normalized counts per million
  • a likelihood-ratio test was used to identify differentially abundant cell subtypes, employing the differentialGeneTest() function of Monocle2 (version 2.28.0) (Qiu et al., 2017, Nat. Methods 14, 979–982).
  • fold change calculations first the cell counts for each cell subtype were normalized relative to the total cell count in each condition. Then these normalized values were compared between case and control conditions, adding a small numerical value (10 ⁇ -6) to reduce noise from very small clusters. To classify a cell subtype as a "significantly changed cell subtype," criteria of a maximum false discovery rate of 1e-5 and a fold change greater than 1.5 between conditions were set.
  • the abundance of aging-associated cell subtypes was quantified in the different annotated brain regions by performing differential abundance tests comparing adult and aged samples. Recognizing that variations in one cell subtype can influence the relative proportions of others, particularly static cell subtypes, this analysis focused on cell subtypes exhibiting significant changes—more than a 1.5 shift in population during aging. This approach is based on the observation that many significantly changed cell clusters correspond to rare cell states and represent a small portion of the global cell population. Consequently, even if these changing cell subtypes have a substantial impact on others, the overall relative proportion shifts are expected to remain within a two-fold range.
  • a new receiver bead by cell-cell interaction matrix was created. This matrix was generated by first filtering out low RTCD likelihood probability values ( ⁇ 0.05) for subtype deconvolutions. Next, a pairwise analysis of cell subtype co-existence on the same bead was conducted. If two cell subtypes had a positive value after filtering out low RTCD likelihood probability values, a count of 1 was added to the corresponding cell-cell interaction column. Using the hypergeometric test the total number of beads within the region (N), the number of beads with a specific cell subtype-subtype interaction (k), the number of beads where colocalization is observed (n), and the number of beads with the other interacting cell subtype (x) were defined.
  • the optimized IRISeq protocol comprises several key steps ( Figure 4A-4B, Figure 5):
  • Photocleavage and oligo capture Beads are evenly distributed on a glass slide. A UV device is then utilized to photocleave oligos from the sender beads, which then diffuse and are captured by the receiver beads, mimicking the capture of tissue mRNA ( Figure 5B). The bead array is then frozen on dry ice to stabilize it.
  • Tissue transfer and mRNA capture Frozen tissue sections are transferred onto this array. The mRNA from the tissue is then captured by the receiver beads through hybridization and tissue digestion processes.
  • Reverse transcription and sequencing post tissue digestion, beads are collected for reverse transcription, second strand synthesis, tagmentation, and PCR, followed by sequencing to obtain transcriptome data and bead connection details.
  • IRISeq protocols are provided in Example 2 to enable cost-efficient spatial transcriptomic mapping of large tissue sections in individual laboratories.
  • the output from IRISeq includes a bead- bead interaction counts matrix, which identifies connections between sender and receiver beads, and a gene expression matrix that details transcripts mapped to each receiver bead ( Figure 4C, left).
  • PCA principal component analysis
  • UMAP Uniform Manifold Approximation and Projection
  • the resulting 2D UMAP coordinates reflect the designed layout of the assay, preserving the positional relationships among the beads ( Figure 4C, middle). Furthermore, dimension reduction and clustering techniques were utilized on the gene expression matrix to annotate each receiver bead based on region-specific gene expression patterns ( Figure 4C, right). This was followed by cell-type-specific deconvolution analysis, integrating single-cell RNA-seq data to map diverse cell types and quantify their spatial interactions.
  • Clustering analyses based on the gene expression profiles of all receiver beads identified 12 transcriptionally distinct brain region clusters, including cortical, caudal putamen, amygdalar, ventricles, white matter, and midbrain regions, validated using region-specific gene markers (Figure 4G, Figure 7B). Further validation was achieved by integrating the IRISeq data with the published 10x Visium spatial transcriptome dataset (Sziraki et al., 2023, Nat. Genet.55, 2104–2116), which showed consistent region-specific gene expression patterns across spatial locations (Figure 7B-7D). The spatial locations of all receiver beads were then mapped based solely on their connection signals with sender beads (Figure 4F).
  • IRISeq maps the spatially barcoded transcriptome without the need for optical imaging.
  • a distinctive feature of IRISeq is its ability to construct the spatial distribution of microbeads based solely on their local interactions, bypassing the need for pre-indexed bead arrays or imaging to decode transcript locations.
  • IRISeq effectively mapped transcriptionally distinct brain regions to their precise spatial locations on the large array ( Figure 4J-4L), which underscores its efficacy in spatial transcriptomics analysis for large tissue areas.
  • Another distinctive feature of IRISeq is its adaptable resolution, achieved by adjusting the size of the beads used in the bead array—an approach similar to other bead-based 86
  • the 5 ⁇ m bead array Similar to the 10 ⁇ m beads, the 5 ⁇ m bead array also enabled detailed mapping of gene expressions (e.g., Ttr in the ventricles; Hpca in the hippocampus; Figure 8F). However, global reconstruction with UMAP 87
  • IRISeq is significantly more affordable than commercial platforms, costing approximately $30 per tissue section (or less than $1 per mm2) ( Figure 4B), compared to over $1,000 per section typically required by other commercial methods (Bressan et al., 2023, Science 381, eabq4964).
  • Scalability the ability to process multiple tissue sections in a large-area array facilitates comparative studies of various conditions and replicates within the same experiment.
  • Optics-free spatial mapping By relying on local neighborhood interactions for spatial reconstruction, IRISeq is particularly well- suited for profiling large tissues without the need for imaging.
  • Adjustable resolution IRISeq offers flexibility to explore gene expression and cellular interactions at different scales by varying bead sizes. This adaptability makes IRISeq a versatile tool suitable for a wide array of research applications.
  • a spatially resolved transcriptome atlas of the mouse brain [0253] With the IRISeq platform, a spatial transcriptome analysis of the brains of adult (4-month) and aged (23-month) wild-type C57BL/6 female mice were conducted, with three replicates per age group (Figure 10A). Twenty-four coronal sections were profiled in total, including one section each for the frontal and middle part of the cortex ("Section 1" and "Section 2"), and two adjacent sections near the dorsal part of the cortex (“Section 3") ( Figure 10A). These sections covered brain areas from the frontal part of the isocortex to the dorsal aspect of the cortex, including the hippocampus, thalamus, hypothalamus, and others.
  • RCTD computes mean gene expression profiles for each cell type from the scRNA-seq dataset and generates a spatial cell type map by representing each spatial transcriptomics pixel as a linear combination of these cell types.
  • the spatial transcriptomics data from IRISeq was integrated with a previously published brain single-cell transcriptome dataset that identified over 300 distinct cell subtypes across different age stages (Sziraki et al., 2023, Nat.
  • genes upregulated across various aged brain regions were significantly enriched in immune response pathways, including the complement pathway (e.g., C4b, C1qa), antigen presentation (e.g., Psmb8, H2-Q7, B2m, H2-K1) and interferon response (e.g., Ifit3, Isg20, lsg15) ( Figure 13B, Figure 14A).
  • the complement pathway e.g., C4b, C1qa
  • antigen presentation e.g., Psmb8, H2-Q7, B2m, H2-K1
  • interferon response e.g., Ifit3, Isg20, lsg15
  • the down-regulated genes are predominantly involved neurogenesis (e.g., Hdac8, Romo1), while the up-regulated genes indicated an increase in immune response and inflammation (e.g., C1qa, C1qb, Ctss, Ifit3), antigen presentation (e.g., B2m, H2-D1) and glial activation (e.g., Serpina3n, Gfap) (Figure 14B, upper panel).
  • immune response and inflammation e.g., C1qa, C1qb, Ctss, Ifit3
  • antigen presentation e.g., B2m, H2-D1
  • glial activation e.g., Serpina3n, Gfap
  • region-specific upregulation includes lymphocyte markers (e.g., Cd24a, Ighm, and Cd52), particularly in the ventricles, white matter, and hypothalamus (Figure 14D).
  • lymphocyte markers e.g., Cd24a, Ighm, and Cd52
  • Sult1c1 associated with detoxification, hormone regulation, and inflammation (Kurogi et al., 2021, Expert Opin. Drug Metab. Toxicol.17, 767– 784)
  • Clec18a known for its roles in metabolic and immune responses (Liao et al., 2023, Microbiol Spectr 11, e0290322), was uniquely upregulated in the aged habenular region.
  • OB neuroblasts (OBN 1-11, marked by Prokr2 and Robo2 (Zeisel et al., 2018, Cell 174, 999–1014.e22; Puverel et al., 2009, J. Comp. Neurol.512, 232–242)) and OB neuronal progenitor cells (OBN 1-17, marked by Mki67 and Egfr (Pastrana et al., 2009, Proc. Natl. Acad. Sci. U. S. A.106, 6387–6392)), both detected primarily in the reconstructed ventricle regions from section 2 ( Figure 16C).
  • microglia subtype MG-9, Apoe+, Csf1+
  • 'DAM' disease-associated microglia
  • OGF-7 reactive oligodendrocyte subtype
  • DAM disease-associated microglia
  • OLIG-7 reactive oligodendrocytes
  • Astrocyte-9 Gfap-high activated astrocytes
  • gene signature analysis of beads within the “DAM niche” shows significantly higher expression of markers for activated astrocytes (e.g., Gfap) and reactive oligodendrocytes (e.g., C4b) compared to non-DAM beads from the same region ( Figure 16H, Figure 17F), underscoring altered cellular interaction and communication networks as key features of brain aging.
  • activated astrocytes e.g., Gfap
  • reactive oligodendrocytes e.g., C4b
  • T cells particularly CD4+ subsets, infiltrate the central nervous system in neurodegenerative diseases like Lewy body dementia and Alzheimer's disease, contributing to neuronal damage. Aligning with these reports, a dramatic increase was observed in lymphocyte markers across different brain regions associated with aging ( Figure 13).
  • lymphocyte knockdown strategy was employed using two immunodeficient mouse genotypes—B6.129S7-Rag1tm1Mom/J and B6.Cg- Prkdcscid/SzJ—which lacks functional or mature lymphocytes (Mombaerts et al., 1992, Cell 68, 869–877; Dorshkind et al., 1984, J. Immunol.132, 1804–1808).
  • IRISeq platform spatial transcriptome analysis was performed on the brains of 23-month-old wild-type and mutant mice (3 replicates per group).
  • lymphocyte depletion significantly reduces this signature, underscoring the role of lymphocytes in interferon activation and suggesting that targeted lymphocyte ablation may help mitigate ventricular inflammation in the aging brain.
  • the transcriptional profiles of single cells isolated from brain sections of aged wild-type and lymphocyte-deficient mice were analyzed using the EasySci platform—an optimized single-cell combinatorial indexing method (Martin et al., 2023, Nat.
  • immune-response genes such as Igkc and Ighm—both key to B-cell receptor assembly—were significantly downregulated in both immune-deficient mutants ( Figure 20E). Their reduced expression indicates impaired B-cell development, aligning with the known roles of Rag1 and Prkdc in V(D)J recombination and DNA repair (Gellert, 2002, Annu Rev Biochem 71, 101–132; Yin et al., 2021, Tumori 107, 483– 488).
  • mutant-specific microglial state was identified characterized by the expression of genes involved in cholesterol biosynthesis (Dhcr7 (Freel et al., 2022, Dis Model Mech 15)) and calcium homeostasis (Tmtc2 (Sunryd et al., 2014, J Biol Chem 289, 16085–16099))( Figure 20H-20I). Although this state has not been reported previously, prior studies have shown that Dhcr7 is expressed in a subset of microglia, with mutations in Dhcr7 driving increased microglial activation and astrocyte reactivity (Freel et al., 2022, Dis Model Mech 15).
  • Glia_Endothelial_rich_region_section1 Tanc2 ⁇ PKRDC ⁇ WT ⁇ 3.1151 ⁇ PKRDC ⁇ Glia_Endothelial_rich_region_section1 ⁇ Tmem179 ⁇ PKRDC ⁇ WT ⁇ 2.9363 ⁇ PKRDC ⁇ Glia_Endothelial_rich_region_section1 ⁇ Lsm6 ⁇ PKRDC ⁇ WT ⁇ 2.3230 ⁇ PKRDC ⁇ Glia_Endothelial_rich_region_section1 ⁇ Nae1 ⁇ PKRDC ⁇ WT ⁇ 2.3068 ⁇ PKRDC ⁇ Glia_Endothelial_rich_region_section1 ⁇ Gnpat ⁇ PKRDC ⁇ WT ⁇ 2.4987 ⁇ PKRDC ⁇ Glia_Endothelial_rich_region_section1 ⁇ Mzt1 ⁇ PKRDC ⁇ WT ⁇ 2.0089 ⁇ PKRDC ⁇ Glia_Endothelial_
  • Olfactory_Striatal_area_Section1 Tmem158 ⁇ PKRDC ⁇ WT ⁇ 2.2847 ⁇ PKRDC ⁇ Olfactory_Striatal_area_Section1 ⁇ Dmkn ⁇ PKRDC ⁇ WT ⁇ 2.4074 ⁇ PKRDC ⁇ Olfactory_Striatal_area_Section1 ⁇ Unc13c ⁇ PKRDC ⁇ WT ⁇ 2.9632 ⁇ PKRDC ⁇ Olfactory_Striatal_area_Section1 ⁇ Gm8292 ⁇ PKRDC ⁇ WT ⁇ 4.7494 ⁇ PKRDC ⁇ Olfactory_Striatal_area_Section1 ⁇ 2010204K13Rik ⁇ PKRDC ⁇ WT ⁇ 2.0178 ⁇ PKRDC ⁇ Olfactory_Striatal_area_Section1 ⁇ Hbb ⁇ bt ⁇ PKRDC ⁇ WT ⁇ 2.1310 ⁇ PKRDC ⁇ Substantia ⁇ Inominata_section2 ⁇ Apba2 ⁇ PKRDC ⁇ WT ⁇ 2.0
  • Glia_Endothelial_rich_region_section1 Rapgef3 ⁇ Rag1 ⁇ WT ⁇ 3.9521 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Ube2v2 ⁇ Rag1 ⁇ WT ⁇ 2.1581 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Trmt2a ⁇ Rag1 ⁇ WT ⁇ 2.5281 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Slc7a4 ⁇ Rag1 ⁇ WT ⁇ 2.4538 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Rcan1 ⁇ Rag1 ⁇ WT ⁇ 2.0842 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Synj1 ⁇ Rag1 ⁇ WT ⁇ 2.0830 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Gpd1 ⁇ Rag1 ⁇ WT ⁇ 2.
  • Glia_Endothelial_rich_region_section1 Upf1 ⁇ Rag1 ⁇ WT ⁇ 2.4018 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Cds2 ⁇ Rag1 ⁇ WT ⁇ 2.0526 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Naa38 ⁇ Rag1 ⁇ WT ⁇ 2.1577 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Ap3b2 ⁇ Rag1 ⁇ WT ⁇ 2.0729 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Manbal ⁇ Rag1 ⁇ WT ⁇ 2.1073 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ B9d2 ⁇ Rag1 ⁇ WT ⁇ 2.0041 ⁇ Rag1 ⁇ Glia_Endothelial_rich_region_section1 ⁇ Crem ⁇ Rag1 ⁇ WT ⁇ 2.7288 ⁇ Rag1 ⁇ Gl
  • Glia_Endothelial_rich_region_section1 Rplp2 ⁇ WT ⁇ PKRDC ⁇ 2.6124 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Crcp ⁇ WT ⁇ PKRDC ⁇ 3.9840 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Arhgef9 ⁇ WT ⁇ PKRDC ⁇ 2.2686 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Gng13 ⁇ WT ⁇ PKRDC ⁇ 2.3138 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Iscu ⁇ WT ⁇ PKRDC ⁇ 11.4045 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Lancl1 ⁇ WT ⁇ PKRDC ⁇ 2.1076 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Igf
  • Glia_Endothelial_rich_region_section1 Ntrk3 ⁇ WT ⁇ PKRDC ⁇ 2.7007 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Fam19a1 ⁇ WT ⁇ PKRDC ⁇ 2.4918 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Ddn ⁇ WT ⁇ PKRDC ⁇ 2.0249 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Jakmip3 ⁇ WT ⁇ PKRDC ⁇ 8.0431 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Tpt1 ⁇ WT ⁇ PKRDC ⁇ 42.0695 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1 ⁇ Ap2a1 ⁇ WT ⁇ PKRDC ⁇ 2.5075 ⁇ WT ⁇ Glia_Endothelial_rich_region_section1
  • Olfactory_Striatal_area_Section1 Fau ⁇ WT ⁇ PKRDC ⁇ 20.1163 ⁇ WT ⁇ Olfactory_Striatal_area_Section1 ⁇ Phb ⁇ WT ⁇ PKRDC ⁇ 3.0189 ⁇ WT ⁇ Olfactory_Striatal_area_Section1 ⁇ Nrn1 ⁇ WT ⁇ PKRDC ⁇ 2.7958 ⁇ WT ⁇ Olfactory_Striatal_area_Section1 ⁇ Tspyl4 ⁇ WT ⁇ PKRDC ⁇ 2.4256 ⁇ WT ⁇ Olfactory_Striatal_area_Section1 ⁇ Mrps28 ⁇ WT ⁇ PKRDC ⁇ 2.0008 ⁇ WT ⁇ Olfactory_Striatal_area_Section1 ⁇ Rabggta ⁇ WT ⁇ PKRDC ⁇ 2.2951 ⁇ WT ⁇ Olfactory_Striatal_area_Section1 ⁇ Dgkz ⁇ WT ⁇ PKRDC ⁇ 3.3996 ⁇ WT ⁇ Olfactory_Striatal_area_Se
  • Thalamus_Reticular_Nucleus_section3 4930453N24Rik ⁇ WT ⁇ Rag1 ⁇ 2.1719 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Brwd1 ⁇ WT ⁇ Rag1 ⁇ 2.1959 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Catsperd ⁇ WT ⁇ Rag1 ⁇ 3.9749 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Jakmip2 ⁇ WT ⁇ Rag1 ⁇ 2.0904 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Rpp30 ⁇ WT ⁇ Rag1 ⁇ 2.0326 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Brcc3 ⁇ WT ⁇ Rag1 ⁇ 2.0106 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Ptprz1 ⁇ WT ⁇ Rag1 ⁇ 2.0599 ⁇ WT ⁇ Thalamus_Reticular_Nucleus_section3 ⁇ Gphn ⁇

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Abstract

La présente invention concerne des compositions permettant de produire une carte transcriptionnelle spatiale d'un échantillon biologique, ainsi que les procédés correspondants, les procédés incluant l'application de billes émettrices et de billes réceptrices fixées à des oligonucléotides sur une surface ou une lame.
PCT/US2025/025375 2024-04-18 2025-04-18 Profilage transcriptionnel à haute résolution spatiale par séquençage indexé Pending WO2025222124A1 (fr)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200063191A1 (en) * 2017-11-15 2020-02-27 10X Genomics, Inc. Functionalized gel beads
US20210371909A1 (en) * 2020-06-02 2021-12-02 Becton, Dickinson And Company Oligonucleotides and beads for 5 prime gene expression assay
US20220326251A1 (en) * 2019-11-08 2022-10-13 10X Genomics, Inc. Spatially-tagged analyte capture agents for analyte multiplexing
US20230002812A1 (en) * 2019-11-13 2023-01-05 10X Genomics, Inc. Generating capture probes for spatial analysis
US20230287476A1 (en) * 2020-07-08 2023-09-14 Illumina, Inc. Beads as Transposome Carriers
WO2024073412A2 (fr) * 2022-09-26 2024-04-04 The Rockefeller University Compositions et procédés de synthèse de banques de séquençage multi-indexées

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200063191A1 (en) * 2017-11-15 2020-02-27 10X Genomics, Inc. Functionalized gel beads
US20220326251A1 (en) * 2019-11-08 2022-10-13 10X Genomics, Inc. Spatially-tagged analyte capture agents for analyte multiplexing
US20230002812A1 (en) * 2019-11-13 2023-01-05 10X Genomics, Inc. Generating capture probes for spatial analysis
US20210371909A1 (en) * 2020-06-02 2021-12-02 Becton, Dickinson And Company Oligonucleotides and beads for 5 prime gene expression assay
US20230287476A1 (en) * 2020-07-08 2023-09-14 Illumina, Inc. Beads as Transposome Carriers
WO2024073412A2 (fr) * 2022-09-26 2024-04-04 The Rockefeller University Compositions et procédés de synthèse de banques de séquençage multi-indexées

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