Olivar is a Python software for multiplex PCR tiling design. Olivar first builds an index for each target of interest, incorporating undesired sequence features such as homologous regions, SNPs and extreme GC content. Olivar then designs tiled amplicons covering a single index or multiple indexes, and minimizes primer dimers with the SADDLE algorithm. Olivar is published as an article on Nature Communications.

A web interface is available at olivar.rice.edu, although it does not support all available functions at the moment.

conda create -n olivar olivar --channel conda-forge --channel bioconda --channel defaults --strict-channel-priority

conda activate olivar
olivar --help

python >=3.8
blast >=2.12.0
biopython
numpy <2
pandas
plotly >=5.13.0
tqdm

To reproduce the results in example_output (primers used in the publication), specify package versions during installation and run example.py.

conda create -n olivar olivar=1.1.5 blast=2.13.0 numpy=1 --channel conda-forge --channel bioconda --strict-channel-priority

• (Required) Reference sequence for each target for tiling, in FASTA format (example). Ambiguous bases are not supported and may raise errors.

• (Optional) A list of sequence variations to be avoided for each reference, in csv format (example). Column "START" and "STOP" are required, "FREQ" is considered as 1.0 if empty. Other columns are not required. Coordinates are 1-based.

• (Optional) A BLAST database of non-specific sequences. More details can be found in Prepare a BLAST database.

Olivar CLI comprises of four sub-commands: build, tiling, save and validate. Descriptions of command-line arguments can be found in Command-line parameters.

A reference sequence in FASTA format is required, coordinates of sequence variations and BLAST database are optional. Only the first FASTA record is considered.

olivar build example_input/EPI_ISL_402124.fasta -v example_input/delta_omicron_loc.csv -d example_input/Human/GRCh38_primary -o example_output -p 1

An Olivar reference file (EPI_ISL_402124.olvr) will be generated, named by the ID of the FASTA record by default. Use multiple CPU cores (-p) to accelerate this process.

If you have multiple targets, run olivar build on each FASTA file and place all output .olvr files in the same directory.

In this step, the input reference sequence is chopped into kmers, and GC content, sequence complexity and BLAST hits are calculated for each kmer. Sequence variations are also labeled if coordinates are provided. A risk score is assigned to each nucleotide of the reference sequence, guiding the placement of primer design regions.

Input a single Olivar reference file generated in step 1, or a directory of multiple .olvr files. Set random seed (--seed) to make the results reproducible. Use multiple CPU cores (-p) to accelerate this process. Output files are listed below (coordinates are 1-based).

olivar tiling example_output/EPI_ISL_402124.olvr -o example_output --max-amp-len 420 --min-amp-len 252 --check-var --seed 10 -p 1

"olivar-design" is the name of the whole design (might contain multiple targets), and "EPI_ISL_402124" is the name of a single target, determined by the ID of the reference FASTA record by default (see step 1).

In this step, the placement of primer design regions (PDRs) is optimized based on the risk array (Fig.1d), and primer candidates are generated by SADDLE for each PDR in the optimized PDR set. SADDLE also minimizes primer dimer by exploring different combinations of primer candidates.

Output files in step 2 can be generated repeatedly as long as the Olivar deisng file (.olvd) is provided.

olivar save example_output/olivar-design.olvd -o example_output

Input should be a csv file, with four required columns: "amplicon_id" (amplicon name), "fP" (sequence of forward primer), "rP" (sequence of reverse primer) and "pool" (primer pool number, e.g., 1). This could be an Olivar designed primer pool generated in step 2, or primer pools that are not designed by Olivar. Output files are listed below (coordinates are 1-based). Use multiple CPU cores (-p) to accelerate this process.

olivar validate example_output/olivar-design.csv --pool 1 -d example_input/Human/GRCh38_primary -o example_output -p 1

Olivar can also be imported as a Python package, comprising of four functions with the same names and parameters as the four sub-commands in the CLI.

from olivar import build, tiling, save, validate

Refer to example.py for more details.

olivar build fasta-file [--var <string>] [--db <string>] [--output <string>] 
[--title <string>] [--threads <int>]

olivar tiling olvr-path [--output <string>] [--title <string>] [--max-amp-len <int>] 
[--min-amp-len <int>] [--w-egc <float>] [--w-lc <float>] [--w-ns <float>] [--w-var <float>] 
[--temperature <float>] [--salinity <float>] [--dg-max <float>] [--min-gc <float>] 
[--max-gc <float>] [--min-complexity <float>] [--max-len <int>] [--check-var] 
[--fp-prefix <DNA>] [--rp-prefix <DNA>] [--seed <int>] [--threads <int>]

olivar save olvd-file [--output <string>]

olivar validate csv-file [--pool <int>] [--db <string>] [--output <string>] 
[--title <string>] [--max-amp-len <int>] [--temperature <float>] [--threads <int>]

• To make your own BLAST database with the makeblastdb command, check out the NCBI BLAST User Manual.
  The example BLAST database is created with 23 Chromosomes and MT of human genome assembly GRCh38, with the command (BLAST version 2.12.0):

makeblastdb -in GRCh38_primary.fasta -dbtype nucl -title GRCh38_primary -parse_seqids -hash_index -out GRCh38_primary -max_file_sz 4GB -logfile makeblastdb.out -taxid 9606

• To download a pre-built BLAST database from NCBI (e.g., RefSeq representative gennomes for viruses), use the update_blastdb.pl script:

update_blastdb.pl --decompress ref_viruses_rep_genomes

For more details about update_blastdb.pl, check the BLAST Help.
For more pre-built databases, check the NCBI FTP site.