dbprime is a Python toolkit for primer design, and selection of molecular markers (SNPs / InDels) with a focus on maize breeding and comparative genomics.

• Fast (built on minimap2, samtools, Primer3)
• Flexible (pairwise or multi-sample analysis)
• Breeder-friendly (outputs primer-ready marker candidates)
• Reproducible (Conda/Bioconda environment provided)

What dbprime Does

Given one reference genome/assembly and one or more query assemblies or FASTA/FASTQ files, dbprime will:

. Align query sequences to the reference (via minimap) . Detect SNPs and InDels (with emphasis on InDels) . Extract flanking sequences around each variant . Design PCR primers flanking each candidate marker (via Primer) . Output structured results for downstream genotyping or breeding pipelines

Typical applications:

• Maize cultivar comparison
• Marker-assisted selection (MAS)
• Population genotyping
• Comparative genomics

Repository Structure

dbprime/
├── dbprime.py               Main CLI entry point
├── primer_design.py         Core logic (alignment, indel calling, primer design)
├── examples/
│   └── dbprime/             Example input/output data
├── env.yaml                 Bioconda environment definition
├── README.md                This file

Installation

You have two options: recommended Bioconda/Conda installation, or with pip.

Option : Recommended (Bioconda / Conda)

This ensures all compiled bioinformatics tools work correctly.

. Create environment

conda env create -f env.yaml
conda activate dbprime

. Environment definition (env.yaml)

name: dbprime
channels:
  - conda-forge
  - bioconda
  - defaults

dependencies:
  - python=.

   #alignment tools
  - minimap
  - samtools
  - seqtk

   #python libraries
  - biopython
  - pysam
  - pandas
  - primer-py

  - pip:
      - tqdm
      - rich

Option : pip (Not recommended, but possible)

You must install system binaries manually first:

• minimap2
• samtools
• primer3

Then:

pip install biopython pysam pandas primer-py tqdm rich

This may fail on some systems due to compiled dependencies.

Usage

The main entry point is dbprime.py.

Pairwise comparison (two samples)

python dbprime.py pair \
  -q query.fasta \
  -r reference.fasta \
  -o results_pair/ \
  -l  \
  -f  \
  -s   \
  -p  \
  -t  \
  -d

Multi-sample comparison (population mode)

python dbprime.py multi \
  -q queries_dir/ \
  -r reference.fasta \
  -o results_population/ \
  -l  \
  -f  \
  -s   \
  -p  \
  -t  \
  -d

Command-line Arguments

Common arguments

Outputs

Each run produces:

• indel_candidates.tsv – tabular list of markers
• indel_candidates.json – full structured metadata
• Primer sequences (LEFT / RIGHT)
• Coordinates relative to reference genome

These outputs are directly usable for:

• PCR validation
• Marker-assisted breeding
• Database ingestion

Maize Breeding Context

dbprime was designed with plant breeding workflows in mind:

• Works with draft or polished assemblies
• Handles cultivar-to-cultivar comparisons
• Supports population-level marker discovery
• Produces primer-ready outputs for wet-lab validation