SNiPlay

SNiPlay performs analysis of polyploid genomic data to detect SNPs, reconstruct haplotypes, assess diversity and linkage disequilibrium, and infer phylogenetic and network relationships using RAD sequencing data for evolutionary genomics studies.

Key Features:

• Polyploid-specific analysis: Handles loci with more than two alleles to address genomic complexity arising from events such as allopolyploidy.
• SNP detection and haplotype reconstruction: Performs SNP calling and reconstructs haplotypes from short-read RAD sequencing data.
• Diversity and linkage disequilibrium assessment: Computes measures of genetic diversity and evaluates linkage disequilibrium across loci.
• RAD sequencing integration: Processes concatenated RAD loci as references and scales to large datasets (e.g., 23,393 loci and 320,010 SNPs in a Salix case study).
• Phylogenetic and network approaches: Applies phylogenetic and network methods to resolve species relationships (demonstrated on 35 Eurasian shrub willow species).
• Genome composition analysis: Compares polyploid genomes with putative parental species to identify signatures of hybrid origin, backcrossing, and secondary evolution post-polyploidization.
• Integration with established tools: Incorporates analyses using RAxML, STRUCTURE, SplitsTree, SNAPP, and HyDe alongside the core pipeline components.
• Input data: Accepts preprocessed short-read datasets from diploid or polyploid accessions for downstream analyses.

Scientific Applications:

• Evolutionary research: Infers evolutionary processes and speciation events in polyploid taxa using RAD-derived SNP data.
• Genomic diversity studies: Characterizes genetic diversity within and between polyploid species to inform conservation genetics and breeding programs.
• Hybridization analysis: Identifies hybrid origins and assesses the extent of backcrossing and secondary evolution following polyploidization.

Methodology:

Processes preprocessed short-read datasets from diploid or polyploid accessions and uses concatenated RAD loci as references to analyze SNP composition and genetic structure.