Abstract
Read mapping is a fundamental part of next-generation genomic research but is complicated by genome duplication in many plants. Categorizing DNA sequence reads into their respective genomes enables current methods to analyze polyploid genomes as if they were diploid. We present PolyCat-a pipeline for mapping and categorizing all types of next-generation sequence data produced from allopolyploid organisms. PolyCat uses GSNAP's single-nucleotide polymorphism (SNP)-tolerant mapping to minimize the mapping efficiency bias caused by SNPs between genomes. PolyCat then uses SNPs between genomes to categorize reads according to their respective genomes. Bisulfite-treated reads have a significant reduction in nucleotide complexity because nucleotide conversion events are confounded with transition substitutions. PolyCat includes special provisions to properly handle bisulfite-treated data. We demonstrate the functionality of PolyCat on allotetraploid cotton, Gossypium hirsutum, and create a functional SNP index for efficiently mapping sequence reads to the D-genome sequence of G. raimondii. PolyCat is appropriate for all allopolyploids and all types of next-generation genome analysis, including differential expression (RNA sequencing), differential methylation (bisulfite sequencing), differential DNA-protein binding (chromatin immunoprecipitation sequencing), and population diversity.