Abstract
The advent of next-generation sequencing (NGS) has revolutionized the study of single nucleotide polymorphisms (SNPs), making it increasingly cost-effective. Haplotypes, which combine alleles from adjacent variants, offer several advantages over bi-allelic SNPs, including enhanced information content, reduced dimensionality, and improved statistical power in genomic studies. These benefits are particularly significant for polyploid species, where distinguishing all homologous copies using SNP markers alone can be challenging. This article introduces HaploCharmer, a flexible workflow designed for read-scale haplotype calling from NGS data. HaploCharmer identifies haplotypes within preconfigured genomic regions smaller than a sequencing read, ensuring direct comparability across individuals. It integrates a series of processing steps including mapping, haplotype identification, filtration, and reporting of haplotype sequences, as presence-absence, in the panel of accessions analyzed. The performance of HaploCharmer was validated by building a genetic map using whole-genome sequencing data from a highly polyploid sugarcane cultivar (R570) and its self-progeny, and performing a diversity analysis in the polyploid Saccharum genus using targeted sequencing data. The workflow successfully identified a large number of high-quality haplotypes, with less than 1% of false positives. The dense genetic map obtained using single-dose haplotypes accurately depicted the known genome architecture of the R570 cultivar, including large chromosome rearrangements. The diversity analysis accurately reflected the known genetic structure within this genus. It also allowed inferring ancestral origins to mapped haplotypes and the corresponding chromosome segments in the R570 genetic map. HaploCharmer provides a robust method for diversity, genetic mapping, and quantitative genetics studies in both diploid and polyploid species.