Genetic Mapping in Autohexaploid Sweet Potato with Low-coverage NGS-based Genotyping Data

Abstract

Next-generation sequencing (NGS)-based genotyping methods can generate numerous genetic markers in a single experiment and have contributed to plant genetic mapping. However, the benefits of NGS-based methods are limited in autopolyploids as their genetic segregation mode is complex. Moreover, autopolyploids have large genomes and require abundant sequencing data to obtain sufficient genetic markers. There are several methods for genetic mapping in autopolyploids. These approaches may be impractical for plant genetic studies as they require large amounts of data and are not cost-effective. In the present study, we propose a simple strategy for genetic mapping of polyploids in a cost-effective manner. The allele dosage probabilities calculated from NGS read counts were used in association analyses to detect loci associated with specific phenotypes. This approach is superior to conventional methods of determining allele dosage, which usually result in the filtering of many genetic markers with low read depth. The validity of the strategy was demonstrated using real phenotype data from autohexaploid sweet potato populations to detect genetic loci for both qualitative and quantitative traits, the latter of which required the use of allele dosage probabilities for the detection of loci. We demonstrate that this proposed method is useful with reasonable NGS read counts.