Abstract
Genomic regions that control traits of interest can be rapidly identified using BSA-Seq, a technology in which next-generation sequencing (NGS) is applied to bulked segregant analysis (BSA). We recently developed the significant structural variant method for BSA-Seq data analysis that exhibits higher detection power than standard BSA-Seq analysis methods. Our original algorithm was developed to analyze BSA-Seq data in which genome sequences of one parent served as the reference sequences in genotype calling, and thus required the availability of high-quality assembled parental genome sequences. Here we modified the original script to effectively detect the genomic region-trait associations using only bulk genome sequences. We analyzed two public BSA-Seq datasets using our modified method and the standard allele frequency and G-statistic methods with and without the aid of the parental genome sequences. Our results demonstrate that the genomic region(s) associated with the trait of interest could be reliably identified via the significant structural variant method without using the parental genome sequences.
Next-generation sequencing from bulked segregant analysis identifies a dwarfism gene in watermelon
