Sat-BSA: an NGS-based method using local de novo assembly of long reads for rapid identification of genomic structural variations associated with agronomic traits.

Abstract

Advances in next generation sequencing (NGS)-based methodologies have accelerated the identifications of simple genetic variants such as point mutations and small insertions/deletions (InDels). Structural variants (SVs) including large InDels and rearrangements provide vital sources of genetic diversity for plant breeding. However, their analysis remains a challenge due to their complex nature. Consequently, novel NGS-based approaches are needed to rapidly and accurately identify SVs. Here, we present an NGS-based bulked-segregant analysis (BSA) technique called Sat-BSA (SVs associated with traits) for identifying SVs controlling traits of interest in crops. Sat-BSA targets allele frequencies at all SNP positions to first identify candidate genomic regions associated with a trait, which is then reconstructed by long reads-based local de novo assembly. Finally, the association between SVs, RNA-seq-based gene expression patterns and trait is evaluated for multiple cultivars to narrow down the candidate genes. We applied Sat-BSA to segregating F2 progeny obtained from crosses between turnip cultivars with different tuber colors and successfully isolated two genes harboring SVs that are responsible for tuber phenotypes. The current study demonstrates the utility of Sat-BSA for the identification of SVs associated with traits of interest in species with large and heterozygous genomes.