DeepVariant calling provides insights into race diversity and its implication for sorghum breeding

Abstract

AbstractDue to evolutionary divergence, sorghum race populations exhibit vast genetic and morphological variations. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all sorghum race accessions and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand the sorghum race structure, diversity and domestication, deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and SNP markers assist in plant breeding programs.