Genome-wide association study of Barley Yellow Dwarf Virus resistance in a Nested Association Mapping population of winter wheat using Skim Exome Capture and Practical Haplotype Graph imputation

Abstract

Barley Yellow Dwarf Virus (BYDV) is a major constraint to wheat (Triticum aestivum L.) production, causing severe yield losses due to stunted growth, chlorosis, and reduced kernel weight. While chemical and cultural control strategies offer limited effectiveness, genetic resistance remains the most sustainable approach. In this study, a genome-wide association study (GWAS) was conducted to identify loci associated with BYDV resistance in a Nested Association Mapping (NAM) population of winter wheat derived from ‘Overland’. Phenotypic evaluations were conducted under natural BYDV infection, assessing disease severity, chlorophyll content, plant height, and flowering date. To characterize genetic variation, exome capture sequencing was performed on the parental lines, while skim exome capture sequencing coupled with Practical Haplotype Graph (PHG)-based imputation was used for high-density genotyping of the recombinant inbred lines (RILs). A GWAS approach was employed using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) and Multi-Locus Mixed Model (MLMM). Significant quantitative trait loci (QTL) were detected on chromosomes 5B, 6A, 7B, and 7D, with BLINK identifying stronger associations for BYDV severity and MLMM capturing additional loci for flowering date. A subset of significant markers was tested for validation through Kompetitive Allele-Specific PCR (KASP) assays. Despite strong marker-trait associations in the discovery population, validation in an independent field trial did not replicate all associations, highlighting the complexity of trait expression and the importance of conducting evaluations across diverse conditions and seasons to ensure robustness of results. These findings provide novel insights into the genetic architecture of BYDV resistance in winter wheat and highlight the value of integrating exome capture sequencing and PHG-based imputation for association mapping in polyploid crops.