Genomic selection models based on integration of GWAS loci and epistatic interactions

The potential to integrate consistent associations identified from GWAS as fixed variables in GP models to improve prediction accuracy for complex traits (for example, grain yield) has not been investigated comprehensively in wheat. Here, we untangled the genetic architecture of grain yield and yield stability by haplotypes-based GWAS and epistatic scan of the genome. We then integrated robust and stable associations (and interacting loci) as fixed effects in GP models to investigate the importance of these associations in improving prediction accuracies of the said traits. We concluded that the utility of GP incorporating GWAS results is noteworthy for GY when GWAS results identify significant and robust genomic regions.