Whole-genome prediction of reaction norms to environmental stress in bread wheat (Triticum aestivum L.) by genomic random regression

Since drought at flowering explained a fairly large variance in G × E in MET1, the FR-gBLUP model was more accurate than the additive gBLUP across all types of cross validation. Accuracy gains varied from 2.4% to 12.9% for the genomic regression to drought. In MET2 accuracy gains were modest, varying from −5.7% to 2.4%. When a major stress influencing G × E is identified, the FR-gBLUP strategy makes it possible to predict the level of adaptation of genotyped individuals to varying stress intensities, and thus to select them in silico. Our study demonstrates how genome-wide selection can facilitate breeding for adaptation.