Genomewide association and prediction of phenotypic stability in barley

Climate change threatens crop production through an increase in the occurrence of extreme abiotic stress. Breeding and growing crop cultivars that are more tolerant of these stresses may be accomplished by selecting for phenotypic stability (opposite of plasticity), which may be aided by understanding the genetic architecture and marker-based predictive ability of plasticity. Using data from a multi-environment experiment in barley (Hordeum vulgare L.), our objectives were to (1) identify genomic regions associated with the mean per se and linear plasticity for five agronomic and malting quality traits, (2) determine the genomewide prediction accuracy of plasticity, and (3) assess the impact of subsampling environments on estimates and predictions of plasticity. We calculated trait genotype means and linear plasticity (slope) for 233 lines (both founders and offspring) grown in 42 environments. We identified 87 marker-trait associations and nearly all significant single nucleotide polymorphisms for the slope overlapped with previously discovered mean per se QTL for the same trait. Genomewide prediction accuracy of slope was moderate as measured using cross-validation (r_MP = 0.32-0.69) and when predicting the slope of an unobserved offspring test population (r_MP = 0.26-0.61). Increasing the number of sampled environments from which to use phenotypic data led to more precise estimates of the slope, greater rates of marker-trait association discovery, and greater genomewide prediction accuracy; however, a modest number of environments was sufficient for obtaining accurate predictions. Our results suggest more shared genetic control of the plasticity and mean per se of traits, but genomewide prediction may be used to select for plasticity without resource-intensive multi-environment trials.