Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.
Bottom Line: We compared the M×E model with a stratified (i.e., within-environment) analysis and with a standard (across-environment) GS model that assumes that effects are constant across environments (i.e., ignoring G×E).The M×E model decomposes marker effects and genomic values into components that are stable across environments (main effects) and others that are environment-specific (interactions).Therefore, in principle, the interaction model could shed light over which variants have effects that are stable across environments and which ones are responsible for G×E.
Affiliation: Department of Plant, Soil and Microbial Sciences, Michigan State University (MSU), East Lansing, Michigan 4882.Show MeSH
Related in: MedlinePlus
Mentions: Figure 1 shows box-plots of adjusted yield per data set and environmental condition. As expected, average yield increased with the number of irrigation events and, other factors being equal, late planting (H) produced lower yields than normal planting (N). In all cases, the empirical distribution of grain yield within data set and environment was reasonably symmetric.
Affiliation: Department of Plant, Soil and Microbial Sciences, Michigan State University (MSU), East Lansing, Michigan 4882.