Genomic Selection in Multi-environment Crop Trials.

ABSTRACT: Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and n

SUBMITTER: Oakey H 

PROVIDER: S-EPMC4856083 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature