Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel.

ABSTRACT:

Key message

The optimization of training populations and the use of diagnostic markers as fixed effects increase the predictive ability of genomic prediction models in a cooperative wheat breeding panel. Plant breeding programs often have access to a large amount of historical data that is highly unbalanced, particularly across years. This study examined approaches to utilize these data sets as training populations to integrate genomic selection into existing pipelines. We used cross-validation to evaluate predictive ability in an unbalanced data set of 467 winter wheat (Triticum aestivum L.) genotypes evaluated in the Gulf Atlantic Wheat Nursery from 2008 to 2016. We evaluated the impact of different training population sizes and training population selection methods (Random, Clus

SUBMITTER: Sarinelli JM 

PROVIDER: S-EPMC6449317 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature