Genomic selection using random regressions on known and latent environmental covariates.

ABSTRACT:

Key message

The integration of known and latent environmental covariates within a single-stage genomic selection approach provides breeders with an informative and practical framework to utilise genotype by environment interaction for prediction into current and future environments. This paper develops a single-stage genomic selection approach which integrates known and latent environmental covariates within a special factor analytic framework. The factor analytic linear mixed model of Smith et al. (2001) is an effective method for analysing multi-environment trial (MET) datasets, but has limited practicality since the underlying factors are latent so the modelled genotype by environment interaction (GEI) is observable, rather than predictable. The advantage of using random regress

SUBMITTER: Tolhurst DJ 

PROVIDER: S-EPMC9519718 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature