Integrating a growth degree-days based reaction norm methodology and multi-trait modeling for genomic prediction in wheat.

ABSTRACT: Multi-trait and multi-environment analyses can improve genomic prediction by exploiting between-trait correlations and genotype-by-environment interactions. In the context of reaction norm models, genotype-by-environment interactions can be described as functions of high-dimensional sets of markers and environmental covariates. However, comprehensive multi-trait reaction norm models accounting for marker × environmental covariates interactions are lacking. In this article, we propose to extend a reaction norm model incorporating genotype-by-environment interactions through (co)variance structures of markers and environmental covariates to a multi-trait reaction norm case. To do that, we propose a novel methodology for characterizing the environment at different growth stages based on growt

SUBMITTER: Raffo MA 

PROVIDER: S-EPMC9481302 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature