Optimizing design to estimate genetic correlations between environments with common environmental effects.

ABSTRACT: Breeding programs for different species aim to improve performance by testing members of full-sib (FS) and half-sib (HS) families in different environments. When genotypes respond differently to changes in the environment, this is defined as genotype by environment (G × E) interaction. The presence of common environmental effects within families generates covariance between siblings, and these effects should be taken into account when estimating a genetic correlation. Therefore, an optimal design should be established to accurately estimate the genetic correlation between environments in the presence of common environmental effects. We used stochastic simulation to find the optimal population structure using a combination of FS and HS groups with different levels of common environmental ef

SUBMITTER: Lozano-Jaramillo M 

PROVIDER: S-EPMC7039408 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature