Marker Selection in Multivariate Genomic Prediction Improves Accuracy of Low Heritability Traits.

ABSTRACT: Multivariate analysis using mixed models allows for the exploration of genetic correlations between traits. Additionally, the transition to a genomic based approach is simplified by substituting classic pedigrees with a marker-based relationship matrix. It also enables the investigation of correlated responses to selection, trait integration and modularity in different kinds of populations. This study investigated a strategy for the construction of a marker-based relationship matrix that prioritized markers using Partial Least Squares. The efficiency of this strategy was found to depend on the correlation structure between investigated traits. In terms of accuracy, we found no benefit of this strategy compared with the all-marker-based multivariate model for the primary trait of diameter a

SUBMITTER: Klapste J 

PROVIDER: S-EPMC7662070 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature