Genomic models for accurate estimation of breeding values in Sitka spruce (Picea sitchensis Bong. Carr).

Abstract

Genomics is advancing estimation of breeding values for selective breeding. Traditional pedigree information used in the estimation of breeding values can still be competitive to genomic information when markers do not adequately capture genetic variance or genomic datasets are not sufficiently large. Using the UK Sitka spruce breeding population as a study system, we assessed the accuracy of estimated breeding values using pedigree or genomic information. Nine phenotypic traits associated with growth and wood quality were measured across 1295 individuals in 50 full-sib families replicated across two plantation sites. Pedigree-based estimation was compared to genome-based estimation using identity by state (IBS) or identity by descent (IBD) information from 4123 SNPs. Accuracy of estimated breeding values was assessed using model-based standard errors, which assumes the fitted model and parameters are correct, and more objective 12-fold cross-validation by withholding some phenotypes from the model fitting. Accuracies obtained directly from the model were very similar across different types of information, but cross-validation showed genomic information gave highest accuracies for all but one of the traits. No bias was observed for any of the trait- information combinations. Results demonstrate that the estimation of breeding values with genomic information in this study system is already competitive with the pedigree information, despite evidence that the marker panel did not capture the full genetic variance. Furthermore, accuracies with genomic information have the potential to significantly improve, unlike pedigree, by increasing the size of the training set and marker density.