Background Mathematical models are needed for the design of breeding programs using
genomic prediction. While deterministic models for selection on pedigree-based estimates of …

The genomic prediction of phenotypes and breeding values in animals and plants has
developed rapidly into its own research field. Results of genomic prediction studies are often …

Reference populations for genomic selection usually involve selected individuals, which
may result in biased prediction of estimated genomic breeding values (GEBV). In a …

Key message A practical approach is developed to determine a cost-effective optimal
training set for selective phenotyping in a genomic prediction study. An R function is …

Background The theory of genomic selection is based on the prediction of the effects of
genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic …

Genomic selection describes a selection strategy based on genomic estimated breeding
values (GEBV) predicted from dense genetic markers such as single nucleotide …

Background Single-step genomic best linear unbiased prediction (ssGBLUP) models allow
the combination of genomic, pedigree, and phenotypic data into a single model, which is …

Partial least square regression (PLSR) and principal component regression (PCR) are
methods designed for situations where the number of predictors is larger than the number of …

Genomic selection uses genome-wide dense SNP marker genotyping for the prediction of
genetic values, and consists of two steps:(1) estimation of SNP effects, and (2) prediction of …

Background The use of genomic selection in breeding programs may increase the rate of
genetic improvement, reduce the generation time, and provide higher accuracy of estimated …