Prediction of genomic breeding values is of major practical relevance in dairy cattle
breeding. Deterministic equations have been suggested to predict the accuracy of genomic …

This study investigated the accuracy of direct genomic breeding values (DGV) using a
genomic BLUP model, genomic enhanced breeding values (GEBV) using a one-step …

Background The purpose of this work was to study the impact of both the size of genomic
reference populations and the inclusion of a residual polygenic effect on dairy cattle genetic …

The success and sustainability of a breeding program incorporating genomic information is
largely dependent on the accuracy of predictions. For low heritability traits, large training …

The basic idea of cross-validation procedures is to divide a data set into a reference and a
validation set, to omit any kind of information of the validation set and to predict this …

Background Two key findings from genomic selection experiments are 1) the reference
population used must be very large to subsequently predict accurate genomic estimated …

Various models have been used for genomic prediction. Bayesian variable selection models
often predict more accurate genomic breeding values than genomic BLUP (GBLUP), but …

Genomic prediction is widely used to select candidates for breeding. Size and composition
of the reference population are important factors influencing prediction accuracy. In Holstein …

Background Currently, genomic prediction in cattle is largely based on panels of about 54k
single nucleotide polymorphisms (SNPs). However with the decreasing costs of and current …

The objectives of this study were to investigate bias in genomic predictions for dairy cattle
and to find a practical approach to reduce the bias. The simulated data included …