Genetic evaluations in cattle using the single-step genomic best linear unbiased predicto (2020)
Conventional genetic evaluations have been framed on estimated breeding values from equation systems of mixed models that consider simultaneously random and fixed effects. Recently, the development in genome sequencing technologies has allowed obtaining genomic information to include in genetic evaluations in order to increase the accuracy and genetic progress, and decrease the generation interval. The single-step best linear unbiased predictor is a methodology developed in the last years and accepts including genomic information replacing the genomic relationship matrix by a matrix that combines relationship by pedigree, and the genomic relationship of a genotyped population, allowing the estimation of breeding values for non-genotyped animals. The aim of this review article was to describe the methodology and its recent progress, as well as to know some of the strategies that could be used when the number of genotyped animals is low