title: Genomic best linear unbiased prediction (gBLUP) for the estimation of genomic breeding values.
abstract: Genomic best linear unbiased prediction (gBLUP) is a method that utilizes genomic relationships to estimate the genetic merit of an individual. For this purpose, a genomic relationship matrix is used, estimated from DNA marker information. The matrix defines the covariance between individuals based on observed similarity at the genomic level, rather than on expected similarity based on pedigree, so that more accurate predictions of merit can be made. gBLUP has been used for the prediction of merit in livestock breeding, may also have some applications to the prediction of disease risk, and is also useful in the estimation of variance components and genomic heritabilities.
authors.affiliation: School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.
authors.forename: Samuel A
authors.initials: SA
authors.lastname: Clark
authors.forename: Julius
authors.initials: J
authors.lastname: van der Werf
mesh_terms: D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D001947:Breeding; D016678:Genome; D055106:Genome-Wide Association Study; D016014:Linear Models; D008957:Models, Genetic; D010375:Pedigree; D010944:Plants / Q000235:genetics*; D019655:Quantitative Trait, Heritable