Submitted to: Journal of Dairy Science
Publication Type: Abstract Only
Publication Acceptance Date: 3/10/2019
Publication Date: 6/23/2019
Citation: Van Raden, P.M. 2019. How to implement genomic selection. Journal of Dairy Science. 102(Suppl. 1):98(abstr. 66).
Technical Abstract: Key features of genomic selection remain essential, and new features continue to be added 10 years after first being implemented. Breeding values with higher reliability earlier in life are estimated by combining DNA genotypes for many thousands of loci using existing identification, pedigree, and phenotype databases for millions of animals. Quality control for both new and previous data greatly improves by comparing genomic and pedigree relationships to fix parent-progeny conflicts and discover many additional ancestors. Many quantitative trait loci and gene tests have been added to previous assays that used only evenly spaced, highly polymorphic markers. Imputation now combines genotypes from many assays of differing marker density. Prediction models have gradually advanced from normal or Bayesian distributions within breed and trait to single-step, multitrait, multibreed, or other more complex models. Genomic selection was initially applied to males to predict progeny performance but now is widely applied to females or even embryos to predict their own later performance. The initial focus on additive merit has expanded to include mating programs, genomic inbreeding, and recessive alleles. Many producers now use DNA testing to decide which heifers should be inseminated with elite dairy, beef, or gender-sorted semen; be embryo donors or recipients; or be sold or kept for breeding. Because some of these decisions are expensive to delay, predictions are now provided weekly instead of every few months. International genomic databases and predictions are often more accurate than within-country genetic evaluations previously designed for progeny testing. Obtaining predictions from an international database is usually more effective than computing predictions from only local data unless local breeds, conditions, or traits differ greatly from the large database. Selection indexes include many new traits, often with lower heritability or requiring large initial investments to obtain phenotypes, which provide further incentive to cooperate internationally. The genomic prediction methods developed for dairy cattle are now applied widely to many other animal, human, and plant populations.