W140 Current Status of Genomic Selection in US Beef Cattle

Date: Saturday, January 14, 2012
Time: 2:10 PM
Room: Pacific Salon 3
Jeremy Taylor , Division of Animal Sciences, University of Missouri, Columbia, MO
Robert Schnabel , University of Missouri - Columbia, Columbia, MO
Mahdi Saatchi , Iowa State University, Ames, IA
Dorian J. Garrick , Iowa State University, Ames, IA
US Feed Efficiency Consortium , http://www.beefefficiency.org/
US Bovine Respiratory Disease CAP Consortium , http://www.brdcomplex.org/
The accuracy of direct genomic values (DGV) depends on the amount of information (number of individuals with phenotypes or deregressed EPDs and trait heritability or accuracy of deregressed EPDs) available on individuals in the training population and the genetic relatedness between individuals in the implementation and training populations. Consequently, the optimum strategy for the implementation of genomic selection is a dynamic training population in which selection candidates have parents in the training population and following selection and capture of progeny phenotypes, selected individuals are used to retrain prior to the next round of selection. This design fits perfectly the US dairy industry but not the beef industry where numerous breeds are employed and many important phenotypes are not routinely captured (meat tenderness, feed efficiency, disease resistance). Furthermore, the need to develop across-breed DGV suggests that more expensive, higher density assays are required to capture linkage disequilibrium between markers and QTLs in multi-breed training populations. Recent work suggests that the BOS 1 (640K) and BovineHD (778K) assays do little to increase the accuracy of DGV obtained from multibreed training populations and that the BovineLD (9K) assay can be used for the imputation of BovineSNP50 (50K) genotypes. This development should alleviate the test cost impediment to the adoption of genomic selection in the beef industry, however, periodic retraining will be required to mitigate the loss of DGV accuracies. Future efforts must focus on the identification of causal mutations underlying QTL and a strategy to accomplish this will be discussed.