Title: Improving genomic prediction for Danish Jersey using a joint Danish-US reference population Authors
Submitted to: World Congress of Genetics Applied in Livestock Production
Publication Type: Proceedings
Publication Acceptance Date: April 21, 2014
Publication Date: August 17, 2014
Citation: Guosheng, S., Nielsen, U.S., Wiggans, G.R., Aamand, G.P., Guldbrandtsen, B., Lund, M.S. 2014. Improving genomic prediction for Danish Jersey using a joint Danish-US reference population. World Congress of Genetics Applied in Livestock Production. Vancouver, Canada, Aug. 17–22. 3 pp. Technical Abstract: Accuracy of genomic prediction depends on the information in the reference population. Achieving an adequate sized reference population is a challenge for genomic prediction in small cattle populations. One way to increase the size of reference population is to combine reference data from different populations. The objective of this study was to assess the gain of genomic prediction accuracy when including US Jersey bulls in the Danish Jersey reference population. The data included 1,262 Danish progeny-tested bulls and 1,157 US progeny-tested bulls. Genomic breeding values (GEBV) were predicted using a GBLUP model from the Danish reference population and the joint Danish-US reference population. The traits in the analysis were milk yield, fat yield, protein yield, fertility, mastitis, longevity, body conformation, feet & legs, and longevity. Eight of the nine traits benefitted from the inclusion of US Jersey bulls in the reference population. The gains ranged from 1.6% points for fertility to 12.5% points for udder conformation. The exception was longevity for which the joint reference population resulted in a loss of 5.5% points in reliability of GEBV. Averaged over all nine traits, reliability of GEBV using the joint reference population was 4.0% points higher than the reliability of GEBV using the Danish reference population alone. The results confirm that exchanging reference data to increase the size of reference population is an efficient approach to increase the accuracy of genomic prediction, especially for the population with small number of reference bulls.