Invited review: genomic selection in dairy cattle: progress and challenges

Hayes, B. J., Bowman, P. J., Chamberlain, A. J. and Goddard, M. E. (2009) Invited review: genomic selection in dairy cattle: progress and challenges. Journal of Dairy Science, 92 2: 433-443. doi:10.3168/jds.2008-1646

Author Hayes, B. J.
Bowman, P. J.
Chamberlain, A. J.
Goddard, M. E.
Title Invited review: genomic selection in dairy cattle: progress and challenges
Journal name Journal of Dairy Science   Check publisher's open access policy
ISSN 0022-0302
Publication date 2009-02
Sub-type Critical review of research, literature review, critical commentary
DOI 10.3168/jds.2008-1646
Open Access Status Not yet assessed
Volume 92
Issue 2
Start page 433
End page 443
Total pages 11
Place of publication New York, NY, United States
Publisher Elsevier
Language eng
Abstract A new technology called genomic selection is revolutionizing dairy cattle breeding. Genomic selection refers to selection decisions based on genomic breeding values (GEBV). The GEBV are calculated as the sum of the effects of dense genetic markers, or haplotypes of these markers, across the entire genome, thereby potentially capturing all the quantitative trait loci (QTL) that contribute to variation in a trait. The QTL effects, inferred from either haplotypes or individual single nucleotide polymorphism markers, are first estimated in a large reference population with phenotypic information. In subsequent generations, only marker information is required to calculate GEBV. The reliability of GEBV predicted in this way has already been evaluated in experiments in the United States, New Zealand, Australia, and the Netherlands. These experiments used reference populations of between 650 and 4,500 progeny-tested Holstein-Friesian bulls, genotyped for approximately 50,000 genome-wide markers. Reliabilities of GEBV for young bulls without progeny test results in the reference population were between 20 and 67%. The reliability achieved depended on the heritability of the trait evaluated, the number of bulls in the reference population, the statistical method used to estimate the single nucleotide polymorphism effects in the reference population, and the method used to calculate the reliability. A common finding in 3 countries (United States, New Zealand, and Australia) was that a straightforward BLUP method for estimating the marker effects gave reliabilities of GEBV almost as high as more complex methods. The BLUP method is attractive because the only prior information required is the additive genetic variance of the trait. All countries included a polygenic effect (parent average breeding value) in their GEBV calculation. This inclusion is recommended to capture any genetic variance not associated with the markers, and to put some selection pressure on low-frequency QTL that may not be captured by the markers. The reliabilities of GEBV achieved were significantly greater than the reliability of parental average breeding values, the current criteria for selection of bull calves to enter progeny test teams. The increase in reliability is sufficiently high that at least 2 dairy breeding companies are already marketing bull teams for commercial use based on their GEBV only, at 2 yr of age. This strategy should at least double the rate of genetic gain in the dairy industry. Many challenges with genomic selection and its implementation remain, including increasing the accuracy of GEBV, integrating genomic information into national and international genetic evaluations, and managing long-term genetic gain.
Keyword Genomic selection
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collection: Queensland Alliance for Agriculture and Food Innovation
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 564 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 588 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 05 Aug 2016, 09:51:18 EST by System User on behalf of Learning and Research Services (UQ Library)