Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits

Aliloo, Hassan, Pryce, Jennie E., Gonzalez-Recio, Oscar, Cocks, Benjamin G. and Hayes, Ben J. (2016) Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits. Genetics Selection Evolution, 48 1: 8.1-8.11. doi:10.1186/s12711-016-0186-0

Author Aliloo, Hassan
Pryce, Jennie E.
Gonzalez-Recio, Oscar
Cocks, Benjamin G.
Hayes, Ben J.
Title Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits
Journal name Genetics Selection Evolution   Check publisher's open access policy
ISSN 1297-9686
Publication date 2016-02-01
Year available 2016
Sub-type Article (original research)
DOI 10.1186/s12711-016-0186-0
Open Access Status DOI
Volume 48
Issue 1
Start page 8.1
End page 8.11
Total pages 11
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Formatted abstract
Background: Dominance effects may contribute to genetic variation of complex traits in dairy cattle, especially for traits closely related to fitness such as fertility. However, traditional genetic evaluations generally ignore dominance effects and consider additive genetic effects only. Availability of dense single nucleotide polymorphisms (SNPs) panels provides the opportunity to investigate the role of dominance in quantitative variation of complex traits at both the SNP and animal levels. Including dominance effects in the genomic evaluation of animals could also help to increase the accuracy of prediction of future phenotypes. In this study, we estimated additive and dominance variance components for fertility and milk production traits of genotyped Holstein and Jersey cows in Australia. The predictive abilities of a model that accounts for additive effects only (additive), and a model that accounts for both additive and dominance effects (additive + dominance) were compared in a fivefold cross-validation.

Results: Estimates of the proportion of dominance variation relative to phenotypic variation that is captured by SNPs, for production traits, were up to 3.8 and 7.1 % in Holstein and Jersey cows, respectively, whereas, for fertility, they were equal to 1.2 % in Holstein and very close to zero in Jersey cows. We found that including dominance in the model was not consistently advantageous. Based on maximum likelihood ratio tests, the additive + dominance model fitted the data better than the additive model, for milk, fat and protein yields in both breeds. However, regarding the prediction of phenotypes assessed with fivefold cross-validation, including dominance effects in the model improved accuracy only for fat yield in Holstein cows. Regression coefficients of phenotypes on genetic values and mean squared errors of predictions showed that the predictive ability of the additive + dominance model was superior to that of the additive model for some of the traits.

Conclusions: In both breeds, dominance effects were significant (P < 0.01) for all milk production traits but not for fertility. Accuracy of prediction of phenotypes was slightly increased by including dominance effects in the genomic evaluation model. Thus, it can help to better identify highly performing individuals and be useful for culling decisions.
Keyword Dairy cows
Milk production
Genetic variation
Dominance effects
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Alliance for Agriculture and Food Innovation
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Citation counts: TR Web of Science Citation Count  Cited 10 times in Thomson Reuters Web of Science Article | Citations
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Created: Thu, 07 Jul 2016, 22:08:29 EST by Anthony Yeates on behalf of Learning and Research Services (UQ Library)