Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets

de Haas, Y., Calus, M. P. L., Veerkamp, R. F., Wall, E., Coffey, M. P., Daetwyler, H. D., Hayes, B. J. and Pryce, J. E. (2012) Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets. Journal of Dairy Science, 95 10: 6103-6112. doi:10.3168/jds.2011-5280


Author de Haas, Y.
Calus, M. P. L.
Veerkamp, R. F.
Wall, E.
Coffey, M. P.
Daetwyler, H. D.
Hayes, B. J.
Pryce, J. E.
Title Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets
Journal name Journal of Dairy Science   Check publisher's open access policy
ISSN 0022-0302
1525-3198
Publication date 2012-10
Sub-type Article (original research)
DOI 10.3168/jds.2011-5280
Open Access Status Not yet assessed
Volume 95
Issue 10
Start page 6103
End page 6112
Total pages 10
Place of publication New York, United States
Publisher Elsevier
Language eng
Abstract With the aim of increasing the accuracy of genomic estimated breeding values for dry matter intake (DMI) in dairy cattle, data from Australia (AU), the United Kingdom (UK), and the Netherlands (NL) were combined using both single-trait and multi-trait models. In total, DMI records were available on 1,801 animals, including 843 AU growing heifers with records on DMI measured over 60 to 70. d at approximately 200. d of age, and 359 UK and 599 NL lactating heifers with records on DMI during the first 100. d in milk. The genotypes used in this study were obtained from the Illumina Bovine 50K chip (Illumina Inc., San Diego, CA). The AU, UK, and NL genomic data were matched using the single nucleotide polymorphism (SNP) name. Quality controls were applied by carefully comparing the genotypes of 40 bulls that were available in each data set. This resulted in 30,949 SNP being used in the analyses. Genomic predictions were estimated with genomic REML, using ASReml software. The accuracy of genomic prediction was evaluated in 11 validation sets; that is, at least 3 validation sets per country were defined. The reference set (in which animals had both DMI phenotypes and genotypes) was either AU or Europe (UK and NL) or a multi-country reference set consisting of all data except the validation set. When DMI for each country was treated as the same trait, use of a multi-country reference set increased the accuracy of genomic prediction for DMI in UK, but not in AU and NL. Extending the model to a bivariate (AU-EU) or trivariate (AU-UK-NL) model increased the accuracy of genomic prediction for DMI in all countries. The highest accuracies were estimated for all countries when data were analyzed with a trivariate model, with increases of up to 5.5% compared with univariate models within countries.
Keyword Dry matter intake
Genomic prediction
Multi-trait genomic REML
Validation
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 29 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 34 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Fri, 05 Aug 2016, 09:45:50 EST by System User on behalf of Learning and Research Services (UQ Library)