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dc.contributor.authorDe Haas Yen_US
dc.contributor.authorCalus MPLen_US
dc.contributor.authorVeerkamp RFen_US
dc.contributor.authorWall Een_US
dc.contributor.authorCoffey MPen_US
dc.contributor.authorDaetwyler HDen_US
dc.contributor.authorHayes BJen_US
dc.contributor.authorPryce JEen_US
dc.date.accessioned2013-09-11T15:09:37Z
dc.date.available2013-09-11T15:09:37Z
dc.date.issued2012en_US
dc.identifier.citation95en_US
dc.identifier.other13248en_US
dc.identifier.urihttp://hdl.handle.net/11262/8223
dc.identifier.urihttp://dx.doi.org/doi:10.3168/jds.2011-5280en_US
dc.description.abstractWith 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.
dc.relation.isformatof13248.pdfen_US
dc.relation.ispartofJournal of Dairy Scienceen_US
dc.subjectDry matter intakeen
dc.subjectMulti-trait genomic REMLen
dc.subjectValidationen
dc.subjectGenomic predictionen
dc.titleImproved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data setsen_US
dc.extent.pageNumbers6103en_US
dc.extent.pageNumbers6112en_US


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