Journal article

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Yvonne CJ Wientjes, Mario PL Calus, Michael E Goddard, Ben J Hayes



BACKGROUND: Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian an..

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University of Melbourne Researchers


Awarded by Breed4Food

Awarded by EU

Funding Acknowledgements

The authors thank Roel Veerkamp, Chris Schrooten and Henk Bovenhuis for their useful comments. This study was financially supported by Breed4Food (KB-12-006.03-005-ASG-LR), a public-private partnership in the domain of animal breeding and genomics, the cooperative cattle improvement organization CRV BV (Arnhem, The Netherlands), and EU FP7 IRSES SEQSEL (Grant no. 317697) by funding the research visit of Yvonne Wientjes at the Department of Environmental and Primary Industries in Victoria, Australia. The 1000 bulls genomes consortium is acknowledged for providing the sequence data, and in particular Paul Stothard for providing the annotations.