Improved precision of QTL mapping using a nonlinear Bayesian method in a multi-breed population leads to greater accuracy of across-breed genomic predictions
Kathryn E Kemper, Coralie M Reich, Philip J Bowman, Christy J vander Jagt, Amanda J Chamberlain, Brett A Mason, Benjamin J Hayes, Michael E Goddard
Genetics Selection Evolution | BMC | Published : 2015
BACKGROUND: Genomic selection is increasingly widely practised, particularly in dairy cattle. However, the accuracy of current predictions using GBLUP (genomic best linear unbiased prediction) decays rapidly across generations, and also as selection candidates become less related to the reference population. This is likely caused by the effects of causative mutations being dispersed across many SNPs (single nucleotide polymorphisms) that span large genomic intervals. In this paper, we hypothesise that the use of a nonlinear method (BayesR), combined with a multi-breed (Holstein/Jersey) reference population will map causative mutations with more precision than GBLUP and this, in turn, will in..View full abstract
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Awarded by Australian Research Council's Discovery Projects funding scheme
Authors thank Gert Nieuwhof and Kon Konstantinov from the Australian Dairy Herd Improvement Scheme (ADHIS) and the Dairy Futures Co-operative Research Centre for the provision of data and resources to conduct this research. The Australian Red Breed Association, Holstein Australia, Jersey Australia and many dairy farmers are warmly thanked for sample collection. This research was supported under Australian Research Council's Discovery Projects funding scheme (project DP1093502). The views expressed herein are those of the authors and are not necessarily those of the Australian Research Council.