Using sequence data to improve accuracy of genomic prediction and QTL discovery for dairy cow fertility. — ASN Events
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  2. Concurrent 10 - Reproduction, behaviour & health II
  3. Using sequence data to improve accuracy of genomic prediction and QTL discovery for dairy cow fertility.

Using sequence data to improve accuracy of genomic prediction and QTL discovery for dairy cow fertility. (#59)

Iona MacLeod 1 2 3 , Ben Hayes 2 3 4 , Mekonnen Haile-Mariam 2 3 , Phil Bowman 2 3 , Amanda Chamberlain 2 3 , Christy Vander Jagt 2 3 , Chris Schrooten 5 , Michael Goddard 1 2 3
  1. Faculty of Veterinary & Agricultural Science, University of Melbourne , Melbourne, Victoria , Australia
  2. Dairy Futures Cooperative Research Centre, AgriBio, Bundoora , Victoria, Australia
  3. AgriBio, Dept. Economic Dev., Jobs, Transport & Resources, Melbourne, Victoria, Australia
  4. Biosciences Research Centre, La Trobe University, Melbourne, Victoria, Australia
  5. CRV, 6800 AL, Arnhem, Netherlands

Using a Bayesian genomic prediction method, BayesR, we demonstrate improved accuracy of genomic prediction for cow fertility using high density SNP markers combined with imputed sequence variants in and close to genes. We also used the same analysis to identify candidate genes and potential causal mutations with a broad range of effects on fertility.

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