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Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit

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Authors:
  • Thomasen, Jørn Rind ;
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    Department of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Science and Technology, Aarhus University
  • Egger-Danner, C ;
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    ZuhchtData EDV-Dienstleistungen GmbH
  • Willam, A ;
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    Division of Livestock Sciences, Department of Sustainable Agricultural Systems, University of Natural Resources and Life Science Vienna
  • Guldbrandtsen, Bernt ;
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    Department of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Science and Technology, Aarhus University
  • Lund, Mogens Sandø ;
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    Department of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Science and Technology, Aarhus University
  • Sørensen, Anders Christian
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    Department of Molecular Biology and Genetics - Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Science and Technology, Aarhus University
DOI:
10.3168/jds.2013-6599
Abstract:
Small dairy cattle populations are challenged because of the low reliabilities of genomic predictions. We have demonstrated that low reliabilities of genomic predictions sets limitations for moving towards more genetic efficient breeding schemes with more intensive use of young bulls without progeny testing. Strong positive interaction effects between increased reliability of genomic predictions and more intensive use of young bulls exist. From an economic perspective a juvenile scheme is always advantageous. The main future focus area for the smaller dairy cattle breeds is to join forces that increase reliabilities of genomic predictions.
Type:
Journal article
Language:
English
Published in:
Journal of Dairy Science, 2014, Vol 97, Issue 1, p. 458-470
Main Research Area:
Science/technology
Publication Status:
Published
Review type:
Peer Review
Submission year:
2013
Scientific Level:
Scientific
ID:
255873660

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