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Genomic selection: the option for new robustness traits?

Published online by Cambridge University Press:  30 July 2013

M. P. L. Calus ,
D. P. Berry ,
G. Banos ,
Y. de Haas  and
R. F. Veerkamp
M. P. L. Calus*
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 8200 AB Lelystad, The Netherlands
D. P. Berry
Affiliation:
Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Co. Cork, Ireland
G. Banos
Affiliation:
Animal & Veterinary Sciences Group, SRUC, Roslin Institute Building, Easter Bush, Penicuik, EH25 9RG Scotland, UK
Y. de Haas
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 8200 AB Lelystad, The Netherlands
R. F. Veerkamp
Affiliation:
Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, 8200 AB Lelystad, The Netherlands
*
†E-mail: mario.calus@wur.nl
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Abstract

Genomic selection is rapidly becoming the state-of-the-art genetic selection methodology in dairy cattle breeding schemes around the world. The objective of this paper was to explore possibilities to apply genomic selection for traits related to dairy cow robustness. Deterministic simulations indicate that replacing progeny testing with genomic selection may favour genetic response for production traits at the expense of robustness traits, owing to a disproportional change in accuracies obtained across trait groups. Nevertheless, several options are available to improve the accuracy of genomic selection for robustness traits. Moreover, genomic selection opens up the opportunity to begin selection for new traits using specialised reference populations of limited size where phenotyping of large populations of animals is currently prohibitive. Reference populations for such traits may be nucleus-type herds, research herds or pooled data from (international) research experiments or research herds. The RobustMilk project has set an example for the latter approach, by collating international data for progesterone-based traits, feed intake and energy balance-related traits. Reference population design, both in terms of relatedness of the animals and variability in phenotypic performance, is important to optimise the accuracy of genomic selection. Use of indicator traits, combined with multi-trait genomic prediction models, can further contribute to improved accuracy of genomic prediction for robustness traits. Experience to date indicates that for newly recorded robustness traits that are negatively correlated with the main breeding goal, cow reference populations of ⩾10 000 are required when genotyping is based on medium- or high-density single-nucleotide polymorphism arrays. Further genotyping advances (e.g. sequencing) combined with post-genomics technologies will enhance the opportunities for (genomic) selection to improve cow robustness.

Keywords

genomic selectionrobustnessdairy cattle
Type
Full Paper
Information
Advances in Animal Biosciences , Volume 4 , Issue 3: Proceedings of the ROBUSTMILK project, an EU wide programme which was financially supported by the European Commission under the Seventh Research Framework Program, Grant Agreement KBBE–211708 , July 2013 , pp. 618 - 625
Copyright
Copyright © The Animal Consortium 2013 

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