Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-23T15:12:49.787Z Has data issue: false hasContentIssue false

Genomic dairy cattle breeding: risks and opportunities for cow welfare

Published online by Cambridge University Press:  01 January 2023

T Mark
Affiliation:
Department of Basic Animal and Veterinary Sciences, Faculty of Life Sciences, University of Copenhagen, 1870 Frederiksberg C, Denmark
P Sand⊘e*
Affiliation:
Department of Large Animal Sciences, Faculty of Life Sciences, University of Copenhagen, 1870 Frederiksberg C, Denmark
*
* Contact for correspondence and requests for reprints: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The aim of this paper is to discuss the potential consequences of modern dairy cattle breeding for the welfare of dairy cows. The paper focuses on so-called genomic selection, which deploys thousands of genetic markers to estimate breeding values. The discussion should help to structure the thoughts of breeders and other stakeholders on how to best make use of genomic breeding in the future. Intensive breeding has played a major role in securing dramatic increases in milk yield since the Second World War. Until recently, the main focus in dairy cattle breeding was on production traits, but during the past couple of decades more emphasis has been placed on a few rough, but useful, measures of traits relevant to cow welfare, including calving ease score and ‘clinical disease or not’; the aim being to counteract the unfavourable genetic association with production traits. However, unfavourable genetic trends for metabolic, reproductive, claw and leg diseases indicate that these attempts have been insufficient. Today, novel genome-wide sequencing techniques are revolutionising dairy cattle breeding; these enable genetic changes to occur at least twice as rapidly as previously. While these new genomic tools are especially useful for traits relating to animal welfare that are difficult to improve using traditional breeding tools, they may also facilitate breeding schemes with reduced generation intervals carrying a higher risk of unwanted side-effects on animal welfare. In this paper, a number of potential risks are discussed, including detrimental genetic trends for non-measured welfare traits, the increased chance of spreading unfavourable mutations, reduced sharing of information arising from concerns over patents, and an increased monopoly within dairy cattle breeding that may make it less accountable to the concern of private farmers for the welfare of their animals. It is argued that there is a need to mobilise a wide range of stakeholders to monitor developments and maintain pressure on breeding companies so that they are aware of the need to take precautionary measures to avoid negative effects on animal welfare and to invest in breeding for increased animal welfare. Researchers are encouraged to further investigate the long-term effects of various breeding schemes that rely on genomic breeding values.

Type
Research Article
Copyright
© 2010 Universities Federation for Animal Welfare

References

Daetwyler, HD, Villaneuva, B, Bijma, P and Wooliams, JA 2007 Inbreeding in genome-wide selection. Journal of Animal Breeding Genetics 124: 369376CrossRefGoogle ScholarPubMed
Danish Cattle Federation 2008 Årsstatistik, Avl 2007-2008. Report 119. US Nielsen: Denmark. [Title translation: Annual statistics, breeding 2007-2008]Google Scholar
Dekkers, JCM 2007 Prediction of response to marker-assisted and genomic selection using selection index theory. Journal of Animal Breeding Genetics 124: 331341CrossRefGoogle ScholarPubMed
de Jong, G and Voskamp, W 2009 Genomic selection in CRV. Interbull Bull 39: 4750Google Scholar
de Roos, APW, Schrooten, C, Mullaart, E, van der Beek, S, Feugang, JM, Camargo-Rodríguez, O and Memili, E 2009 Culture systems for bovine embryos Livestock Science 121: 141149Google Scholar
Georges, M and Massey, JM 1991 Velogenetics, or the synergistic use of marker assisted selection and germ-line manipulation. Theriogenology 35: 151159CrossRefGoogle Scholar
Goddard, ME 2009 Genomic selection: prediction of accuracy and maximisation of long term response. Genetica 136: 245257CrossRefGoogle ScholarPubMed
Haley, CS and Visscher, PM 1998 Strategies to utilize markerquantitative trait loci associations. Journal of Dairy Science 81(2): 8597CrossRefGoogle ScholarPubMed
Henderson, CR 1984 Applications of Linear Models in Animal Breeding. University of Guelph: Ontario, CanadaGoogle Scholar
Heringstad, B, Klemetsdal, G and Raune, J 2000 Selection for mastitis in dairy cattle: a review with focus on the situation in the Nordic countries. Livestock Production Science 64: 95106CrossRefGoogle Scholar
Hill, WG 1982 Predictions of response to artificial selection from new mutations. Genetics Research 40: 255278.CrossRefGoogle ScholarPubMed
Interbull 2009 www.interbull.org | genetic evaluationsGoogle Scholar
Johansson, K, Pösö, J, Nielsen, US, Eriksson, J-Å and Aamand, GP 2008 Joint genetic evaluation of other disease traits in Denmark, Finland and Sweden. Interbull Bull 38: 107112Google Scholar
König, S, Lessner, S and Simianer, H 2007 Application of controlling instruments for improvements in cow sire selection. Journal of Dairy Science 90: 19671980CrossRefGoogle ScholarPubMed
König, S, Simianer, H and Willam, A 2009 Economic evaluation of genomic breeding programs. Journal of Dairy Science 92: 282291CrossRefGoogle ScholarPubMed
Loberg, A and Dürr, JW 2009 Interbull survey on the use of genomic information. Interbull Bull 39: 313Google Scholar
Meuwissen, THE, Hayes, BJ and Goddard, ME 2001 Prediction of total genetic value using genome-wide dense marker maps. Genetics 157: 18191829CrossRefGoogle ScholarPubMed
Miglior, F, Muir, BL and van Doormaal, BJ 2005 Selection indices in Holstein cattle of various countries. Journal of Dairy Science 88: 12551263Google ScholarPubMed
Olsson, IAS, Gamborg, C and Sand⊘e, P 2006 Taking ethics into account in farm animal breeding: What can the breeding companies achieve? Journal of Agricultural and Environmental Ethics 19: 3746CrossRefGoogle Scholar
Rauw, WM, Kanis, E, Noordhuizen-Stassen, EN and Grommers, FJ 1998 Undesirable side effects of selection for high production efficiency in farm animals: A review. Livestock Production Science 56: 1533CrossRefGoogle Scholar
Rutten, MJM, Bijma, P, Woolliams, JA and van Arendonk, JAM 2002 SelcAction: Software to predict selection response and rate of inbreeding in livestock breeding programs. Journal of Heredity 93: 456458CrossRefGoogle Scholar
Schaeffer, LR 2008 Bull selection strategies using genomic estimated breeding values. Proceedings of the ICAR 36th Session pp 319324. Niagara Falls, United StatesGoogle Scholar
S⊘rensen, MK, Norberg, E, Pedersen, J and Christensen, LG 2008 Invited review: Crossbreeding in dairy cattle: a Danish perspective. Journal of Dairy Science 91: 41164128CrossRefGoogle Scholar
S⊘rensen, AC and S⊘rensen, MK 2009 Inbreeding rates in breeding programs with different strategies for using genomic selection. Proceedings of the Interbull Meeting. 21-24 August 2009, Barcelona, SpainGoogle Scholar
Su, G, Guldbrandtsen, B and Gregersen, VR and Lund, MS 2010 Preliminary investigation on reliability of genomic estimated breeding values in the Danish Holstein population. Journal of Dairy Science, in pressCrossRefGoogle Scholar
VanRaden, PM, Van Tassel, CP, Wiggans, GR, Sonstegard, TS, Schnabel, RD, Taylor, JF and Schenkel, FS 2008 Invited review: Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science 92: 1624CrossRefGoogle Scholar