Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-25T05:36:48.303Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic management strategies for controlling infectious diseases in livestock populations

Published online by Cambridge University Press:  20 November 2017

S. C. Bishop  and
K. Mackenzie
S. C. Bishop
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian, Scotland, EH25 9PS
K. Mackenzie
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian, Scotland, EH25 9PS
Get access

Extract

Disease resistance is often cited as the major challenge facing animal geneticists, with much effort directed towards finding disease-resistance genes. The PrP gene controlling resistance of sheep to scrapie is such an example. To design effective breeding strategies utilising such genes, it is critical to understand the impact that these genes have upon disease transmission. For example, it has been shown that it is not necessary to make all animals genetically resistant in order to protect the population as a whole from epidemics (MacKenzie and Bishop, 1999). Additionally, concern is often voiced over the possibility of the pathogen co-evolving with the host, reducing the utility of the genes. By combining animal breeding and epidemiology theory, this study derives strategies for using disease resistance genes to control disease transmission, and considers the co-evolution risks with such strategies.

Type
Theatre Presentations
Information
Proceedings of the British Society of Animal Science , Volume 2002 , 2002 , pp. 55
Copyright
Copyright © The British Society of Animal Science 2002

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Dushoff, J. and Levin, S. 1995. The effects of population heterogeneity on disease invasion. Math. Biosci., 128, 25–40.Google Scholar
MacKenzie, Katrin and Bishop, S.C. 1999. A discrete-time epidemiological model to quantify selection for disease resistance. Anim. Sci., 69: 543–552.Google Scholar
Renshaw, E. 1991. “Modelling Biological Populations in Space and Time”, Cambridge University Press.Google Scholar