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Bayesian segregation analysis of faecal egg count data simulated from a stochastic genetic epidemiological model of gastrointestinal nematode infections in sheep

Published online by Cambridge University Press:  20 November 2017

M Nath*
Affiliation:
Biomathematics and Statistics Scotland, Edinburgh, United Kingdom
R Pong-wong
Affiliation:
Roslin Institute and Royal (Dick) School of Veterinary Studies, Roslin, Edinburgh, United Kingdom
J.W. Woolliams
Affiliation:
Roslin Institute and Royal (Dick) School of Veterinary Studies, Roslin, Edinburgh, United Kingdom
S.C Bishop
Affiliation:
Roslin Institute and Royal (Dick) School of Veterinary Studies, Roslin, Edinburgh, United Kingdom
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Extract

Resistance to gastro-intestinal (GI) nematode infection in sheep may be partly attributed to host genetic variation. Faecal egg count (FEC) of an individual is an important indicator trait that measures the relative resistance of sheep to GI nematode infections. The FEC can be measured easily and repeatedly over short time intervals, and its genetic properties and utility as a selection tool are well understood (Bishop and Stear, 2001). However, FEC is the result of a complex series of host-parasite interactions that depend on host genetics and immunological mechanisms, epidemiology of the disease, and other non-genetic measures. The objective of the present study was to determine, in silico, underlying host immunological mechanisms that could lead to observable major genes for FEC. To achieve that, we have extended the stochastic genetic epidemiological model for nematode infection in sheep as described by Bishop and Stear (2001), and used complex segregation analyses to explore the genetic properties of the simulated FEC data.

Type
Theatre Presentations
Copyright
Copyright © The British Society of Animal Science 2008

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References

Bishop, S.C. and Stear, M.J. 2001. Animal Science. 73, 389–395.CrossRefGoogle Scholar
Janss, L.L.G., Thompson, R. and Arendonk, J.A.M. van. 1995. Theoretical and Applied Genetics. 91, 1137–147.Google Scholar