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The effect of linkage disequilibrium on the estimates of Single Nucleotide Polymorphic effects

Published online by Cambridge University Press:  22 November 2017

K Moore ,
J Gibson  and
D Johnston
K Moore*
Affiliation:
Animal Genetics and Breeding Unit, University of New England, Armidale, NSW, Australia EGENES, Scottish Agricultural College, Penicuik, United Kingdom
J Gibson
Affiliation:
The Institute of Genetics and Bioinformatics, University of New England, Armidale, NSW, Australia
D Johnston
Affiliation:
Animal Genetics and Breeding Unit, University of New England, Armidale, NSW, Australia
*
Email: Kirsty.Moore@sac.ac.uk
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Extract

The identification and exploitation of single nucleotide polymorphisms (SNP) associated with production traits present new opportunities for livestock genetic improvement. Often the identified SNP is not the causative mutation but rather is in some degree of linkage disequilibrium (LD). LD markers within 5cM can be considered as direct markers for the causative mutation because they are located close to the causative mutation (Dekkers, 2004). In a dairy herd, Farnir et al., (2000) estimated that the average LD, measured as D′ was 0.5 for loci pairs positioned within 5cM. Goddard et al., (2006) estimated that LD measured as r2 decreased rapidly as the physical distance between loci increased; at a separating distance of 0.5Mb the LD (r2) was only approximately 0.2. The aim of this work was to use stochastic simulation to investigate the effect that the distance between the SNP and causative mutation had on the accuracy of estimating additive and dominance effects of the causative mutation.

Type
Theatre Presentations
Information
Proceedings of the British Society of Animal Science , Volume 2009 , April 2009 , pp. 44
Copyright
Copyright © The British Society of Animal Science 2009

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References

Dekkers, J.C.M. 2004. Journal of Animal Science. 82, E313–E328 Google Scholar
Farnir, F., Coppieters, W., Arranz, J.J., Berzi, p., Cambisano, N., Grisart, B., Karim, L., Marcq, F., Moreau, L., Mni, M., Nezer, C., Simon, P., Vanmanshoven, P., Wagenaar, D. and Georges, M. 2000. Genome Research. 10, 220–227 CrossRefGoogle Scholar
Gilmour, A.R., Gogel, B.J., Cullis, B.R., Welham, S.J. and Thompson, R. 2002. ASReml user guide release 1.0Google Scholar
Goddard, M.E., Hayes, B.J., McPartlan, H. and Chamberlain, A.J. 2006. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production. Communication 22–16 Google Scholar