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A strategy for QTL detection in half-sib populations

Published online by Cambridge University Press:  02 September 2010

D. J. de Koning
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS Wageningen Agricultural University, Department of Animal Breeding, PO Box 338, 6700 AH Wageningen, The Netherlands
P. M. Visscher
Affiliation:
Institute of Ecology and Resource Management, University of Edinburgh, West Mains Road, Edinburgh EH9 3JG
S. A. Knott
Affiliation:
Institute of Cell, Animal and Population Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT
C. S. Haley
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
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Abstract

A statistical analysis strategy for the detection of quantitative trait loci (QTLs) in half-sib populations is outlined. The initial exploratory analysis is a multiple regression of the trait score on a subset of markers to allow a rapid identification of possible chromosomal regions of interest. This is followed by multiple marker interval mapping with regression methods within and across families fitting one or two QTLs. Empirical thresholds are determined by experiment-wise permutation tests for different significance levels and empirical confidence intervals for the QTLs' positions are obtained by bootstrapping methods. For traits with evidence for a significant single-QTL effect, an approximate maximum likelihood analysis is performed to obtain estimates of QTL effect and the probability of the QTL genotype for each parent of a group of half-sibs. The strategy is demonstrated in an analysis of previously published data on chromosome 6 and five production traits from a granddaughter design in dairy cattle. The results confirm and extend evidence for QTLs affecting protein percentage. Informativeness of markers limited the possibility of mapping more than one QTL on the same linkage group.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1998

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References

Andersson, L., Haley, C. S., Ellegren, H., Knott, S. A., Johansson, M., Andersson, K., Andersson-Eklund, L., Edfors-Lilja, I., Fredholm, M., Hansson, I., Hakansson, J. and Lundström, K. 1994. Genetic mapping of quantitative trait loci for growth and fatness in pigs. Science 263: 17711774.CrossRefGoogle ScholarPubMed
Bovenhuis, H. and Weller, J. I. 1994. Mapping and analysis of dairy-cattle quantitative trait loci by maximum likelihood methodology using milk protein genes as genetic markers. Genetics 137: 267280.Google ScholarPubMed
Chatfield, C. and Collins, A. J. 1989. Introduction to multivariate analysis. Chapman and Hall, London.Google Scholar
Churchill, G. A. and Doerge, R. W. 1994. Empirical threshold values for quantitative trait mapping. Genetics 138: 963971.Google ScholarPubMed
Dekkers, J. M. C. and Dentine, M. R. 1991. Quantitative genetic variance associated with chromosomal markers in segregating populations. Theoretical and Applied Genetics 81: 212220.CrossRefGoogle ScholarPubMed
Elsen, J. M., Knott, S. A., Le Roy, P. and Haley, C. S. 1997. Comparison between some approximate maximum likelihood methods for quantitative trait locus detection in progeny test designs. Theoretical and Applied Genetics 95: 236245.CrossRefGoogle Scholar
Genstat 5 Committee. 1993. GENSTAT 5 release 3 reference manual. Clarendon Press, Oxford.Google Scholar
Georges, M., Nielsen, D., Mackinnon, M., Mishra, A., Okimoto, R., Pasquino, A. T., Sargeant, L. S., Sorensen, A., Steele, M. R., Zhao, X., Womack, J. E. and Hoeschele, I. 1995. Mapping quantitative trait loci controlling milk production in dairy cattle by exploiting progeny testing. Genetics 139: 907920.Google ScholarPubMed
Haley, C. S. and Knott, S. A. 1992. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. Heredity 69: 315324.CrossRefGoogle ScholarPubMed
Haley, C. S., Knott, S. A. and Elsen, J. M. 1994. Multi marker approaches to quantitative trait loci in livestock. Proceedings of the 45th meeting of the European Association of Animal Production, Edinburgh.Google Scholar
Jansen, R. C. 1993. Interval mapping of quantitative trait loci. Genetics 135: 205211.Google ScholarPubMed
Knott, S. A., Elsen, J. M. and Haley, C. S. 1994. Multiple marker mapping of quantitative trait loci in half sib populations. Proceedings of the fifth world congress on genetics applied to livestock production, Guelph, vol. 21, pp. 3336.Google Scholar
Knott, S. A., Elsen, J. M. and Haley, C. S. 1996. Methods for multiple marker mapping of quantitative trait loci in half-sib populations. Theoretical and Applied Genetics 93: 7180.CrossRefGoogle ScholarPubMed
Knott, S. A., Haley, C. S. and Thompson, R. 1991. Methods of segregation analysis for animal breeding data: parameter estimates. Heredity 68: 313320.CrossRefGoogle Scholar
Kruglyak, L. and Lander, E. S. 1995. Complete multipoint sib-pair analysis of qualitative and quantitative traits. American Journal of Human Genetics 57: 439454.Google ScholarPubMed
Lander, E. S. and Botstein, D. 1989. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121: 185199.Google ScholarPubMed
Lander, E. and Kruglyak, L. 1995. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nature Genetics 11: 241247.CrossRefGoogle ScholarPubMed
Martinez, O. and Curnow, R. N. 1992. Estimating the locations and the sizes of the effects of quantitative trait loci using flanking markers. Theoretical and Applied Genetics 85: 480488.CrossRefGoogle ScholarPubMed
Neimann-Sorensen, A. and Robertson, A. 1961. The association between blood groups and several production characteristics in three Danish cattle breeds. Acta Agriculturae Scandinavica 11: 163196.CrossRefGoogle Scholar
Ooijen, J. W. van. 1992. Accuracy of mapping quantitative trait loci in autogamous species. Theoretical and Applied Genetics 84: 803811.CrossRefGoogle ScholarPubMed
Ron, M., Band, M., Yanai, A. and Weller, J. I. 1994. Mapping quantitative trait loci with DNA microsatellites in a commercial dairy cattle population. Animal Genetics 25: 259264.CrossRefGoogle Scholar
Spelman, R. J., Coppieters, W., Karim, L., Arendonk, J. A. M. van and Bovenhuis, H. 1996. Quantitative trait loci analysis for five milk production traits on chromosome six in the Dutch Holstein-Friesian population. Genetics 144: 17991808.Google ScholarPubMed
Van Raden, P. M. and Wiggans, G. R. 1991. Derivation, calculation and use of national animal-model information. Journal of Dairy Science 74: 27372746.CrossRefGoogle Scholar
Vilkki, H. J., Koning, D.-J. de, Elo, K., Velmala, R. and Mäki-Tanila, A. 1997. Multiple marker mapping of quantitative trait loci of Finnish dairy cattle by regression. Journal of Dairy Science 80: 198204.CrossRefGoogle ScholarPubMed
Visscher, P. M. 1996. Proportion of the variation in genetic composition in backcrossing programs explained by generic markers. Journal of Heredity 87: 136138.CrossRefGoogle Scholar
Visscher, P. M. and Haley, C. S. 1996. Detection of putative quantitative trait loci in line crosses under infinitesimal genetic models. Theoretical and Applied Genetics 93: 691702.CrossRefGoogle ScholarPubMed
Visscher, P. M., Thompson, R. and Haley, C. S. 1996. Confidence intervals in QTL mapping by bootstrapping. Genetics 143: 10131020.Google ScholarPubMed
Weller, J. I., Kashi, Y. and Soller, M. 1990. Power of daughter and granddaughter designs for determining linkage between marker loci and quantitative trait loci in dairy cattle. Journal of Dairy Science 73: 25252537.CrossRefGoogle ScholarPubMed
Whittaker, J. C., Thompson, R. and Visscher, P. M. 1996. On the mapping of QTL by regression of phenotype on marker-type. Heredity 77: 2332.CrossRefGoogle Scholar

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