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On the efficiency of marker-assisted introgression

Published online by Cambridge University Press:  18 August 2016

P. M. Visscher  and
C. S. Haley
P. M. Visscher
Affiliation:
institute of Ecology and Resource Management, University of Edinburgh, West Mains Road, Edinburgh EH9 3JG
C. S. Haley
Affiliation:
Roslin Institute (Edinburgh), Roślin, Midlothian EH25 9PS
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Abstract

The efficiency of marker-assisted introgression programmes, expressed as genetic lag relative to a commercial population under continuous selection, was investigated using analytical methods. A genetic model was assumed for which the genetic variance in the introgression population was a function of the within-breed genetic variance and the initial breed difference. It was found that most of the genetic lag occurs in the latter stages of an introgression programme, when males and females which are heterozygous for the alíele to be introgressed are mated to produce homozygous individuals. Reducing genetic lag through selection on genomie proportion by using genetic markers throughout the genome, i.e. by selecting heterozygous individuals which resemble the recipient (commercial) population most, was effective if the initial breed difference was very large (e.g. 20 within-breed phenotypic standard deviations). In that case, selection solely on genetic markers could be practised to speed up genome recovery of the commercial line. If the initial breed difference is small, phenotypic or best linear unbiased prediction (BLUP) selection is superior in reducing genetic lag under the assumed genetic model.

Keywords

genetic markersintrogressionpigsselection
Type
Research Article
Information
Animal Science , Volume 68 , Issue 1 , February 1999 , pp. 59 - 68
Copyright
Copyright © British Society of Animal Science 1999

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References

Gama, L. T., Smith, C. and Gibson, J. P. 1992. Transgene effects, introgression strategies and testing schemes in pigs. Animal Production 54: 427–440.Google Scholar
Hill, W. G. 1993. Variation in genetic composition in backcrossing programs. Journal of Heredity 84: 212–213.Google Scholar
Hospital, F., Chevalet, C. and Mulsant, P. 1992. Using markers in gene introgression breeding programs. Genetics 132: 1199–1210.CrossRefGoogle ScholarPubMed
Lander, E. S. 1996. The new genomics: global views of biology. Science 274: 536–539.CrossRefGoogle ScholarPubMed
Rothschild, M. F., Jacobson, C., Vaske, D. A., Tuggle, C. K., Wang, L., Short, T. H., Eckardt, G. R., Sasaki, S., Vincent, A., McLaren, D. G., Southwood, O., Van der Steen, H., Mileham, A. and Plastow, G. 1996. The estrogen receptor locus is associated with a major gene influencing litter size in pigs. Proceedings of the National Academy of Sciences of the United States of America 93: 201–205.CrossRefGoogle Scholar
Smith, C. 1984. Rates of genetic change in farm livestock. Research and Development in Agriculture 1: 79–85.Google Scholar
Stam, P. and Zeven, A. C. 1981. The theoretical proportion of the donor genome in near-isogenic lines of self-fertilizers bred by backcrossing. Euphytica 30: 227–238.CrossRefGoogle Scholar
Visscher, P. M. 1996. Proportion of the variation in genetic composition in backcrossing programs explained by genetic markers. Journal of Heredity 87: 136–138.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: 691–702.CrossRefGoogle ScholarPubMed
Visscher, P. M., Haley, C. S. and Thompson, R. 1996. Marker assisted introgression in backcross breeding programs. Genetics 144: 1–4.Google Scholar