Hostname: page-component-77c89778f8-sh8wx Total loading time: 0 Render date: 2024-07-21T10:58:54.673Z Has data issue: false hasContentIssue false
  • English
  • Français

The impact of different genetic models on the optimum design of crossbreeding experiments

Published online by Cambridge University Press:  02 September 2010

J. Sölkner
J. Sölkner
Affiliation:
Institut für Nutztierwissenschaften, Universität für Bodenkultur, Gregor-Mendel-Strasse 33, A-1180 Wien, Austria
Get access

Abstract

A method for the iterative set-up of optimum designs for crossbreeding experiments was used to study the robustness of designs to differences in the biological interpretation of two-locus epistatic interaction. Designs could be found which are efficient for the estimation of genetic models including, alternatively, seven different types of epistatic effects. Also, the design efficiency of a large-scale beef cattle crossbreeding experiment between Angus and Hereford cattle conducted at the Clay Center, Nebraska, and reported by Koch, Dickerson, Cundiff and Gregory (1985) was investigated and found to be high (proportionately 0·88 of the optimum). It was concluded that choice of the right genetic groups (i.e. types of crossbreds) seems to be more important for a good design than the exact number of observations allocated to each group.

Keywords

cattlecrossbreedingexperimental designgenetic models
Type
Research Article
Information
Animal Production , Volume 52 , Issue 2 , April 1991 , pp. 255 - 262
Copyright
Copyright © British Society of Animal Science 1991

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

REFERENCES

Anderson, V. L. and Kempthorne, O. 1954. A model for the study of quantitative inheritance. Genetics 39: 883–898.CrossRefGoogle Scholar
Atkinson, A. C. 1988. Recent developments in the methods of optimum and related designs. International Statistical Review 56: 99–115.CrossRefGoogle Scholar
Atkinson, A. C. and Cox, D. R. 1974. Planning experiments for discriminating between models (with discussion). Journal of the Royal Statistical Society B 36: 321–348.Google Scholar
Aumann, J. 1986. Modellversuch mit Mausen zur Schatzung von Kreuzungswirkungen unter Beriicksichtigung der Epistasie. Dissertation München, Weihenstephan.Google Scholar
Cameron, N. D. and Thompson, R. 1986. Design of multivariate selection experiments. Theoretical and Applied Genetics 72: 466–476.CrossRefGoogle ScholarPubMed
Cockerham, C. C. 1954. An extension of the concept of partitioning hereditary variance for analysis of covariances among relatives when epistasis is present. Genetics, USA 39: 859–882.CrossRefGoogle ScholarPubMed
Dickerson, G. E. 1969. Experimental approaches in utilising breed resources. Animal Breeding Abstracts 37: 191–202.Google Scholar
Dickerson, G. E. 1973. Inbreeding and heterosis in animals. Proceedings of the Animal Breeding and Genetics Symposium in honour of Dr J. L. Lush in Blacksburg, Virginia. ASAS and ADSA, pp. 54–77.Google Scholar
Hagger, C. 1989. Genetic effects estimated from crosses and backcrosses of two related lines of White Leghorn chickens. Journal of Animal Breeding and Genetics 106: 241–248.CrossRefGoogle Scholar
Henderson, C. R. 1973. Sire evaluation and genetic trends. Proceedings of the Animal Breeding and Genetics Symposium in honour of Dr J. L. Lush in Blacksburg, Virginia. ASAS and ADSA, pp. 10–41.Google Scholar
Hill, W. G. 1982. Dominance and epistasis as components of heterosis. Zeitschrift fur Tierzuchtung und Zuchtungsbiologie 99: 161–168.CrossRefGoogle Scholar
Kinghorn, B. 1980. The expression of “recombination loss” in quantitative traits. Zeitschrift fur Tierzuchtung und Zuchtungsbiologie 97: 138–143.CrossRefGoogle Scholar
Kinghorn, B. 1982. Genetic effects in crossbreeding. I. Models of merit. Zeitschrift fur Tierzuchtung und Zuchtungsbiologie 99: 59–68.CrossRefGoogle Scholar
Kinghorn, B. 1987. The nature of 2-locus epistatic interactions in animals: evidence from Sewall Wright's guinea pig data. Theoretical and Applied Genetics 73: 595–604.CrossRefGoogle ScholarPubMed
Kinghorn, B. P. and Vercoe, P. E. 1989. The effects of using the wrong genetic model to predict the merit of crossbred genotypes. Animal Production 49: 209–216.Google Scholar
Koch, R. M., Dickerson, G. E., Cundiff, L. V. and Gregory, K. E. 1985. Heterosis retained in advanced generations of crosses among Angus and Hereford cattle. Journal of Animal Science 60: 1117–1132.CrossRefGoogle ScholarPubMed
Nitter, G. 1985. Parameter in der Kreuzungszucht. Hohenheimer Arbeiten 131: 49–68.Google Scholar
Pedersen, J. and Christensen, L. G. 1989. Heterosis for milk production traits by crossing Red Danish, Finnish Ayrshire and Holstein-Friesian cattle. Livestock Production Science 23: 253–266.CrossRefGoogle Scholar
St John, R. C. and Draper, N. R. 1975. D-optimality for regression designs: a review. Technometrics 17: 15–23.CrossRefGoogle Scholar
Searle, S. R. 1966. Matrix Algebra for the Biological Sciences. John Wiley, New York.Google Scholar
Solkner, J. and James, J. W. 1990a. Optimum design of crossbreeding experiments. I. A basic sequential procedure. Journal of Animal Breeding and Genetics 107: 61–67.CrossRefGoogle Scholar
Solkner, J. and James, J. W. 1990b. Optimum design of crossbreeding experiments II. Optimum relationship structures of animals within and between genetic groups. Journal of Animal Breeding and Genetics 107: 411–420.CrossRefGoogle Scholar