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Combining the genetic and clonal responses in a closed dairy cattle nucleus scheme

Published online by Cambridge University Press:  02 September 2010

I. J. M. de Boer ,
T. H. E. Meuwissen  and
J. A. M. van Arendonk
I. J. M. de Boer
Affiliation:
Department of Animal Breeding, Wageningen Agricultural University, PO Box 338, 6700 AH Wageningen, The Netherlands
T. H. E. Meuwissen
Affiliation:
Research Institute for Animal Production ‘Schoonoord’, PO Box 501, 3700 AM Zeist, The Netherlands
J. A. M. van Arendonk
Affiliation:
Department of Animal Breeding, Wageningen Agricultural University, PO Box 338, 6700 AH Wageningen, The Netherlands
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Abstract

Designs testing clones in a closed nucleus, in which 1024 cows are tested each year, were compared for their additive genetic response to selection (genetic response) and their genetic superiority of female genotype(s) selected for commercial cloning (clonal response), using stochastic simulation. Clones were tested at the expense of dam or sire families, matings per dam (sire), or full-sibs per family. The reference design maximized the genetic response corrected for inbreeding in the absence of cloning. The trait considered was overall economic merit for milk production, which was simulated assuming an approximate infinitesimal model with both additive and dominant gene action. Bulls and cows eligible for breeding were selected on their animal model estimated additive genetic effect at either 15 or 27 months of age. Female genotypes eligible for commercial cloning were selected on their estimated total genetic effect at 27 months of age. All (fe)male full-sibs were available for selection. With only additive gene action, testing clones at the expense of sire families, matings per dam or full-sibs per family reduced genetic response, while it increased clonal response and inbreeding. Testing clones at the expense of dam families, however, added to both the genetic and clonal response without increasing inbreeding. When eight clones were tested at the expense of dam families, the genetic response and the final genetic level of commercially available cloned embryos were maximal. Accuracy of clonal selection equalled 0·83. With dominant gene action, however, testing two clones at the expense of dam families maximized the final genetic level of cloned embryos, irrespective of the level of inbreeding depression (accuracy of 0·72). Reliable commercial clone lines can be produced now and in future generations by testing clones at the expense of dam families.

Keywords

breeding programmescloningdairy cattle
Type
Research Article
Information
Animal Production , Volume 59 , Issue 3 , December 1994 , pp. 345 - 358
Copyright
Copyright © British Society of Animal Science 1994

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References

Balaine, D. S., Pearson, R. E. and Miller, R. H. 1981. Profit functions in dairy cattle and effect of measures of efficiency and prices. journal of Dairy Science 64: 87–95.Google Scholar
Boer, I. J. M. de. 1994. The use of clones in dairy cattle breeding. Ph.D. thesis, Wageningen Agricultural University, Wageningen.Google Scholar
Boer, I. J. M. de and Arendonk, J. A. M. van 1991. Genetic and clonal responses in dairy cattle nucleus schemes. Animal Production 53: 1–9.Google Scholar
Boer, I. J. M. de and Arendonk, J. A. M. van 1992. Prediction of additive and dominance effects in selected or unselected populations with inbreeding. Theoretical and Applied Genetics 84: 451–459.Google Scholar
Boer, I. J. M. de and Arendonk, J. A. M. van 1994. Additive response to selection adjusted for effects of inbreeding in a closed dairy cattle nucleus assuming a large number of gametes per female. Animal Production 58: 173–180.CrossRefGoogle Scholar
Boer, I. J. M. de and Hoeschele, I. 1993. Genetic evaluation methods for populations with dominance and inbreeding. Theoretical and Applied Genetics 86: 245–258.Google Scholar
Bulmer, M. G. 1980. The mathematical theory of quantitative genetics. Clarendon Press, Oxford.Google Scholar
Burrows, P. M. 1972. Expected selection differentials for directional selection. Biometrics 28: 1091–1100.Google Scholar
Colleau, J. J. 1992. Combining use of embryo sexing and cloning within mixed MOETS for selection on dairy cattle. Genetics Selection and Evolution 24: 345–361.Google Scholar
Dekkers, J. C. M. 1989. Economic evaluation of breeding programs for commercial artificial insemination organizations in dairy cattle. Ph.D. thesis, University of Wisconsin, Madison.Google Scholar
Dempfle, L. 1990. Statistical aspects of design of animal breeding programs: a comparison among various selection strategies. In Advances in statistical methods for genetic improvement of livestock (ed. Gianola, D. and Hammond, K.), pp. 98–117. Springer-Verlag, Berlin, Heidelberg.Google Scholar
Falconer, D. S. 1989. Introduction to quantitative genetics. John Wiley, New York.Google Scholar
Fürst, C. and Sölkner, J. 1994. Additive and nonadditive genetic variances for milk production, fertility and lifetime peformance traits in purebred and crossbred cattle populations. Journal of Dairy Science 77: 1114–1125.Google Scholar
Goddard, M. E. and Smith, C. 1990. Adjustment of sires' estimated breeding values for their prospective inbreeding impact on the breed. journal of Dairy Science 73: suppl. 1, p. 223.Google Scholar
Henderson, C. R. 1973. Sire evaluation and genetic trends. Proceedings of the animal breeding and genetics symposium in honor of J. L. Lush, American Society of Animal Science, American Dairy Science Association, American Poultry Science Association, Champaign, Illinois, pp. 10–41.Google Scholar
Henderson, C. R. 1975. Rapid method for computing the inverse of a relationship matrix. Journal of Dairy Science 58: 1727-1730.Google Scholar
Hill, W. G. 1976. Order statistics of correlated variables and implications in genetic selection programs. Biometrics 32: 889–902.CrossRefGoogle Scholar
Hoeschele, I. and VanRaden, P. M. 1991. Rapid inversion of dominance relationship matrices for noninbred populations by including sire by dam subclass effects. journal of Dairy Science 74: 557–569.Google Scholar
Keller, D. S., Gearheart, W. W. and Smith, C. 1990. A comparison of factors reducing selection response in closed nucleus breeding schemes. Journal of Animal Science 68: 1553–1561.Google Scholar
Meuwissen, T. H. E. 1990. The effect of the size of MOET nucleus dairy cattle breeding plans on the genetic gain and its variance. Proceedings of the fourth world congress on genetics applied to livestock production, Edinburgh, vol. XIV, pp. 271–274.Google Scholar
Meuwissen, T. H. E. 1991. Reduction in selection differentials in finite populations with a nested full-half sib family structure. Biometrics 47: 195–203.Google Scholar
Nicholas, F. W. and Smith, C. 1983. Increased rates of genetic change in dairy cattle by embryo transfer and splitting. Animal Production 36: 341–353.Google Scholar
Quaas, R. L. 1988. Additive genetic model with groups and relationships. Journal of Dairy Science 71: 1338–1345.Google Scholar
Rawlings, J. O. 1976. Order statistics for a special class of unequally correlated multinormal variates. Biometrics 32: 875–887.Google Scholar
Ruane, J. 1989. Evaluation of genetic improvement programmes using multiple ovulation and embryo transfer in dairy cattle. Ph.D. thesis, University of Edinburgh.Google Scholar
Ruane, J. 1991. The effect of alternative mating designs and selection strategies on adult multiple ovulation and embryos transfer (MOET) nucleus breeding schemes in dairy cattle. Genetics Selection and Evolution 23: 47–65.Google Scholar
Schaeffer, L. R. and Kennedy, B. W. 1986. Computing solutions to mixed model equations. Proceedings of the third world congress on genetics applied to livestock production, Lincoln, Vol. XII, pp. 382–393.Google Scholar
Schrooten, C. and Arendonk, J. A. M. van 1992. Stochastic simulation of dairy cattle breeding schemes: genetic evaluation of nucleus size and type. journal of Animal Breeding Genetics 109: 1–15.Google Scholar
Searle, S. R. 1971. Linear models. John Wiley, New York.Google Scholar
Smith, C. 1989. Cloning and genetic improvement of beef cattle. Animal Production 49: 49–62.Google Scholar
Teepker, G. and Smith, C. 1989. Combining clonal response and genetic response in dairy cattle improvement. Animal Production 49: 163–169.Google Scholar
Tempelman, R. J. and Burnside, E. B. 1991. Additive and dominance genetic variation for dairy production traits under an animal model. Journal of Animal Breeding and Genetics 108: 330–342.Google Scholar
Tier, B. 1990. Computing inbreeding coefficients quickly. Genetics Selection and Evolution 22: 419–430.Google Scholar
VanRaden, P. M. 1989. Estimates of nonadditive genetic variation for milk and fat yields of Holsteins. Journal of Dairy Science 72: suppl. 1, p. 59.Google Scholar
Van Vleck, L. D. 1981. Potential genetic impact of artificial insemination, sex selection, embryo transfer, cloning and selfing in dairy cattle. In New technologies in animal breeding (ed. Bracket, B. C. and Seidel, S. M.), pp. 221–242. Academic Press, London.Google Scholar
Wei, M. and Van der Werf, J. H. J. 1993. Animal model estimation of additive and dominance variances in egg production traits of poultry. journal of Animal Science 71: 57–65.Google Scholar
Westell, R. A., Quaas, R. L. and Van Vleck, L. D. 1988. Genetic groups in an animal model. journal of Dairy Science 71: 1310–1318.Google Scholar
Woolliams, J. A. 1989. The value of cloning in MOET nucleus breeding schemes for dairy cattle. Animal Production 48: 31–35.Google Scholar
Woolliams, J. A. and Meuwissen, T. H. E. 1993. Decision rules and variance of response in breeding schemes. Animal Production 56: 179–186.Google Scholar
Wray, N. R. 1989. Consequences of selection in closed populations with special reference to closed nucleus herds of pigs. Ph.D. thesis, University of Edinburgh.Google Scholar