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The value of indicator traits in the genetic improvement of dairy cattle

Published online by Cambridge University Press:  02 September 2010

J. A. Woolliams  and
C. Smith
J. A. Woolliams
Affiliation:
AFRC Institute of Animal Physiology and Genetics Research, Edinburgh Research Station, Roslin, Midlothian EH25 9PS
C. Smith
Affiliation:
AFRC Institute of Animal Physiology and Genetics Research, Edinburgh Research Station, Roslin, Midlothian EH25 9PS
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Abstract

The value of indicator traits (7), such as physiological or biochemical traits in the genetic improvement of dairy cattle for milk yield (M) was studied. First, some corrections were made to the base rates of genetic change possible by improvement systems based on progeny testing and on multiple ovulation and embryo transfer (MOET), and on combinations of these. Efficient field progeny-testing systems can be competitive with current adult MOET nucleus herd schemes but juvenile MOET nucleus herd schemes offer substantial increases in rates of response. With high co-heritability, selection for the T alone may allow greater rates of response than those currently considered feasible using progeny testing. However, faster rates are obtained with combined selection. When breeding values are accurately measured by pedigree and performance records on M, as in the progeny test, the extra rates of response with combined selection may be small. Where breeding values are less accurately assessed, as in juvenile MOET nucleus schemes, the extra rates of response can be appreciable. For T with co-heritability (hMrGhT) of 0·27 and the CV for M from 0·15 to 0·20, response rates of 2·0 to 2·7% of the mean per year possible by traditional methods could be increased to 2·2 to 2·9% in progeny testing schemes, 2·3 to 3·1% and to 4·3 to 5·7% for adult and juvenile MOET nucleus schemes respectively.

A possible useful indicator trait is blood urea nitrogen (BUN) measured in young animals after a short fast. Results from four experiments with calves having high or low genetic merit for M were summarized. The pooled co-heritability estimate was —0·27 (s.e. 0·05). With this, or even a more modest effect, BUN would be a useful indicator trait in selection for milk production. Its use in practice in high and low selection lines or in a section of the industry, would allow assessment of the merit of the method.

Type
Research Article
Information
Animal Production , Volume 46 , Issue 3 , June 1988 , pp. 333 - 345
Copyright
Copyright © British Society of Animal Science 1988

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References

REFERENCES

Avalos, E. and Smith, C. 1987. Genetic improvement of litter size in Pigs. Animal Production 44: 153–163.Google Scholar
Brascamp, E. W. 1978. Methods on economic optimisation of animal breeding plans. Research Institute of Animal Husbandry Zeist, Netherlands, pp. 70–72.Google Scholar
Bulmer, M. G. 1971. The effect of selection on genetic variability. American Naturalist 105: 201–211.CrossRefGoogle Scholar
Burrows, r. M. 1984. InbreedingB under selection from related families. Biometrics 40: 895–906.CrossRefGoogle Scholar
Christensen, L. G. 1984. Breeding problems in small cattle populations. 35th Meeting of the European Association of Animal Production, The Hague, Netherlands.Google Scholar
Christensen, L. G. and Liboriussen, T. 1986. Embryo transfer in the genetic improvement of dairy cattle. In Exploiting New Technologies in Animal Breeding: Genetic Developments (ed. Smith, C., King, J. W. B., McKay, C.), pp. 37–46. Clarendon Press, Oxford.Google Scholar
Colleau, J. J. 1985. [Genetic improvement by embryo transfer within selection nuclei in dairy cattle.] Génétique Sélection et Evolution 17: 499–537.CrossRefGoogle Scholar
Falconer, D. S. 1981. Introduction to Quantitative Genetics. 2nd ed. Longman, LondonGoogle Scholar
Fimland, E. 1979. The effect of selection on additive genetic param eters. Zeitschrift fur Tierzuchtung und Zuchtungsbiologie 96: 120–134.CrossRefGoogle Scholar
Gill, J. L., Pirchner, F. and Schwab, M. 1986. Discriminating breeding values of young bulls from their serum concentrations of hormones. Journal of Animal Breeding and Genetics 103: 241–248.CrossRefGoogle Scholar
Hill, W. G. 1972. Estimation of genetic change. 1. General theory and design of control populations. Animal Breeding Abstracts 40: 1–15.Google Scholar
Hill, W. G. 1976. Order statistics of correlated variables and implications in genetic selection programmes. Biometrics 32: 889–902.CrossRefGoogle ScholarPubMed
Hill, W. G. 1977. Order statistics of correlated variables and implications in genetic selection programmes. II. Response to selection. Biometrics 33: 703–712.CrossRefGoogle Scholar
Hill, W. G. 1985. Detection and genetic assessment of physiological criteria of merit within breeds. In Genetics of Reproduction in Sheep (ed. Land, R. B. and Robinson, D. W.), pp. 319–331. Butterworths, London.CrossRefGoogle Scholar
Joakimsen, Ø, Steenberg, K., Lien, H. and Theodorsen, L. 1971. Genetic relationship between thyroxine degradation and fat-corrected milk yield in cattle. Acta Agriculturae Scandinavica 21: 121–124.CrossRefGoogle Scholar
Juga, J. and Maki-Tanila, A. 1987. Genetic change in nucleus breeding daily herds using embryo transfer. Acts Agriculturae Scandinavica 37: 511–519.CrossRefGoogle Scholar
Land, R. B. and Hill, W. G. 1975. The possible use of superovulation and embryo transfer in cattle to increase response to selection. Animal Production 21: 1–12.Google Scholar
Nicholas, F. W. 1979. The genetic implication of multiple ovulation and embryo transfer in small dairy herds. 30th Meeting European Association of Animal Production, Harrogate, Paper G1. 11..CrossRefGoogle 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
Owen, D. B. and Steck, G. P. 1962. Moments of order statistics from the equicorrelated normal distribution. Annals of Mathematical Statistics 33: 1286–1291.CrossRefGoogle Scholar
Rawlings, J. O. 1976. Order statistics for a special class of unequally correlated multinormal varieties. Biometrics 32: 875–887.CrossRefGoogle Scholar
Sales, J. and Hill, W. G. 1976a. Effect of sampling errors on the efficiency of selection indices. 1. Use of information from relatives for single trait improvement. Animal Production 22: 1–17.Google Scholar
Sales, J. and Hill, W. G. 1976b. Effect of sampling errors on the efficiency of selection indices. 2. Use of information on associated traits for improvement of a single important trait. Animal Production 23: 1–14.Google Scholar
Sejrsen, K., Larsen, F. and Andersen, B. B. 1984. Use of plasma hormone and metabolic levels to predict breeding value of young bulls for butterfat production. Animal Production 39: 335–344.Google Scholar
Sinnett-Smith, P. A., Slee, J. and Woolliams, J. A. 1987, Biochemical and physiological responses to metabolic stimuli in Friesian calves of differing genetic merit for milk production. Animal Production 44: 11–19.Google Scholar
Sørensen, M. T., Kruse, V. and Andersen, B. B. 1981. Thyroxine degradation rate in young bulls of Danish dual-purpose breeds. Genetic relationship to weight gain, feed conversion and breeding value for butterfat production. Livestock Production Science 8: 399–406.CrossRefGoogle Scholar
Tilakaratne, N., Alliston, J. C., Carr, W. R., Land, R. B. and Osmond, T. J. 1980. Physiological attributes as possible selection criteria for milk production. 1. Study of metabolites in Friesian calves of high and low genetic merit. Animal Production 30: 327–340.Google Scholar
Walkley, J. R. W. and Smith, C. 1980. The use of physiological traits in genetic selection for litter size in sheep. Journal of Reproduction and Fertility 59: 83–88.CrossRefGoogle ScholarPubMed
Wiener, G., Sinnett-Smith, P. A., Slee, J. and Woolliams, J. A. 1986. Genetic variation in physiological factors relating to livestock improvement. Report of AFRC Animal Breeding Research Organisation, pp. 14–16.Google Scholar
Fieller, E. C. 1944. A fundamental formula in the statistics of biological assay and some applications. Quarterly Journal of Pharmacy and Pharmacology 17: 117–123Google Scholar