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Genotype × environment interactions for early growth and ultrasonic measurements in hill sheep

Published online by Cambridge University Press:  02 September 2010

S. C. Bishop
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
J. Conington
Affiliation:
Genetics and Behavioural Sciences Department, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
A. Waterhouse
Affiliation:
Department of Grassland and Ruminant Science, Scottish Agricultural College, Auchincruive, Ayr KA6 5HW
G. Simm
Affiliation:
Genetics and Behavioural Sciences Department, Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
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Abstract

Genotype × environment and genotype × sex interactions were investigated using lines of Scottish Blackface sheep that had been divergently selected under intensive husbandry conditions for predicted carcass lean proportion, and offspring of rams from these selection lines which were reared under extensive hill conditions. Traits considered were live weight and ultrasonic fat and muscle depth. These were measured at 20 weeks of age on the intensively reared lambs and at 17 weeks of age on the extensively reared animals. Heritabilities for the two environments were 0-39 and 0-20 for fat depth, 0-36 and 0-25 for muscle depth and 0-23 and 0-12 for live weight. Genetic correlations between the environments were 0-54 (s.e. 0-17), 0-90 (s.e. 0-14) and 0-11 (s.e. 0-43) for fat depth, muscle depth and live weight, respectively. The extensive environment may be subdivided according to whether the lambs are reared on improved pasture or on the hill side. The genetic correlations (with s.e.s where estimable) between performance in these two environments were 0-70 (s.e. 0-33), 0-71 (s.e. 0-23) and 1-00 for fat depth, muscle depth and live weight. Genetic correlations between male and female performance under extensive conditions were 0-84 (s.e. 0-28), 0-99 (s.e. 0-14) and 1-00 for fat depth, muscle depth and live weight. T-or fat depth, the genetic correlations of the intensively reared lambs (males only) with extensively reared females and males were 0-37 (s.e. 0-22) and 0-67 (s.e. 0-17), respectively.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1996

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References

REFERENCES

Bailey, D. R. C., Gilbert, R. P. and Lawson, J. E. 1990. Lack of sire by diet interaction in Hereford and Angus calves fed one of two diets. Proceedings of the fourth world congress genetics applied to livestock production, vol. XV, pp. 307310.Google Scholar
Baker, J. F., Neville, W. E. and Utley, P. R. 1991. Evaluation of genotype-environment interactions of beef bulls tested in feedlot or on pasture. Journal of Animal Science 69: Suppl. 1, p. 217.Google Scholar
Bishop, S. C. 1993a. Grassland performance of Hereford cattle selected for rate and efficiency of lean gain on a concentrate diet Animal Production 56: 311319.Google Scholar
Bishop, S. C. 1993b. Selection for predicted carcass lean content in Scottish Blackface sheep Animal Production 56: 379386.Google Scholar
Cameron, N. D. 1992. Correlated responses in slaughter and carcass traits of crossbred progeny to selection for carcass lean content in sheep Animal Production 54: 379388.Google Scholar
Conington, J., Bishop, S. C., Waterhouse, A. and Simm, G. 1995. A genetic analysis of early growth and ultrasonic measurements in hill sheep Animal Science 61: 8593.CrossRefGoogle Scholar
Dickerson, G. E. 1962. Implications of genetic environmental interaction in animal breeding Animal Production 4: 4764.Google Scholar
Frisch, J. E. 1981. Changes occurring in cattle as a consequence of selection for growth rate in a stressful environment Journal of Agricultural Science, Cambridge 96: 2338.CrossRefGoogle Scholar
Hough, J. D. and Benyshek, L. L. 1988. Effect of pre-weaning nutritional management on yearling weight response in an open-herd selection program, journal of Animal Science 66: 25082516.Google Scholar
Lawes Agricultural Trust. 1983. GENSTAT a general statistical program. Numerical Algorithms Group Limited.Google Scholar
Lewis, R. M., Simm, G., Dingwall, W. S. and Murphy, S. V. 1996. Selection for lean growth in terminal sires to produce leaner crossbred progeny. Animal Science In press.Google Scholar
Merks, J. W. M. 1989. Genotype × environment interactions in pig breeding programmes. VI. Genetic relations between performance in central test, on-farm test and commercial fattening. Livestock Production Science 22: 325339.CrossRefGoogle Scholar
Meyer, K. 1989. Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm Genctiaue, Selection el Evolution 21: 317340.CrossRefGoogle Scholar
Simm, G. and Murphy, S. V. 1996. The effects of selection for lean growth in Suffolk sires on the saleable meat yield of their crossbred progeny Animal Science 62: 255263.CrossRefGoogle Scholar
Thompson, R., Crump, R. E., Juga, J. and Visscher, P. M. 1995. Estimating variances and covariances for bivariate onanimal models using scaling and transformation. Genetics, Selection, Evolution 11: 3342.CrossRefGoogle Scholar