Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-08T07:49:18.131Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic analyses of lamb survival in Rambouillet and Finnsheep flocks by linear and threshold models

Published online by Cambridge University Press:  18 August 2016

C. A. P. Matos ,
D. L. Thomas ,
L. D. Young  and
D. Gianola
C. A. P. Matos*
Affiliation:
Department of Animal Sciences, University of Wisconsin-Madison, 256 Animal Sciences Building, 1675 Observatory Drive, Madison, WI 53706-1284, USA
D. L. Thomas*
Affiliation:
Department of Animal Sciences, University of Wisconsin-Madison, 256 Animal Sciences Building, 1675 Observatory Drive, Madison, WI 53706-1284, USA
L. D. Young
Affiliation:
Roman L. Hruska US Meat Animal Research Center, USDA/ARS, Clay Center, NE 68933, USA
D. Gianola
Affiliation:
Department of Animal Sciences, University of Wisconsin-Madison, 256 Animal Sciences Building, 1675 Observatory Drive, Madison, WI 53706-1284, USA
*
†Present address: CEBA, Herdade de Abobada, 7830 Vila N. S. Bento, Portugal.
‡To whom correspondence should be addressed.
Get access

Abstract

Data on lamb survival from birth to weaning of Rambouillet and Finnsheep were analysed with sire-maternal grandsire linear (LM) and threshold (TM) models. Models for the Rambouillet included the effects of year, type of birth, age of dam and sex as fixed effects and sire, maternal grandsire and residual as random effects. For the Finnsheep, fixed effects were year-age of dam combination, type of birth-rearing and sex, and random effects were sire, maternal grandsire and residual. Restricted maximum likelihood (REML) and marginal maximum likelihood (MML) estimates of variance and covariance components were obtained under LM and TM, respectively. The performance of LM and TM was assessed in terms of goodness of fit and predictive ability. Within the Rambouillet breed, heritabilities of additive direct (0·06), additive maternal (0·04) and total effects (0·13) obtained with TM were 2, 1·3 and 1·9 times greater than those obtained with LM, respectively. For the Finnsheep data, estimated heritabilities of direct (0·17), maternal (0·26) and total (0·34) effects using TM were 1·9, 1·4 and 1·6 times greater than the estimates using LM, respectively. Estimated genetic correlation between direct and maternal effects was 0·14 for the Finnsheep with both the LM and TM. Higher genetic correlations between direct and maternal effects (0·44 and 0·62 with LM and TM, respectively) were obtained for the Rambouillet data. Goodness of fit and predictive ability of the models used with the Finnsheep data were better than for the models used with the Rambouillet data, but within breed, no sizable or significant differences were detected between LM and TM. Results indicate that maternal effects were important in lamb survival to weaning; especially in the more prolific Finnsheep breed.

Keywords

heritabilitylambslinear modelsmaternal effectssurvivalthreshold models
Type
Breeding and genetics
Information
Animal Science , Volume 71 , Issue 2 , October 2000 , pp. 227 - 234
Copyright
Copyright © British Society of Animal Science 2000

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

Barwick, S. A., Leymaster, K. A., Keele, J. W. and Harvey, W. R. 1990. Estimates of genetic parameters for lamb survival to weaning and birth weight in the U.S. Suffolk. Proceedings of the eighth conference of the Australian Association of Animal Breeding and Genetics, Hamilton and Palmerston North, New Zealand, pp. 331–334.Google Scholar
Bradford, G. E. 1972. The role of maternal effects in animal breeding. VII. Maternal effects in sheep. Journal of Animal Science 35: 1324–1337.CrossRefGoogle Scholar
Cantet, R. J. C., Kress, D. D., Anderson, D. C., Doornbos, D. E., Burfening, P. J. and Blackwell, R. L. 1988. Direct and maternal variances and covariances and maternal phenotypic effects on preweaning growth of beef cattle. Journal of Animal Science 66: 648–660.Google Scholar
Cundiff, L. V., Gregory, K. E. and Koch, R. M. 1982. Selection for increased survival from birth to weaning. Proceedings of the second world congress on genetics applied to livestock production, Madrid, vol. V, pp. 310–337.Google Scholar
Dalton, D. C., Knight, T. W. and Johnson, D. L. 1980. Lamb survival in sheep breeds on New Zealand hill country. New Zealand Journal of Agricultural Research 23: 167–173.CrossRefGoogle Scholar
Dempster, E. R. and Lerner, I. M. 1950. Heritability of threshold characters. Genetics 35: 212–236.CrossRefGoogle Scholar
Falconer, D. S. 1981. Introduction to quantitative genetics, second edition. Longman, London.Google Scholar
Fogarty, N. M. 1981. Heterosis and genetic parameters for reproduction in sheep. Ph.D. dissertation, University of Nebraska.Google Scholar
Fogarty, N. M. 1995. Genetic parameters for live weight, fat and muscle measurements, wool production and reproduction in sheep: a review. Animal Breeding Abstracts 63: 101–143.Google Scholar
Foulley, J. L. and Manfredi, E. 1991. Approaches statistiques de l’évaluation génétique des reproducteurs pour des caracteres binaires `a seuils. Génétique, Sélection, Évolution 23: 309–338.Google Scholar
Gama, L. T., Dickerson, G. E., Young, L. D. and Leymaster, K. A. 1991. Genetic and phenotypic variation in sources of preweaning lamb mortality. Journal of Animal Science 69: 2744–2753.CrossRefGoogle Scholar
Gianola, D. and Foulley, J. L. 1983. Sire evaluation for ordered categorical data with a threshold model. Génétique, Sélection, Évolution 15: 201–224.Google Scholar
Gianola, D., Im, S. and Macedo, F. W. 1989. A framework for prediction of breeding value. In Advances in statistical methods for genetic improvement of livestock (ed. Gianola, D. and Hammond, K.). Springer-Verlag, Berlin.Google Scholar
Henderson, C. R. 1973. Sire evaluation and genetic trends. Proceedings of the animal breeding and genetics symposium in honor of Dr J. Lush, pp. 10–41. American Society of Animal Science, American Dairy Science Association, American Poultry Science Association, Champaign, Illinois.Google Scholar
Hight, G. K. and Jury, K. E. 1969. Lamb mortality in hill country flocks. Proceedings of the New Zealand Society of Animal Production 29: 219–232.Google Scholar
Misztal, I., Gianola, D. and Foulley, J. L. 1989. Computing aspects of a nonlinear method of sire evaluation for categorical data. Journal of Dairy Science 72: 1557–1568.Google Scholar
Notter, D. R. 1981. Repeatability of conception rate and litter size for ewes in an accelerated lambing system. Journal of Animal Science 53: 643–650.CrossRefGoogle Scholar
Perez-Enciso, M., Tempelman, R. J. and Gianola, D. 1993. A comparison between linear and Poisson mixed models for litter size in Iberian pigs. Livestock Production Science 35: 303–312.CrossRefGoogle Scholar
Petersson, C. J. and Danell, Ö. 1985. Factors influencing lamb survival in four Swedish sheep breeds. Acta Agriculturæ Scandinavica 35: 217–232.Google Scholar
Robison, O. W. 1981. The influence of maternal effects on the efficiency of selection; a review. Livestock Production Science 8: 121–137.CrossRefGoogle Scholar
Ron, M., Bar-Anan, R. and Weller, J. I. 1986. Sire and maternal grandsire effects on calving difficulty and calf mortality in Israeli Holsteins. Journal of Dairy Science 69: 243–247.Google Scholar
Ron, M., Ezra, E. and Weller, J. I. 1990. Genetic analysis of twinning rate in Israeli Holstein cattle. Génétique, Sélection, Évolution 22: 349–359.Google Scholar
Shelton, M. and Menzies, J. W. 1970. Repeatability and heritability of components of reproductive efficiency in fine-wool sheep. Journal of Animal Science 30: 1–5.Google Scholar
Smith, G. M. 1977. Factors affecting birth weight, dystocia and preweaning survival in sheep. Journal of Animal Science 44: 745–753.Google Scholar
Statistical Analysis Systems Institute. 1986. User’s guide: statistics. Statistical Analysis Systems Institute Inc., Cary, NC.Google Scholar
Thompson, R. 1979. Sire evaluation. Biometrics 35: 339–353.Google Scholar
Waldron, D. F. and Thomas, D. L. 1992. Increased litter size in Rambouillet sheep. I. Estimation of genetic parameters. Journal of Animal Science 70: 3333–3344.Google Scholar
Wallace, M. H. and Ross, G. S. 1991. Sheep facilities and flock management at MARC. Progress report no. 4, sheep research program, Agricultural Research Service, US Department of Agriculture.Google Scholar
Weller, J. I., Misztal, I. and Gianola, D. 1988. Genetic analysis of dystocia and calf mortality in Israel-Holsteins by threshold and linear models. Journal of Dairy Science 71: 2491–2501.Google Scholar
Wiener, G., Woolliams, C. and Macleod, N. S. M. 1983. The effects of breed, breeding system and other factors on lamb mortality. 1. Causes of death and effects on the incidence of losses. Journal of Agricultural Science, Cambridge 100: 539–551.CrossRefGoogle Scholar
Willham, R. L. 1963. The covariance between relatives for characters composed of components contributed by related animals. Biometrics 19: 18–27.Google Scholar
Willham, R. L. 1972. The role of maternal effects in animal breeding. III. Biometrical aspects of maternal effects in animals. Journal of Animal Science 35: 1288–1293.Google Scholar
Wright, S. 1934. An analysis of variability in number of digits in an inbred strain of guinea pigs. Genetics 19: 506–536.Google Scholar
Zellner, A. 1971. An introduction to Bayesian inference in econometrics. John Wiley and Sons, New York.Google Scholar