Bayesian analysis of the effect of selection for residual feed intake on growth and feed intake curves in Yorkshire swine

Journal of Animal Science

Volumn 90, Issue 1, 2012, Pages 127-141

  Cai, W ^a,b,c   Kaiser, M S ^b   Dekkers, J C M ^a,c  

^a Department of Animal Science ^*  (United States)

^b IOWA STATE UNIVERSITY   (United States)

^c PIONEER HI BRED INTERNATIONAL INC   (United States)

Author keywords

Bayesian analysis; Growth curve; Pig; Residual feed intake; Selection

Indexed keywords

ANIMAL; ANIMAL FOOD; ANIMAL HUSBANDRY; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; BODY COMPOSITION; EATING; EVALUATION STUDY; FEMALE; GENETIC SELECTION; GENETIC VARIABILITY; GENETICS; GROWTH, DEVELOPMENT AND AGING; MALE; METHODOLOGY; NONLINEAR SYSTEM; PHYSIOLOGY; SWINE;

ANIMAL FEED; ANIMAL HUSBANDRY; ANIMAL NUTRITIONAL PHYSIOLOGICAL PHENOMENA; ANIMALS; BAYES THEOREM; BODY COMPOSITION; EATING; FEMALE; GENETIC VARIATION; MALE; MODELS, GENETIC; NONLINEAR DYNAMICS; SELECTION, GENETIC; SUS SCROFA;

EID: 84855373657     PISSN: 00218812     EISSN: 15253163     Source Type: Journal    
DOI: 10.2527/jas.2011-4293     Document Type: Article

References (24)

1. Barbato, G. F. 1991. Genetic architecture of growth curve parameters in chickens. Theor. Appl. Genet. 83:24-32.
2. Blasco, A., M. Piles, and L. Varona. 2003. A Bayesian analysis of the effect of selection for growth rate on growth curves in rabbits. Genet. Sel. Evol. 35:21-41.
3. Cai, W., D. S. Casey, and J. C. M. Dekkers. 2008. Selection response and genetic parameters for residual feed intake in Yorkshire swine. J. Anim. Sci. 86:287-298.
4. Cai, W., M. S. Kaiser, and J. C. M. Dekkers. 2011b. Genetic analysis of longitudinal measurements of performance traits in selection lines for residual feed intake in Yorkshire swine. J. Anim. Sci. 89:1270-1280.
5. Cai, W., H. Wu, and J. C. M. Dekkers. 2011a. Longitudinal analysis of body weight and feed intake in selection lines for residual feed intake in pigs. Asian-australas. J. Anim. Sci. 24:17-27.
6. Clutter, A. C., and E. W. Brascamp. 1998. Genetics of performance traits. Pages 427-455 in The Genetics of the Pig. M. F. Rothschild and A. Ruvinsky, ed. CAB Int., Wallingford, UK.
7. Emmans, G. C., and I. Kyriazakis. 1999. Growth and body composition. Pages 181-197 in A Quantitative Biology of the Pig. I. Kyriazakis, ed. CAB Int., Wallingford, UK.
8. Gelman, A., and D. B. Rubin. 1992. Inference from iterative simulation using multiple sequences. Stat. Sci. 7:457-511.
9. Gilmour, A. R., B. J. Gogel, B. R. Cullis, and R. Thompson. 2006. ASReml User Guide Release 2.0. VSN International Ltd., Hemel Hempstead, UK.
10. Henderson, C. R. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics 31:423-447.
11. Henderson, C. R., O. Kempthorne, S. R. Searle, and C. M. Von Krosigk. 1959. The estimation of environmental and genetic trends from records subject to culling. Biometrics 15:192-218.
12. Kachman, S. D., R. L. Baker, and D. Gianola. 1988. Phenotypic and genetic variability of estimated growth curve parameters in mice. Theor. Appl. Genet. 76:148-156.
13. Koivula, M., M. L. Sevón-Aimonen, I. Strandén, K. Matilainen, T. Serenius, K. J. Stalder, and E. A. Mäntysaari. 2008. Genetic (co)variances and breeding value estimation of Gompertz growth curve parameters in Finnish Yorkshire boars, gilts and barrows. J. Anim. Breed. Genet. 125:168-175.
14. Liu, H. H. 2000. Efficiency of Markov chain Monte Carlo algorithms for Bayesian inference in random regression models. PhD Diss. Iowa State Univ., Ames.
15. Piles, M., D. Gianola, L. Varona, and A. Blasco. 2003. Bayesian inference about parameters of a longitudinal trajectory when selection operates on a correlated trait. J. Anim. Sci. 81:2714-2724.
16. Ratkowsky, D. A. 1990. Handbook of nonlinear regression models. Marcel Dekker Inc., New York, NY.
17. R Development Core Team. 2010. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org.
18. Sorensen, D. A., and B. W. Kennedy. 1984. Estimation of response to selection using least-squares and mixed model methodology. J. Anim. Sci. 58:1097-1106.
19. Sorensen, D. A., and B. W. Kennedy. 1986. Analysis of selection experiments using mixed model methodology. J. Anim. Sci. 63:245-258.
20. Varona, L., C. Moreno, L. A. G. Cortes, and J. Altarriba. 1997. Multiple trait genetic analysis of underlying biological variables of production functions. Livest. Prod. Sci. 47:201-209.
21. Varona, L., C. Moreno, L. A. G. Cortes, and J. Altarriba. 1998. Bayesian analysis of Wood's lactation curve for Spanish dairy cows. J. Dairy Sci. 81:1469-1478.
22. Whittemore, C. T., J. B. Tullis, and G. C. Emmans. 1988. Protein growth in pigs. Anim. Prod. 46:437-445.
23. Wright, D. R., H. S. Stern, and P. J. Berger. 2000. Comparing traditional and Bayesian analyses of selection experiments in animal breeding. J. Agric. Biol. Environ. Stat. 5:240-256.
24. Wu, R., and M. Lin. 2006. Functional mapping-How to map and study the genetic architecture of dynamic complex traits. Nat. Rev. Genet. 7:229-237.