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

• Published in: Journal of animal science Vol. 90; no. 1; pp. 127 - 141
• Main Authors: Cai, W, Kaiser, M. S, Dekkers, J. C. M
• Format: Journal Article
• Language: English
• Published: United States American Society of Animal Science 2012
• Subjects: additive gene effects; Animal Feed; animal growth; Animal Husbandry - methods; Animal Nutritional Physiological Phenomena; Animals; Bayes Theorem; Bayesian theory; boars; Body Composition; body weight; Eating; environmental impact; feed intake; Female; genetic traits; Genetic Variation; gilts; heritability; line differences; linear models; longitudinal studies; Male; Models, Genetic; Nonlinear Dynamics; nonlinear models; probability; sampling; Selection, Genetic; Sus scrofa - genetics; Sus scrofa - growth & development; Sus scrofa - physiology; swine feeding; Yorkshire (swine breed)
• ISSN: 0021-8812; 1525-3163
• DOI: 10.2527/jas.2011-4293

Gompertz growth functions were fitted to longitudinal measurements of daily feed intake (DFI) and BW of 586 boars and 495 gilts from a selection experiment in Yorkshire pigs for residual feed intake (RFI). The selection experiment consists of a line selected for low residual feed intake (LRFI) for 5 generations and a randomly selected control line (CTRL). The objectives of this study were to use Bayesian methods to estimate genetic parameters of the Gompertz curve parameters for DFI and BW, to evaluate the effect of selection for reduced RFI on the Gompertz parameters and shape of curves for DFI and BW, and to develop methodology for quantifying genetic variation at the level of the original phenotypes for DFI and BW based on the Bayesian analysis of the nonlinear model. Separate analyses were done for boars and gilts and for BW and DFI. A hierarchical model was specified in 2 levels: in the first level, the Gompertz function was modeled for each pig, and at the second level, a 3-trait linear mixed model was fitted to the 3 Gompertz parameters (asymptotic value, inflection point, and decay parameter), with fixed effects of line by generation and random effects of additive genetic and environmental effects. Bayesian methods were used to combine the 2 levels of modeling. A total of 30,000 random samples of the posterior distributions after convergence of Markov chains were used for inference. Posterior means of heritability within the first level of the model for the asymptotic value, inflection point, and decay parameter for DFI were 0.74, 0.66, and 0.82 for boars and 0.79, 0.70, and 0.57 for gilts; corresponding estimates for BW were 0.64, 0.58, and 0.60 for boars and 0.46, 0.35, and 0.33 for gilts. For DFI, LRFI boars had a reduced mature DFI (2.91 vs. 3.20 kg/d) and an earlier inflection point (85 vs. 95 d) compared with CTRL boars. For BW, LRFI boars had a lighter mature BW (279 vs. 317 kg), an earlier inflection point (184 vs. 198 d), and a decreased decay parameter (127 vs. 134 d) compared with CTRL boars. In contrast, LRFI gilts had a later inflection point (225 vs. 200 d) and a greater decay parameter (172 vs. 143 d) than CTRL gilts for BW. The other Gompertz curve parameters for DFI and BW for boars and gilts were considered not different between lines, with posterior probabilities of the line differences being greater than zero ranging from 0.1 to 0.9.