Genetic improvement of lean growth rate and reproductive traits in pigs

Chen, Peiqi
Major Professor
Tom J. Baas
Kenneth J. Koehler
Committee Member
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Animal Science
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Animal Science

Breed-specific genetic parameters for lean growth rate (LGR) and reproductive traits were estimated for the U.S. Yorkshire, Duroc, Hampshire, and Landrace populations. Parameters were estimated using an animal model by REML method. Estimates of heritabilities were 0.44, 0.44, 0.46, and 0.39 for LGR; 0.10, 0.09, 0.08, and 0.08 for number born alive; 0.08, 0.07, 0.08, and 0.09 for litter weight at 21 d; and 0.05, 0.07, 0.05, and 0.05 for number weaned in the Yorkshire, Duroc, Hampshire, and Landrace breeds, respectively. Most genetic correlation estimates between lean growth and litter traits were small but unfavorable across breeds. Backfat thickness had the largest genetic correlations with number born alive (0.18 to 0.20) and litter weight at 21 d (-0.27 to -0.30). A four-generation selection experiment was conducted to investigate the effectiveness of selection for LGR and evaluate the correlated responses in litter traits in a synthetic line of pigs based on a Meishan-Yorkshire cross. The estimate of response to selection per generation was 9.6 +/- 0.95 g/d for LGR. Correlated responses in litter traits were regressed on generation. The regression coefficients were negative but not significant (P > 0.05) for number alive at birth, at 21 d, and at 42 d. A significant positive correlated response occurred only for 42-d litter weight (P < 0.05). Five strategies for selection on LGR in pigs that maximize average LGR at the last generation with a planning horizon based on a non-linear biological function were evaluated through simulation over five generations. A linear index with updating index weights yielded the highest LGR at the last generation. The non-linear index performed almost as well as the linear index with updating. Direct selection on single-trait EBV for LGR yielded the lowest responses at generation 5. Direct selection on multi-trait EBV for LGR yielded 3.1% higher responses in LGR than selection on single-trait EBV for LGR ( P < 0.05). It was concluded that simultaneous genetic improvement in LGR and reproductive traits is possible by using breed-specific genetic parameter estimates or creating a synthetic line through selection for LGR based on a appropriate selection criteria.