Intérêt de la sélection génomique dans les programmes de sélection porcins : cas d'une lignée mâle de grande taille

Abstract : The aim of this work was to evaluate the interest of implementing genomic evaluations in pig breeding schemes. Stochastic simulation was used. The simulated population was a pig sire line containing 1,050 breeding females and 50 boars. The line was selected for 10 years for a breeding goal including two uncorrelated traits, recorded on, respectively, 13,770 candidates per year (trait1) and 270 relatives per year born in 10% of the litters (trait2). In the reference breeding scheme (BLUPAM), the selection was based on pedigree-based BLUP estimated breeding values (EBVs). In a first study, we compared the BLUPAM scenario to an alternative genomic breeding scheme with the same phenotyping capacities, where all candidates for selection were genotyped. The genomic breeding values for trait1 and trait2 were estimated using two training populations (TP). The first one (TP1) was made up of selection candidates (phenotyped for trait1) and the second one (TP2) of relatives phenotyped for trait2. The size of TP1 and TP2 increased, respectively, from 13,770 to 55,080 and from 1,000 to 3,430 over time. Our results show that genomic evaluations significantly improve the accuracy of the EBVs of the candidates for both traits and therefore the annual genetic trends for the global breeding goal (+27% to +33% depending on trait heritability), while significantly reducing the inbreeding rate. A second genomic scenario was simulated, in which the candidates were no longer phenotyped for trait1, and the genomic breeding values were estimated with one single TP made up of relatives phenotyped for both traits. In that case, the accuracy of EBVs and the annual genetic trends for trait1 are significantly lower than in the reference (BLUPAM) scenario. This shows that a large TP is required to outperform the current schemes for traits recorded on the candidates. The implementation of genomic evaluations requires the genotyping of a large number of animals, and therefore generates additional costs compared to BLUPAM breeding schemes. In a second study, we showed that genotyping a subset of candidates that have been pre-selected according to their parental EBV allows to significantly reduce the extra costs of a genomic breeding scheme while preserving most of its superiority in terms of genetic trends and inbreeding over the BLUPAM breeding scheme. For instance, reducing the number of genotyped candidates by 40% only reduced by 3 to 4% the global annual genetic trend. We also showed that even a very marked increase in the number of relatives phenotyped for trait2 in a BLUPAM scenario does not allow to be as efficient as a genomic scenario when the number of genotyped candidates is large. Finally, we showed that the economic interest of genetic selection can be characterized by an additional cost threshold; below this threshold, it is preferable to maintain pedigree-based BLUP evaluations and increase the number of relatives, while implementing genomic evaluation is more efficient above this threshold. The value of this threshold depends on the cost of phenotyping additional relatives and on genotyping costs.Our results suggest that implementing genomic evaluations in a large size pig sire line can be a valuable strategy. This strategy could for instance easily be applied to the French Piétrain population, which resembles the nucleus population simulated in this study.
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Thierry Tribout. Intérêt de la sélection génomique dans les programmes de sélection porcins : cas d'une lignée mâle de grande taille. Sciences agricoles. AgroParisTech, 2013. Français. ⟨NNT : 2013AGPT0054⟩. ⟨tel-01135169⟩

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