A dynamic deterministic model to optimize a multiple-trait selection scheme
2009
Devalle Costard, Anne | Vitezica, Zulma | Moreno-Romieux, Carole | Elsen, Jean Michel, J. M. | Station d'Amélioration Génétique des Animaux (SAGA) ; Institut National de la Recherche Agronomique (INRA) | Tissus animaux, nutrition, digestion, écosystème et métabolisme (TANDEM) ; Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT) ; Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT) ; Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT)-Université de Toulouse (UT)
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Show more [+] Less [-]English. A mathematical approach was developed to model and optimize simultaneous selection on 2 traits, a quantitative trait with underlying polygenic variation and a monogenic trait (e.g., resistance to a disease). A deterministic model allows global optimization of the selection scheme to maximize the frequency of the desired genotype for the monogenic trait, while minimizing the loss of genetic progress on the polygenic trait. An additive QTL or gene was considered. Breeding programs with overlapping generations, different selection strategies for males and females, and assortative mating were modeled. A genetic algorithm was used to solve this optimization problem. This modeling approach may easily be adapted to a variety of underlying genetic models and selection schemes. This model was applied to an example where selection on the Prp gene for scrapie resistance was introduced as an additional selection criterion in an already existing dairy sheep selection scheme.
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