J. Anim Sci.
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J. Anim. Sci. 2004. 82:1305-1314
© 2004 American Society of Animal Science

ANIMAL GENETICS

Maximizing genetic gain over multiple generations with quantitative trait locus selection and control of inbreeding1

B. Villanueva*,2, J. C. M. Dekkers{dagger}, J. A. Woolliams{ddagger} and P. Settar{dagger}

* Scottish Agricultural College, Edinburgh, EH9 3JG, Scotland, U.K.; and {dagger} Department of Animal Science, Iowa State University, Ames 50011-3150; and and {ddagger} Roslin Institute (Edinburgh), Roslin, Midlothian, EH25 9PS, Scotland, U.K.

2 Correspondence: Sustainable Livestock Systems Group, Bush Estate, Penicuik, Midlothian EH26 0PH, Scotland, U.K. (phone: +44-131-535-3224; fax: +44-131-535-3121; e-mail: b.villanueva{at}ed.sac.ac.uk).

Abstract

Stochastic computer simulation was used to investigate the potential extra genetic gains obtained from gene-assisted selection (GAS) by combining 1) optimization of genetic contributions for maximizing gain, while restricting the rate of inbreeding with 2) optimization of the relative emphasis given to the QTL over generations. The genetic model assumed implied a mixed inheritance model in which a single quantitative trait locus (i.e., QTL) is segregating together with polygenes. When compared with standard GAS (i.e., fixed contributions and equal emphasis on the QTL and polygenic EBV), combined optimization of contributions of selection candidates and weights on the QTL across generations allowed substantial increases in gain at a fixed rate of inbreeding and avoided the conflict between short- and long-term responses in GAS schemes. Most of the increase of gain was produced by optimization of selection candidates’ contributions. Optimization of the relative emphasis given to the QTL over generations had, however, a greater effect on avoiding the long-term loss usually observed in GAS schemes. Optimized contribution schemes led to lower gametic phase disequilibrium between the QTL and polygenes and to higher selection intensities both on the QTL and polygenes than with standard truncation selection with fixed contributions of selection candidates.

Key Words: Gene-Assisted Selection • Genetic Gain • Optimization • Optimized Contributions Selection • Restricted Inbreeding






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