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Open Access Technical Note

The power to detect artificial selection acting on single loci in recently domesticated species

Sten Karlsson1* and Thomas Moen23

Author Affiliations

1 NOFIMA Marine, Arboretveien 6, N-1432 Ås, Norway

2 Aqua Gen AS, Postboks 1240, 7462 Trondheim, Norway

3 CIGENE, Arboretveien 6, N-1432 Ås, Norway

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BMC Research Notes 2010, 3:232  doi:10.1186/1756-0500-3-232

Published: 26 August 2010

Abstract

Background

An increasing number of aquaculture species are subjected to artificial selection in systematic breeding programs. Rapid improvements of important commercial traits are reported, but little is known about the effects of the strong directional selection applied, on gene level variation. Large numbers of genetic markers are becoming available, making it feasible to detect and estimate these effects. Here a simulation tool was developed in order to explore the power by which single genetic loci subjected to uni-directional selection in parallel breeding populations may be detected.

Findings

Two simulation models were pursued: 1) screening for loci displaying higher genetic differentiation than expected (high-FST outliers), from neutral evolution between a pool of domesticated populations and a pool of wild populations; 2) screening for loci displaying lower genetic differentiation (low-FST outliers) between domesticated strains than expected from neutral evolution. The premise for both approaches was that the isolated domesticated strains are subjected to the same breeding goals. The power to detect outlier loci was calculated under the following parameter values: number of populations, effective population size per population, number of generations since onset of selection, initial FST, and the selection coefficient acting on the locus. Among the parameters investigated, selection coefficient, the number of generation since onset of selection, and number of populations, had the largest impact on power. The power to detect loci subjected to directional in breeding programmes was high when applying the between farmed and wild population approach, and low for the between farmed populations approach.

Conclusions

A simulation tool was developed for estimating the power to detect artificial selection acting directly on single loci. The simulation tool should be applicable to most species subject to domestication, as long as a reasonable high accuracy in input parameters such as effective population size, number of generations since the initiation of selection, and initial differentiation (FST) can be obtained. Identification of genetic loci under artificial selection would be highly valuable, since such loci could be used to monitor maintenance of genetic variation in the breeding populations and monitoring possible genetic changes in wild populations from genetic interaction between escapees and their wild counterpart.