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The effects of dominance, regular Inbreeding and sampling design on QST, an estimator of population differentiation for quantitative traits

The effects of dominance, regular Inbreeding and sampling design on QST, an estimator of population differentiation for quantitative traits

Goudet, Jérôme and Büchi, Lucie ORCID: 0000-0002-1935-6176 (2006) The effects of dominance, regular Inbreeding and sampling design on QST, an estimator of population differentiation for quantitative traits. Genetics, 172 (2). pp. 1337-1347. ISSN 0016-6731 (Print), 1943-2631 (Online) (doi:10.1534/genetics.105.050583)

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Abstract

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Item Type: Article
Uncontrolled Keywords: neutral traits, quantitative genetics, simulations
Subjects: Q Science > QH Natural history > QH426 Genetics
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science > Natural Resources Institute > Ecosystem Services Research Group
Last Modified: 12 Oct 2018 15:27
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/20223

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