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Inferring local adaptation from Q ST – F ST comparisons: neutral genetic and quantitative trait variation in European populations of great snipe
Author(s) -
SÆTHER S. A.,
FISKE P.,
KÅLÅS J. A.,
KURESOO A.,
LUIGUJÕE L.,
PIERTNEY S. B.,
SAHLMAN T.,
HÖGLUND J.
Publication year - 2007
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1111/j.1420-9101.2007.01328.x
Subject(s) - biology , selection (genetic algorithm) , trait , local adaptation , evolutionary biology , natural selection , divergence (linguistics) , adaptation (eye) , genetic divergence , genetic variation , gene flow , genetics , gene , population , genetic diversity , demography , linguistics , philosophy , artificial intelligence , neuroscience , sociology , computer science , programming language
We applied a phenotypic Q ST ( P ST ) vs. F ST approach to study spatial variation in selection among great snipe ( Gallinago media ) populations in two regions of northern Europe. Morphological divergence between regions was high despite low differentiation in selectively neutral genetic markers, whereas populations within regions showed very little neutral divergence and trait differentiation. Q ST > F ST was robust against altering assumptions about the additive genetic proportions of variance components. The homogenizing effect of gene flow (or a short time available for neutral divergence) has apparently been effectively counterbalanced by differential natural selection, although one trait showed some evidence of being under uniform stabilizing selection. Neutral markers can hence be misleading for identifying evolutionary significant units, and adopting the P ST – F ST approach might therefore be valuable when common garden experiments is not an option. We discuss the statistical difficulties of documenting uniform selection as opposed to divergent selection, and the need for estimating measurement error. Instead of only comparing overall Q ST and F ST values, we advocate the use of partial matrix permutation tests to analyse pairwise Q ST differences among populations, while statistically controlling for neutral differentiation.