Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation

Authors

  • STÉPHANIE MANEL,

    1. Laboratoire Population Environnement Développement, UMR 151 UP/IRD, Aix-Marseille Univ, 3 place Victor Hugo, 13331 Marseille Cedex 03, France
    2. Laboratoire d’Écologie Alpine (LECA), CNRS UMR 5553, Université Joseph Fourier, Grenoble I BP 53, 2233 Rue de la Piscine, 38041 Grenoble Cedex 9, France
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  • FELIX GUGERLI,

    1. WSL Swiss Federal Research Institute, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
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  • WILFRIED THUILLER,

    1. Laboratoire d’Écologie Alpine (LECA), CNRS UMR 5553, Université Joseph Fourier, Grenoble I BP 53, 2233 Rue de la Piscine, 38041 Grenoble Cedex 9, France
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  • NADIR ALVAREZ,

    1. Department of Ecology and Evolution, University of Lausanne, Biophore Building, CH-1015 Lausanne, Switzerland
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  • PIERRE LEGENDRE,

    1. Département de Sciences Biologiques, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, Canada H3C 3J7
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  • ROLF HOLDEREGGER,

    1. WSL Swiss Federal Research Institute, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
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  • LUDOVIC GIELLY,

    1. Laboratoire d’Écologie Alpine (LECA), CNRS UMR 5553, Université Joseph Fourier, Grenoble I BP 53, 2233 Rue de la Piscine, 38041 Grenoble Cedex 9, France
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  • PIERRE TABERLET,

    1. Laboratoire d’Écologie Alpine (LECA), CNRS UMR 5553, Université Joseph Fourier, Grenoble I BP 53, 2233 Rue de la Piscine, 38041 Grenoble Cedex 9, France
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  • IntraBioDiv Consortium

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    • IntraBioDiv Consortium members are in Appendix S1.


Stéphanie Manel; E-mail: stephanie.manel@univ-amu.fr

Abstract

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran’s eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

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