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Enhanced AFLP genome scans detect local adaptation in high-altitude populations of a small rodent (Microtus arvalis)

Authors

  • MARTIN C. FISCHER,

    1. Computational and Molecular Population Genetics (CMPG), Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, CH-3012 Bern, Switzerland
    2. Swiss Institute of Bioinformatics, Genopode, CH-1015 Lausanne, Switzerland
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  • MATTHIEU FOLL,

    1. Computational and Molecular Population Genetics (CMPG), Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, CH-3012 Bern, Switzerland
    2. Swiss Institute of Bioinformatics, Genopode, CH-1015 Lausanne, Switzerland
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  • LAURENT EXCOFFIER,

    1. Computational and Molecular Population Genetics (CMPG), Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, CH-3012 Bern, Switzerland
    2. Swiss Institute of Bioinformatics, Genopode, CH-1015 Lausanne, Switzerland
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  • GERALD HECKEL

    1. Computational and Molecular Population Genetics (CMPG), Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, CH-3012 Bern, Switzerland
    2. Swiss Institute of Bioinformatics, Genopode, CH-1015 Lausanne, Switzerland
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Gerald Heckel, Fax: +41 31 631 31 88; E-mail: gerald.heckel@iee.unibe.ch

Abstract

Adaptation to adverse environmental conditions such as high altitude requires physiological and/or morphological changes. Genome scans provide a means to identify the genetic basis of such adaptations without previous knowledge about the particular genetic variants or traits under selection. In this study, we scanned 3027 amplified fragment length polymorphisms (AFLP) in four populations of the common vole Microtus arvalis for loci associated with local adaptation and high altitude. We investigated voles from two populations at high elevation (∼2000 m a.s.l.) representing the upper limit of the altitudinal distribution of the species and two geographically close low-altitude populations (<600 m a.s.l.). Statistical analysis incorporated a new Bayesian FST outlier approach specifically developed for AFLP markers, which considers the intensity of AFLP bands instead of mere presence/absence and allows to derive population-based estimates of allele frequencies and FIS values. Computer simulations showed that this approach increases the statistical power of the detection of AFLP markers under selection almost to the power of single nucleotide polymorphism (SNP) data without compromising specificity. Our enhanced genome scan resulted in 20 prime candidate markers for positive selection, which show mostly extremely high allele frequency differences between the low- and high-altitude populations. The comparison of global- and pairwise-enhanced genome scans demonstrated further that very strong selective signatures may also be associated with single populations suggesting the importance of local adaptation in alpine populations of common voles.

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