Conservation Genetics

, Volume 14, Issue 2, pp 467–481 | Cite as

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

  • Helen Bothwell
  • Sarah Bisbing
  • Nina Overgaard Therkildsen
  • Lindsay Crawford
  • Nadir Alvarez
  • Rolf Holderegger
  • Stéphanie Manel
Research Article

Abstract

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (Radj2 > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Keywords

Adaptive genetic variation Landscape genetics Allele distribution models Outlier locus detection Principle coordinates of neighbor matrices Climate change 

Supplementary material

10592_2012_411_MOESM1_ESM.pdf (681 kb)
Supplementary material 1 (PDF 681 kb)

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Helen Bothwell
    • 1
  • Sarah Bisbing
    • 2
  • Nina Overgaard Therkildsen
    • 3
  • Lindsay Crawford
    • 4
  • Nadir Alvarez
    • 5
  • Rolf Holderegger
    • 6
  • Stéphanie Manel
    • 7
  1. 1.Environmental Genetics and Genomics Laboratory, Department of Biological SciencesNorthern Arizona UniversityFlagstaffUSA
  2. 2.Graduate Degree Program in EcologyColorado State UniversityFort CollinsUSA
  3. 3.Section for Population Ecology and Genetics, National Institute of Aquatic ResourcesTechnical University of DenmarkSilkeborgDenmark
  4. 4.Department of BiologyWestern UniversityLondonCanada
  5. 5.Department of Ecology and EvolutionBiophore Building University of LausanneLausanneSwitzerland
  6. 6.WSL Swiss Federal Research InstituteBirmensdorfSwitzerland
  7. 7.Laboratoire Population Environnement DéveloppementUniversité Aix-MarseilleMarseille Cedex 03France

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