title: Detecting adaptive evolution based on association with ecological gradients: orientation matters!
abstract: Population genetic signatures of local adaptation are frequently investigated by identifying loci with allele frequencies that exhibit high correlation with ecological variables. One difficulty with this approach is that ecological associations might be confounded by geographic variation at selectively neutral loci. Here, we consider populations that underwent spatial expansion from their original range, and for which geographical variation of adaptive allele frequency coincides with habitat gradients. Using range expansion simulations, we asked whether our ability to detect genomic regions involved in adaptation could be impacted by the orientation of the ecological gradients. For three ecological association methods tested, we found, counter-intuitively, fewer false-positive associations when ecological gradients aligned along the main axis of expansion than when they aligned along any other direction. This result has important consequences for the analysis of genomic data under non-equilibrium population genetic models. Alignment of gradients with expansion axes is likely to be common in scenarios in which expanding species track their ecological niche during climate change while adapting to changing environments at their rear edge.
authors.affiliation: Université Joseph Fourier Grenoble, Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Grenoble, France.
authors.forename: E
authors.initials: E
authors.lastname: Frichot
authors.affiliation: University of Wisconsin-Madison, Department of Entomology, Madison, WI, USA.
authors.forename: S D
authors.initials: SD
authors.lastname: Schoville
authors.affiliation: Université Joseph Fourier Grenoble, Centre National de la Recherche Scientifique, Laboratoire d'Ecologie Alpine UMR 5553, Grenoble, France.
authors.forename: P
authors.initials: P
authors.lastname: de Villemereuil
authors.affiliation: 1] Université Joseph Fourier Grenoble, Centre National de la Recherche Scientifique, Laboratoire d'Ecologie Alpine UMR 5553, Grenoble, France [2] University of St Andrews, Scottish Oceans Institute, East Sands, St Andrews, Fife, UK.
authors.forename: O E
authors.initials: OE
authors.lastname: Gaggiotti
authors.affiliation: Université Joseph Fourier Grenoble, Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Grenoble, France.
authors.forename: O
authors.initials: O
authors.lastname: François
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D005075:Biological Evolution; D057231:Climate Change; D004463:Ecology / Q000379:methods; D017753:Ecosystem; D005787:Gene Frequency; D056426:Genetic Loci; D005838:Genotype; D016014:Linear Models; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide