title: Identifying outlier loci in admixed and in continuous populations using ancestral population differentiation statistics.
abstract: Finding genetic signatures of local adaptation is of great interest for many population genetic studies. Common approaches to sorting selective loci from their genomic background focus on the extreme values of the fixation index, FST, across loci. However, the computation of the fixation index becomes challenging when the population is genetically continuous, when predefining subpopulations is a difficult task, and in the presence of admixed individuals in the sample. In this study, we present a new method to identify loci under selection based on an extension of the FSTstatistic to samples with admixed individuals. In our approach, FSTvalues are computed from the ancestry coefficients obtained with ancestry estimation programs. More specifically, we used factor models to estimate FST, and we compared our neutrality tests with those derived from a principal component analysis approach. The performances of the tests were illustrated using simulated data and by re-analysing genomic data from European lines of the plant species Arabidopsis thaliana and human genomic data from the population reference sample, POPRES.
authors: Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Université Grenoble-Alpes, Grenoble, 38042, France.
authors: Helena
authors: H
authors: Martins
authors: Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Université Grenoble-Alpes, Grenoble, 38042, France.
authors: Kevin
authors: K
authors: Caye
authors: Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Université Grenoble-Alpes, Grenoble, 38042, France.
authors: Keurcien
authors: K
authors: Luu
authors: Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Université Grenoble-Alpes, Grenoble, 38042, France.
authors: Michael G B
authors: MG
authors: Blum
authors: Centre National de la Recherche Scientifique, TIMC-IMAG UMR 5525, Université Grenoble-Alpes, Grenoble, 38042, France. olivier.francois@imag.fr.
authors: Olivier
authors: O
authors: François
mesh_terms: D000220:Adaptation, Biological / Q000235:genetics; D017360:Arabidopsis / Q000235:genetics; D003198:Computer Simulation; D005787:Gene Frequency; D056426:Genetic Loci; D005828:Genetics, Population / Q000379:methods*; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012641:Selection, Genetic
keywords: admixed populations; genome scans for selection; inference of population structure; population differentiation tests