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      Global adaptation complicates the interpretation of genome scans for local adaptation.

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          Abstract

          Spatially varying selection promotes variance in allele frequencies, increasing genetic differentiation between the demes of a metapopulation. For that reason, outliers in the genome-wide distribution of summary statistics measuring genetic differentiation, such as FST , are often interpreted as evidence for alleles that contribute to local adaptation. However, theoretical studies have shown that in spatially structured populations the spread of beneficial mutations with spatially uniform fitness effects can also induce transient genetic differentiation. In recent years, numerous empirical studies have suggested that such species-wide, or global, adaptation makes a substantial contribution to molecular evolution. In this perspective, we discuss how commonly such global adaptation may influence the genome-wide distribution of FST and generate genetic differentiation patterns, which could be mistaken for local adaptation. To illustrate this, we use forward-in-time population genetic simulations assuming parameters for the rate and strength of beneficial mutations consistent with estimates from natural populations. We demonstrate that the spread of globally beneficial mutations in parapatric populations may frequently generate FST outliers, which could be misinterpreted as evidence for local adaptation. The spread of beneficial mutations causes selective sweeps at flanking sites, so in some cases, the effects of global versus local adaptation may be distinguished by examining patterns of nucleotide diversity within and between populations in addition to FST . However, when local adaptation has been only recently established, it may be much more difficult to distinguish from global adaptation, due to less accumulation of linkage disequilibrium at flanking sites. Through our discussion, we conclude that a large fraction of FST outliers that are presumed to arise from local adaptation may instead be due to global adaptation.

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          ESTIMATING F-STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE.

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            A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective.

            Identifying loci under natural selection from genomic surveys is of great interest in different research areas. Commonly used methods to separate neutral effects from adaptive effects are based on locus-specific population differentiation coefficients to identify outliers. Here we extend such an approach to estimate directly the probability that each locus is subject to selection using a Bayesian method. We also extend it to allow the use of dominant markers like AFLPs. It has been shown that this model is robust to complex demographic scenarios for neutral genetic differentiation. Here we show that the inclusion of isolated populations that underwent a strong bottleneck can lead to a high rate of false positives. Nevertheless, we demonstrate that it is possible to avoid them by carefully choosing the populations that should be included in the analysis. We analyze two previously published data sets: a human data set of codominant markers and a Littorina saxatilis data set of dominant markers. We also perform a detailed sensitivity study to compare the power of the method using amplified fragment length polymorphism (AFLP), SNP, and microsatellite markers. The method has been implemented in a new software available at our website (http://www-leca.ujf-grenoble.fr/logiciels.htm).
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              Conceptual issues in local adaptation

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                Author and article information

                Journal
                Evol Lett
                Evolution letters
                Wiley
                2056-3744
                2056-3744
                Feb 2021
                : 5
                : 1
                Affiliations
                [1 ] Department of Forest and Conservation Sciences University of British Columbia Vancouver Canada.
                [2 ] Biodiversity Research Centre University of British Columbia Vancouver Canada.
                [3 ] Department of Biological Sciences University of Calgary Calgary Canada.
                [4 ] Department of Zoology University of British Columbia Vancouver Canada.
                Article
                EVL3208
                10.1002/evl3.208
                7857299
                33552532
                800592de-1e35-46d9-9bcc-c809f2b48aed
                History

                FST outlier,genetics of adaptation,genome scans,global adaptation,local adaptation

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