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      Genetics of dispersal

      research-article
      1 , , 2 , 3 , 4 , 5 , 6 , 5 , 7 , 8 , 2 , 9 , 1 , 4 , 10 , 11 , 12 , 13 , 5 , 14 , 1 , 1 , 4 , 2 , 15 , 16 , 17
      Biological Reviews of the Cambridge Philosophical Society
      Blackwell Publishing Ltd
      dispersal kernel, eco‐evolutionary models, gene flow, genetic architecture, genotype–environment interactions, heritability, life‐history traits, migration, mobility, movement

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          ABSTRACT

          Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we ( i) review the empirical literature on the genetic basis of dispersal, ( ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and ( iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences.

          Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent.

          By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

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          Introduction to Quantitative Genetics

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            Evolution of crop species: genetics of domestication and diversification.

            Domestication is a good model for the study of evolutionary processes because of the recent evolution of crop species (<12,000 years ago), the key role of selection in their origins, and good archaeological and historical data on their spread and diversification. Recent studies, such as quantitative trait locus mapping, genome-wide association studies and whole-genome resequencing studies, have identified genes that are associated with the initial domestication and subsequent diversification of crops. Together, these studies reveal the functions of genes that are involved in the evolution of crops that are under domestication, the types of mutations that occur during this process and the parallelism of mutations that occur in the same pathways and proteins, as well as the selective forces that are acting on these mutations and that are associated with geographical adaptation of crop species.
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              The genetic theory of adaptation: a brief history.

              Theoretical studies of adaptation have exploded over the past decade. This work has been inspired by recent, surprising findings in the experimental study of adaptation. For example, morphological evolution sometimes involves a modest number of genetic changes, with some individual changes having a large effect on the phenotype or fitness. Here I survey the history of adaptation theory, focusing on the rise and fall of various views over the past century and the reasons for the slow development of a mature theory of adaptation. I also discuss the challenges that face contemporary theories of adaptation.
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                Author and article information

                Contributors
                marjo.saastamoinen@helsinki.fi
                Journal
                Biol Rev Camb Philos Soc
                Biol Rev Camb Philos Soc
                10.1111/(ISSN)1469-185X
                BRV
                Biological Reviews of the Cambridge Philosophical Society
                Blackwell Publishing Ltd (Oxford, UK )
                1464-7931
                1469-185X
                03 August 2017
                February 2018
                : 93
                : 1 ( doiID: 10.1111/brv.2018.93.issue-1 )
                : 574-599
                Affiliations
                [ 1 ] Department of Biosciences, Metapopulation Research Centre University of Helsinki, P.O. Box 65 00014 Helsinki Finland
                [ 2 ] School of Biological Sciences University of Aberdeen Aberdeen AB24 2TZ U.K.
                [ 3 ] Laboratoire Évolution & Diversité Biologique UMR5174, CNRS, Université Toulouse III Paul Sabatier 31062 Toulouse France
                [ 4 ] Centre National de la Recherche Scientifique and Université Paul Sabatier Toulouse III, SETE Station d'Ecologie Théorique et Expérimentale, UMR 5321 09200 Moulis France
                [ 5 ] Department of Evolutionary Biology and Environmental Studies University of Zurich CH‐8057 Zurich Switzerland
                [ 6 ] Population Genetics, Department of Zoology Stockholm University S‐10691 Stockholm Sweden
                [ 7 ] Department of Aquatic Ecology Eawag, Swiss Federal Institute of Aquatic Science and Technology CH‐8600 Dubendorf Switzerland
                [ 8 ] CIBIO‐InBIO, Universidade do Porto 4485‐661 Vairão Portugal
                [ 9 ] School of GeoSciences University of Edinburgh Edinburgh EH89XP U.K.
                [ 10 ] Museum National d'Histoire Naturelle Institut Systématique, Evolution, Biodiversité, UMR 7205 F‐75005 Paris France
                [ 11 ] Department of Biology Ghent University B‐9000 Ghent Belgium
                [ 12 ] PSL Research University, CEFE UMR 5175, CNRS, Université de Montpellier, Université Paul‐Valéry Montpellier, EPHE, Biogéographie et Ecologie des Vertébrés 34293 Montpellier France
                [ 13 ] CESCO UMR 7204, Bases écologiques de la conservation, Muséum national d'Histoire naturelle 75005 Paris France
                [ 14 ] Evolutionary Ecology Group, Department of Biology University of Antwerp, Universiteitsplein 1 2610 Wilrijk Belgium
                [ 15 ] Department of Biology Duke University Durham NC 27708 U.S.A.
                [ 16 ] NERC Centre for Ecology & Hydrology Wallingford OX10 8BB U.K.
                [ 17 ] Research Unit of Biodiversity (UO‐CSIC‐PA), Oviedo University 33600 Mieres Spain
                Author notes
                [*] [* ]Address for correspondence (Tel: +358 (0)50 4484471; E‐mail: marjo.saastamoinen@ 123456helsinki.fi )
                Author information
                http://orcid.org/0000-0001-7009-2527
                Article
                BRV12356
                10.1111/brv.12356
                5811798
                28776950
                663514f1-2f56-4e74-bef3-c409dc0e7fc4
                © 2017 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 31 March 2017
                : 03 July 2017
                : 05 July 2017
                Page count
                Figures: 2, Tables: 2, Pages: 26, Words: 10255
                Funding
                Funded by: European Research Council (Independent Starting grant META‐STRESS)
                Award ID: 637412
                Funded by: Academy of Finland
                Award ID: 273098
                Award ID: 265461
                Funded by: Ministerio de Economia y Competitividad “Ramón y Cajal program”
                Award ID: RYC‐2014‐16263
                Funded by: FWO research community EVENET
                Funded by: FWO research grant INVADED
                Award ID: G.018017
                Funded by: Fyssen foundation
                Funded by: ANR
                Award ID: ANR‐12‐JSV7‐0004‐01
                Funded by: SNSF grant
                Award ID: PP00P3_144846
                Funded by: International postdoctoral fellowship (Swedish Research Council)
                Funded by: FCT (Fundação para a Ciencia e a Tecnologia)
                Award ID: FCT‐ANR/BIA‐BIC/0010/2013
                Funded by: CEH
                Award ID: NEC05264
                Funded by: FCT (Fundação para a Ciencia e a Tecnologia)
                Award ID: FCT‐ANR/BIA‐BIC/0010/2013
                Funded by: ANR (INDHET program)
                Award ID: ANR‐12‐BSV7‐0023
                Funded by: ANR (GEMS program)
                Award ID: ANR‐13‐JSV7‐0010‐01
                Funded by: Ella and Georg Ehrnrooth Foundation
                Funded by: Emil Aaltonen Foundation for funding
                Funded by: UA‐TOPBOF
                Funded by: FWO‐project
                Award ID: G030813N
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                brv12356
                February 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.3.2.2 mode:remove_FC converted:14.02.2018

                Ecology
                dispersal kernel,eco‐evolutionary models,gene flow,genetic architecture,genotype–environment interactions,heritability,life‐history traits,migration,mobility,movement

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