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      Can the experimental evolution programme help us elucidate the genetic basis of adaptation in nature?

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          Abstract

          There have been a variety of approaches taken to try to characterize and identify the genetic basis of adaptation in nature, spanning theoretical models, experimental evolution studies and direct tests of natural populations. Theoretical models can provide formalized and detailed hypotheses regarding evolutionary processes and patterns, from which experimental evolution studies can then provide important proofs of concepts and characterize what is biologically reasonable. Genetic and genomic data from natural populations then allow for the identification of the particular factors that have and continue to play an important role in shaping adaptive evolution in the natural world. Further to this, experimental evolution studies allow for tests of theories that may be difficult or impossible to test in natural populations for logistical and methodological reasons and can even generate new insights, suggesting further refinement of existing theories. However, as experimental evolution studies often take place in a very particular set of controlled conditions – that is simple environments, a small range of usually asexual species, relatively short timescales – the question remains as to how applicable these experimental results are to natural populations. In this review, we discuss important insights coming from experimental evolution, focusing on four key topics tied to the evolutionary genetics of adaptation, and within those topics, we discuss the extent to which the experimental work compliments and informs natural population studies. We finish by making suggestions for future work in particular a need for natural population genomic time series data, as well as the necessity for studies that combine both experimental evolution and natural population approaches.

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          Widespread parallel evolution in sticklebacks by repeated fixation of Ectodysplasin alleles.

          Major phenotypic changes evolve in parallel in nature by molecular mechanisms that are largely unknown. Here, we use positional cloning methods to identify the major chromosome locus controlling armor plate patterning in wild threespine sticklebacks. Mapping, sequencing, and transgenic studies show that the Ectodysplasin (EDA) signaling pathway plays a key role in evolutionary change in natural populations and that parallel evolution of stickleback low-plated phenotypes at most freshwater locations around the world has occurred by repeated selection of Eda alleles derived from an ancestral low-plated haplotype that first appeared more than two million years ago. Members of this clade of low-plated alleles are present at low frequencies in marine fish, which suggests that standing genetic variation can provide a molecular basis for rapid, parallel evolution of dramatic phenotypic change in nature.
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            Soft sweeps: molecular population genetics of adaptation from standing genetic variation.

            A population can adapt to a rapid environmental change or habitat expansion in two ways. It may adapt either through new beneficial mutations that subsequently sweep through the population or by using alleles from the standing genetic variation. We use diffusion theory to calculate the probabilities for selective adaptations and find a large increase in the fixation probability for weak substitutions, if alleles originate from the standing genetic variation. We then determine the parameter regions where each scenario-standing variation vs. new mutations-is more likely. Adaptations from the standing genetic variation are favored if either the selective advantage is weak or the selection coefficient and the mutation rate are both high. Finally, we analyze the probability of "soft sweeps," where multiple copies of the selected allele contribute to a substitution, and discuss the consequences for the footprint of selection on linked neutral variation. We find that soft sweeps with weaker selective footprints are likely under both scenarios if the mutation rate and/or the selection coefficient is high.
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              Convergence, adaptation, and constraint.

              Convergent evolution of similar phenotypic features in similar environmental contexts has long been taken as evidence of adaptation. Nonetheless, recent conceptual and empirical developments in many fields have led to a proliferation of ideas about the relationship between convergence and adaptation. Despite criticism from some systematically minded biologists, I reaffirm that convergence in taxa occupying similar selective environments often is the result of natural selection. However, convergent evolution of a trait in a particular environment can occur for reasons other than selection on that trait in that environment, and species can respond to similar selective pressures by evolving nonconvergent adaptations. For these reasons, studies of convergence should be coupled with other methods-such as direct measurements of selection or investigations of the functional correlates of trait evolution-to test hypotheses of adaptation. The independent acquisition of similar phenotypes by the same genetic or developmental pathway has been suggested as evidence of constraints on adaptation, a view widely repeated as genomic studies have documented phenotypic convergence resulting from change in the same genes, sometimes even by the same mutation. Contrary to some claims, convergence by changes in the same genes is not necessarily evidence of constraint, but rather suggests hypotheses that can test the relative roles of constraint and selection in directing phenotypic evolution. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.
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                Author and article information

                Journal
                Mol Ecol
                Mol. Ecol
                10.1111/(ISSN)1365-294X
                MEC
                Molecular Ecology
                John Wiley and Sons Inc. (Hoboken )
                0962-1083
                1365-294X
                January 2016
                14 October 2015
                : 25
                : 1 , DETECTING SELECTION IN NATURAL POPULATIONS ( doiID: 10.1111/mec.2016.25.issue-1 )
                : 203-218
                Affiliations
                [ 1 ] Bioinformatics Research CentreAarhus University C.F. Møllers Allé 8 DK‐8000 Aarhus CDenmark
                Author notes
                [*] [* ]Correspondence: Susan F. Bailey, Fax: +45 871 54102; E‐mail: susan.f.bailey@ 123456gmail.com
                Article
                MEC13378
                10.1111/mec.13378
                5019151
                26346808
                61478006-abba-47d2-9485-ee0f697bbebc
                © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

                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
                : 12 May 2015
                : 26 August 2015
                : 04 September 2015
                Page count
                Pages: 16
                Funding
                Funded by: European Research Council under the European Union's Seventh Framework Program
                Award ID: FP7/20072013
                Award ID: ERC Grant 311341
                Categories
                Detecting Selection in Natural Populations: Making Sense of Genome Scans and Towards Alternative Solutions
                Laboratory Methods
                Custom metadata
                2.0
                mec13378
                January 2016
                Converter:WILEY_ML3GV2_TO_NLMPMC version:4.9.4 mode:remove_FC converted:12.09.2016

                Ecology
                adaptive evolution,experimental evolution,genomic data,natural populations
                Ecology
                adaptive evolution, experimental evolution, genomic data, natural populations

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