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      Constraints on the evolution of phenotypic plasticity: limits and costs of phenotype and plasticity

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          Abstract

          Phenotypic plasticity is ubiquitous and generally regarded as a key mechanism for enabling organisms to survive in the face of environmental change. Because no organism is infinitely or ideally plastic, theory suggests that there must be limits (for example, the lack of ability to produce an optimal trait) to the evolution of phenotypic plasticity, or that plasticity may have inherent significant costs. Yet numerous experimental studies have not detected widespread costs. Explicitly differentiating plasticity costs from phenotype costs, we re-evaluate fundamental questions of the limits to the evolution of plasticity and of generalists vs specialists. We advocate for the view that relaxed selection and variable selection intensities are likely more important constraints to the evolution of plasticity than the costs of plasticity. Some forms of plasticity, such as learning, may be inherently costly. In addition, we examine opportunities to offset costs of phenotypes through ontogeny, amelioration of phenotypic costs across environments, and the condition-dependent hypothesis. We propose avenues of further inquiry in the limits of plasticity using new and classic methods of ecological parameterization, phylogenetics and omics in the context of answering questions on the constraints of plasticity. Given plasticity's key role in coping with environmental change, approaches spanning the spectrum from applied to basic will greatly enrich our understanding of the evolution of plasticity and resolve our understanding of limits.

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          Most cited references 39

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          A map of local adaptation in Arabidopsis thaliana.

          Local adaptation is critical for species persistence in the face of rapid environmental change, but its genetic basis is not well understood. Growing the model plant Arabidopsis thaliana in field experiments in four sites across the species' native range, we identified candidate loci for local adaptation from a genome-wide association study of lifetime fitness in geographically diverse accessions. Fitness-associated loci exhibited both geographic and climatic signatures of local adaptation. Relative to genomic controls, high-fitness alleles were generally distributed closer to the site where they increased fitness, occupying specific and distinct climate spaces. Independent loci with different molecular functions contributed most strongly to fitness variation in each site. Independent local adaptation by distinct genetic mechanisms may facilitate a flexible evolutionary response to changing environment across a species range.
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            Massive genomic variation and strong selection in Arabidopsis thaliana lines from Sweden.

            Despite advances in sequencing, the goal of obtaining a comprehensive view of genetic variation in populations is still far from reached. We sequenced 180 lines of A. thaliana from Sweden to obtain as complete a picture as possible of variation in a single region. Whereas simple polymorphisms in the unique portion of the genome are readily identified, other polymorphisms are not. The massive variation in genome size identified by flow cytometry seems largely to be due to 45S rDNA copy number variation, with lines from northern Sweden having particularly large numbers of copies. Strong selection is evident in the form of long-range linkage disequilibrium (LD), as well as in LD between nearby compensatory mutations. Many footprints of selective sweeps were found in lines from northern Sweden, and a massive global sweep was shown to have involved a 700-kb transposition.
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              Gene duplication and the adaptive evolution of a classic genetic switch.

              How gene duplication and divergence contribute to genetic novelty and adaptation has been of intense interest, but experimental evidence has been limited. The genetic switch controlling the yeast galactose use pathway includes two paralogous genes in Saccharomyces cerevisiae that encode a co-inducer (GAL3) and a galactokinase (GAL1). These paralogues arose from a single bifunctional ancestral gene as is still present in Kluyveromyces lactis. To determine which evolutionary processes shaped the evolution of the two paralogues, here we assess the effects of precise replacement of coding and non-coding sequences on organismal fitness. We suggest that duplication of the ancestral bifunctional gene allowed for the resolution of an adaptive conflict between the transcriptional regulation of the two gene functions. After duplication, previously disfavoured binding site configurations evolved that divided the regulation of the ancestral gene into two specialized genes, one of which ultimately became one of the most tightly regulated genes in the genome.
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                Author and article information

                Journal
                Heredity (Edinb)
                Heredity (Edinb)
                Heredity
                Nature Publishing Group
                0018-067X
                1365-2540
                October 2015
                18 February 2015
                1 October 2015
                : 115
                : 4
                : 293-301
                Affiliations
                [1 ]Department of Biology, College of Charleston , Charleston, SC, USA
                [2 ]Department of Biology, West Chester University , West Chester, PA, USA
                [3 ]Barnard College, Columbia University , New York, NY, USA
                [4 ]Department of Biology, Colorado State University , Fort Collins, CO, USA
                [5 ]Research School of Biology, Australian National University, Acton , Canberra, Australian Capital Territory, Australia
                [6 ]Department of Biology, University of North Carolina , Chapel Hill, NC, USA
                [7 ]Department of Ecology and Evolutionary Biology, University of Arizona , Tucson, AZ, USA
                [8 ]Ronin Institute , Montclair, NJ, USA
                [9 ]Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, USA
                [10 ]Department of Ecology and Evolution, University of Colorado Boulder , Boulder, CO, USA
                [11 ]Department of Ecology, Evolution and Behavior, University of Minnesota , St Paul, MN, USA
                [12 ]Department of Biology, University of Southern Denmark, Max-Planck Odense Centre on the Biodemography of Aging , Odense, Denmark
                [13 ]Department of Ecology and Evolutionary Biology, University of Connecticut , Storrs, CT, USA
                Author notes
                [* ]Department of Biology, College of Charleston , 66 George Street, Charleston, SC 29424, USA. E-mail: murrenc@ 123456cofc.edu
                Article
                hdy20158
                10.1038/hdy.2015.8
                4815460
                25690179
                Copyright © 2015 The Genetics Society

                This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

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