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    Population genetics of non-genetic traits: Evolutionary roles of stochasticity in gene expression

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    Type
    Article
    Authors
    Mineta, Katsuhiko cc
    Matsumoto, Tomotaka
    Osada, Naoki
    Araki, Hitoshi
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Date
    2015-05
    Permanent link to this record
    http://hdl.handle.net/10754/566151
    
    Metadata
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    Abstract
    The role of stochasticity in evolutionary genetics has long been debated. To date, however, the potential roles of non-genetic traits in evolutionary processes have been largely neglected. In molecular biology, growing evidence suggests that stochasticity in gene expression (SGE) is common and that SGE has major impacts on phenotypes and fitness. Here, we provide a general overview of the potential effects of SGE on population genetic parameters, arguing that SGE can indeed have a profound effect on evolutionary processes. Our analyses suggest that SGE potentially alters the fate of mutations by influencing effective population size and fixation probability. In addition, a genetic control of SGE magnitude could evolve under certain conditions, if the fitness of the less-fit individual increases due to SGE and environmental fluctuation. Although empirical evidence for our arguments is yet to come, methodological developments for precisely measuring SGE in living organisms will further advance our understanding of SGE-driven evolution.
    Sponsors
    We thank Tomoko Ohta, Dan Graur, Daniel Hartl, Kunihiko Kaneko, Hidenori Tachida, Carlos Melian, Mathieu Camenzind, and Julian Junker for their useful discussions in the early stages of this article. This work was supported by the Swiss National Science Foundation Grant to HA. (No. 31003A_125213) and by a grant for young scientists from the Graduate School of Information Science and Technology, Hokkaido University to K.M.
    Publisher
    Elsevier BV
    Journal
    Gene
    DOI
    10.1016/j.gene.2015.03.011
    PubMed ID
    25752289
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.gene.2015.03.011
    Scopus Count
    Collections
    Articles; Computational Bioscience Research Center (CBRC)

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