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An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/64669

Title: An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous
Authors: Matsumoto, Tomotaka Browse this author
Mineta, Katsuhiko Browse this author
Osada, Naoki Browse this author
Araki, Hitoshi Browse this author →KAKEN DB
Keywords: stochastic gene expression
environmental change
viability selection
effective population size
individual-based simulation
Issue Date: 24-Nov-2015
Journal Title: Frontiers in Genetics
Volume: 6
Start Page: 336
Publisher DOI: 10.3389/fgene.2015.00336
Abstract: Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, anditsnon-negligible effecton their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE become sadvantageous, indicating a better opportunity for the evolution of SGE in different genetic models.
Rights: https://creativecommons.org/licenses/by/4.0/
Type: article
URI: http://hdl.handle.net/2115/64669
Appears in Collections:農学院・農学研究院 (Graduate School of Agriculture / Faculty of Agriculture) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 荒木 仁志

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