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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Optimization Of Gene Expression By Natural Selection
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Optimization Of Gene Expression By Natural Selection

机译：通过自然选择优化基因表达

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摘要

It is generally assumed that stabilizing selection promoting a phenotypic optimum acts to shape variation in quantitative traits across individuals and species. Although gene expression represents an intensively studied molecular phenotype, the extent to which stabilizing selection limits divergence in gene expression remains contentious. In this study, we present a theoretical framework for the study of stabilizing and directional selection using data from between-species divergence of continuous traits. This framework, based upon Brownian motion, is analytically tractable and can be used in maximum-likelihood or Bayesian parameter estimation. We apply this model to gene-expression levels in 7 species of Drosophila, and find that gene-expression divergence is substantially curtailed by stabilizing selection. However, we estimate the selective effect, s, of gene-expression change to be very small, approximately equal to Ns for a change of one standard deviation, where N is the effective population size. These findings highlight the power of natural selection to shape phenotype, even when the fitness effects of mutations are in the nearly neutral range.
机译：通常认为，促进表型最优的稳定选择会影响个体和物种间数量性状的变化。尽管基因表达代表了一个深入研究的分子表型，但稳定选择限制基因表达差异的程度仍然存在争议。在这项研究中，我们提供了一个使用来自连续性状的种间差异的数据进行稳定和方向选择研究的理论框架。该框架基于布朗运动，在分析上易于处理，可用于最大似然或贝叶斯参数估计。我们将此模型应用于果蝇7种物种中的基因表达水平，并发现通过稳定选择，基因表达差异已大大减少。但是，我们估计基因表达变化的选择性效应s非常小，大约等于一个标准差变化的Ns，其中N是有效种群大小。这些发现强调了自然选择对表型的影响力，即使突变的适应性效应处于近乎中性的范围内。

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