Optimization of gene expression by natural selection
Optimization of gene expression by natural selection
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DOI：
10.1073/pnas.0812009106
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发表时间：
2009-01-27
影响因子：
11.1
通讯作者：
Hartl, Daniel L.
中科院分区：
文献类型：
--
作者：
Bedford, Trevor;Hartl, Daniel L.
通常认为，稳定选择促进表型最佳，从而塑造个体和物种之间数量性状的变化。尽管基因表达代表了一种经过深入研究的分子表型，但稳定选择在多大程度上限制了基因表达的差异仍然存在争议。在这项研究中，我们提出了一个利用物种间连续性状差异数据来研究稳定和定向选择的理论框架。该框架基于布朗运动，易于分析处理，可用于最大似然或贝叶斯参数估计。我们将该模型应用于 7 个果蝇物种的基因表达水平，发现稳定选择大大减少了基因表达差异。然而，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 是有效群体大小。这些发现凸显了自然选择塑造表型的力量，即使突变的适应度效应处于接近中性的范围内。
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.