Hodgins-Davis Andrea, Rice Daniel P, Townsend Jeffrey P
Department of Ecology and Evolutionary Biology, Yale University Department of Biostatistics, School of Public Health, Yale University.
Department of Ecology and Evolutionary Biology, Yale University Department of Organismic and Evolutionary Biology, Harvard University.
Mol Biol Evol. 2015 Aug;32(8):2130-40. doi: 10.1093/molbev/msv094. Epub 2015 Apr 20.
Divergence in gene regulation is hypothesized to underlie much of phenotypic evolution, but the role of natural selection in shaping the molecular phenotype of gene expression continues to be debated. To resolve the mode of gene expression, evolution requires accessible theoretical predictions for the effect of selection over long timescales. Evolutionary quantitative genetic models of phenotypic evolution can provide such predictions, yet those predictions depend on the underlying hypotheses about the distributions of mutational and selective effects that are notoriously difficult to disentangle. Here, we draw on diverse genomic data sets including expression profiles of natural genetic variation and mutation accumulation lines, empirical estimates of genomic mutation rates, and inferences of genetic architecture to differentiate contrasting hypotheses for the roles of stabilizing selection and mutation in shaping natural expression variation. Our analysis suggests that gene expression evolves in a domain of phenotype space well fit by the House-of-Cards (HC) model. Although the strength of selection inferred is sensitive to the number of loci controlling gene expression, the model is not. The consistency of these results across evolutionary time from budding yeast through fruit fly implies that this model is general and that mutational effects on gene expression are relatively large. Empirical estimates of the genetic architecture of gene expression traits imply that selection provides modest constraints on gene expression levels for most genes, but that the potential for regulatory evolution is high. Our prediction using data from laboratory environments should encourage the collection of additional data sets allowing for more nuanced parameterizations of HC models for gene expression.
基因调控的差异被认为是许多表型进化的基础,但自然选择在塑造基因表达分子表型中的作用仍存在争议。为了解决基因表达模式的问题,进化需要对长期选择效应进行可及的理论预测。表型进化的进化数量遗传模型可以提供这样的预测,但这些预测依赖于关于突变和选择效应分布的潜在假设,而这些假设很难区分。在这里,我们利用各种基因组数据集,包括自然遗传变异和突变积累系的表达谱、基因组突变率的实证估计以及遗传结构的推断,来区分关于稳定选择和突变在塑造自然表达变异中作用的不同假设。我们的分析表明,基因表达在一个由纸牌屋(HC)模型很好拟合的表型空间域中进化。尽管推断出的选择强度对控制基因表达的基因座数量敏感,但该模型并非如此。从芽殖酵母到果蝇的进化时间内这些结果的一致性意味着该模型具有普遍性,并且突变对基因表达的影响相对较大。基因表达性状遗传结构的实证估计表明,对于大多数基因,选择对基因表达水平提供适度的限制,但调控进化的潜力很高。我们使用实验室环境数据的预测应该会鼓励收集更多数据集,以便对基因表达的HC模型进行更细致的参数化。