Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI 48109, USA.
Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA.
Philos Trans R Soc Lond B Biol Sci. 2023 May 22;378(1877):20220057. doi: 10.1098/rstb.2022.0057. Epub 2023 Apr 3.
Heritable variation in gene expression is common within and among species and contributes to phenotypic diversity. Mutations affecting either - or -regulatory sequences controlling gene expression give rise to variation in gene expression, and natural selection acting on this variation causes some regulatory variants to persist in a population for longer than others. To understand how mutation and selection interact to produce the patterns of regulatory variation we see within and among species, my colleagues and I have been systematically determining the effects of new mutations on expression of the gene in and comparing them to the effects of polymorphisms segregating within this species. We have also investigated the molecular mechanisms by which regulatory variants act. Over the past decade, this work has revealed properties of - and -regulatory mutations including their relative frequency, effects, dominance, pleiotropy and fitness consequences. Comparing these mutational effects to the effects of polymorphisms in natural populations, we have inferred selection acting on expression level, expression noise and phenotypic plasticity. Here, I summarize this body of work and synthesize its findings to make inferences not readily discernible from the individual studies alone. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.
基因表达的可遗传性变异在物种内和物种间都很常见，是表型多样性的基础。影响基因表达调控序列的突变会导致基因表达的变异，而自然选择作用于这种变异会导致一些调控变异在种群中比其他变异持续存在的时间更长。为了了解突变和选择如何相互作用产生我们在物种内和物种间看到的调控变异模式，我和我的同事们一直在系统地确定新突变对 基因表达的影响，并将其与该物种内分离的多态性的影响进行比较。我们还研究了调控变异起作用的分子机制。在过去的十年中，这项工作揭示了 - 和 - 调控突变的特性，包括它们的相对频率、效应、显性、多效性和适应度后果。将这些突变效应与自然种群中多态性的效应进行比较，我们推断出对表达水平、表达噪声和表型可塑性的选择。在这里，我总结了这方面的工作，并综合了其研究结果，以便从单独的研究中不易得出推论。本文是主题为“预测进化生物学的跨学科方法”的特刊的一部分。
