Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06520, USA.
Genetics. 2012 Apr;190(4):1533-45. doi: 10.1534/genetics.111.137075. Epub 2012 Jan 31.
Evolutionary biologists attribute much of the phenotypic diversity observed in nature to the action of natural selection. However, for many phenotypic traits, especially quantitative phenotypic traits, it has been challenging to test for the historical action of selection. An important challenge for biologists studying quantitative traits, therefore, is to distinguish between traits that have evolved under the influence of strong selection and those that have evolved neutrally. Most existing tests for selection employ molecular data, but selection also leaves a mark on the genetic architecture underlying a trait. In particular, the distribution of quantitative trait locus (QTL) effect sizes and the distribution of mutational effects together provide information regarding the history of selection. Despite the increasing availability of QTL and mutation accumulation data, such data have not yet been effectively exploited for this purpose. We present a model of the evolution of QTL and employ it to formulate a test for historical selection. To provide a baseline for neutral evolution of the trait, we estimate the distribution of mutational effects from mutation accumulation experiments. We then apply a maximum-likelihood-based method of inference to estimate the range of selection strengths under which such a distribution of mutations could generate the observed QTL. Our test thus represents the first integration of population genetic theory and QTL data to measure the historical influence of selection.
进化生物学家将自然界中观察到的许多表型多样性归因于自然选择的作用。然而,对于许多表型特征,特别是定量表型特征,要测试选择的历史作用一直具有挑战性。因此,对于研究定量特征的生物学家来说,一个重要的挑战是区分在强烈选择影响下进化的特征和中性进化的特征。大多数现有的选择测试都使用分子数据,但选择也在特征的遗传结构上留下了痕迹。特别是,数量性状基因座(QTL)效应大小的分布和突变效应的分布共同提供了有关选择历史的信息。尽管 QTL 和突变积累数据的可用性不断增加,但这些数据尚未被有效地用于此目的。我们提出了一个 QTL 进化模型,并利用它来制定一个历史选择的测试。为了提供性状中性进化的基线,我们从突变积累实验中估计突变效应的分布。然后,我们应用基于最大似然的推断方法来估计在这种突变分布下可以产生观察到的 QTL 的选择强度范围。因此,我们的测试代表了群体遗传理论和 QTL 数据的首次整合,用于衡量选择的历史影响。