Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA.
Mol Biol Evol. 2019 Aug 1;36(8):1701-1710. doi: 10.1093/molbev/msz092.
The fate of alleles in the human population is believed to be highly affected by the stochastic force of genetic drift. Estimation of the strength of natural selection in humans generally necessitates a careful modeling of drift including complex effects of the population history and structure. Protein-truncating variants (PTVs) are expected to evolve under strong purifying selection and to have a relatively high per-gene mutation rate. Thus, it is appealing to model the population genetics of PTVs under a simple deterministic mutation-selection balance, as has been proposed earlier (Cassa et al. 2017). Here, we investigated the limits of this approximation using both computer simulations and data-driven approaches. Our simulations rely on a model of demographic history estimated from 33,370 individual exomes of the Non-Finnish European subset of the ExAC data set (Lek et al. 2016). Additionally, we compared the African and European subset of the ExAC study and analyzed de novo PTVs. We show that the mutation-selection balance model is applicable to the majority of human genes, but not to genes under the weakest selection.
人类群体中基因的命运被认为受到遗传漂变的随机力量的高度影响。人类自然选择强度的估计通常需要仔细模拟漂变，包括人口历史和结构的复杂影响。截断蛋白变异体（PTV）预计在强大的纯化选择下进化，并具有相对较高的每个基因的突变率。因此，人们希望在简单的确定性突变-选择平衡下对 PTV 的群体遗传学进行建模，正如早期提出的那样（Cassa 等人，2017）。在这里，我们使用计算机模拟和数据驱动的方法来研究这种近似的局限性。我们的模拟依赖于从 ExAC 数据集的非芬兰欧洲个体外显子组的 33370 个个体外显子中估计的人口历史模型（Lek 等人，2016）。此外，我们比较了 ExAC 研究的非洲和欧洲子集中的个体，并分析了新生 PTV。我们表明，突变-选择平衡模型适用于大多数人类基因，但不适用于选择最弱的基因。
