Determining the factors driving selective effects of new nonsynonymous mutations
Determining the factors driving selective effects of new nonsynonymous mutations
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DOI：
10.1073/pnas.1619508114
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发表时间：
2017-04-25
影响因子：
11.1
通讯作者：
Lohmueller, Kirk E.
中科院分区：
文献类型：
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作者：
Huber, Christian D.;Kim, Bernard Y.;Lohmueller, Kirk E.
新突变的适应度效应（DFE）分布在进化遗传学中起着重要作用。然而，DFE在物种间的差异程度还有待系统研究。此外，在自然种群中确定DFE的生物学机制仍不清楚。在这里，我们表明，理论模型强调不同的生物因素在确定DFE，如蛋白质的稳定性，回复突变，物种的复杂性，和突变的鲁棒性作出不同的预测DFE将如何不同物种之间。在比较群体基因组框架中分析来自自然群体的氨基酸变化变体，我们发现人类比果蝇具有更高比例的强烈有害突变。此外，当比较酵母、果蝇、小鼠和人类的DFE时，平均选择系数随着物种复杂性的增加而变得更加有害。最后，多效性基因的DFE比非多效性基因的DFE可变性小。比较四类理论模型，只有费雪几何模型（FGM）是与我们的研究结果一致。FGM假设多种表型处于稳定选择下，表型的数量决定了生物体的复杂性。我们的研究结果表明，长期的人口规模和成本的复杂性驱动的进化的DFE，进化和医学基因组学的许多影响。
The distribution of fitness effects (DFE) of new mutations plays a fundamental role in evolutionary genetics. However, the extent to which the DFE differs across species has yet to be systematically investigated. Furthermore, the biological mechanisms determining the DFE in natural populations remain unclear. Here, we show that theoretical models emphasizing different biological factors at determining the DFE, such as protein stability, back-mutations, species complexity, and mutational robustness make distinct predictions about how the DFE will differ between species. Analyzing amino acid-changing variants from natural populations in a comparative population genomic framework, we find that humans have a higher proportion of strongly deleterious mutations than Drosophila melanogaster. Furthermore, when comparing the DFE across yeast, Drosophila, mice, and humans, the average selection coefficient becomes more deleterious with increasing species complexity. Last, pleiotropic genes have a DFE that is less variable than that of nonpleiotropic genes. Comparing four categories of theoretical models, only Fisher's geometrical model (FGM) is consistent with our findings. FGM assumes that multiple phenotypes are under stabilizing selection, with the number of phenotypes defining the complexity of the organism. Our results suggest that long-term population size and cost of complexity drive the evolution of the DFE, with many implications for evolutionary and medical genomics.