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新突变对适应性的影响:来自模型和数据的启示。

Effects of new mutations on fitness: insights from models and data.

机构信息

Bioinformatics Research Center, Aarhus University, Aarhus, Denmark.

出版信息

Ann N Y Acad Sci. 2014 Jul;1320(1):76-92. doi: 10.1111/nyas.12460. Epub 2014 May 30.

Abstract

The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.

摘要

新突变影响适应度的速率和特性对进化生物学中的许多悬而未决的问题具有重要意义。获得突变率和效应的估计值在历史上一直具有挑战性,并且几乎没有理论可用于预测适应度效应分布(DFE);然而,这两个方面都取得了最近的进展。极值理论预测了适应良好的种群中有益突变的 DFE,而表型适应度景观模型则根据初始适应水平和对适应度相关性状的稳定选择强度,对所有突变的 DFE 做出预测。直接实验证据证实了有益突变的 DFE 预测,并支持大致呈指数分布但右侧有界的分布。越来越多的研究使用多态性和分歧的基因组模式推断 DFE,从而恢复了广泛的 DFE。未来的工作应该旨在确定驱动 DFE 观察到的变异的因素。我们强调需要进一步的理论,明确纳入部分多效性和环境异质性对预期 DFE 的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/405c/4282485/a371b0598a04/nyas1320-0076-f1.jpg

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