Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples.
Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples.
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DOI：
10.1534/genetics.116.197145
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发表时间：
2017-05
期刊：
影响因子：
3.3
通讯作者：
Lohmueller KE
中科院分区：
文献类型：
--
作者：
Kim BY;Huber CD;Lohmueller KE
适合度效应的分布在群体遗传学中具有重要意义。迄今为止，DFE的估计值来自使用少量个体的研究。因此，估计中度至强烈有害的新突变的比例可能是不可靠的，因为这些变异不太可能在数据中分离。此外，DFE的真实功能形式是未知的，并且DFE的估计值在研究之间存在显著差异。在这里，我们提出了一个灵活的和计算上易于处理的方法，称为拟合的突变，估计DFE的新突变使用的网站频谱从大量的个人。我们将我们的方法应用于来自外显子组测序项目ESP 6400数据集的1300名欧洲人，来自LuCamp数据集的1298名丹麦人和来自1000个基因组项目的432名欧洲人的频谱，以估计有害非同义突变的DFE。我们推断选择系数显著减少（0.38-0.84倍）强有害突变|S|> 0.01和更多（1.24-1.43倍）具有选择系数的弱有害突变|S| 0.001与之前的估计相比。此外，在三个数据集中的两个中，作为中性点质量的混合分布加上伽马分布的DFE比伽马分布拟合得更好。我们的研究结果表明，接近中性的力量在人类进化中发挥的作用比以前认为的要大。
The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38–0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24–1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought.