Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations
Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations
复制标题
DOI：
10.1093/bioinformatics/btz498
复制
发表时间：
2020-01-01
期刊：
影响因子：
5.8
通讯作者：
Kiryu, Hisanori
中科院分区：
文献类型：
--
作者：
Kojima, Yasuhiro;Matsumoto, Hirotaka;Kiryu, Hisanori
动机进化和重测序（E&R）实验显示出在全基因组范围内捕获实时进化的前景，使得能够评估等位基因频率变化SNP在不断变化的人群中，从而估计群体遗传参数的赖特-费舍尔模型（WF），量化选择SNP。目前，这些分析面临着两个关键的困难：在E&R数据中的众多SNPs和估计的频繁不可靠性。因此，需要有效地估计WF参数的方法来了解形状genomes.Results的进化过程，我们开发了一种新的方法估计WF参数（EMWER），通过应用期望最大化算法的Kolmogorov向前方程与WF模型扩散近似。利用EMWER方法从E&R数据中推断有效群体大小、选择系数和优势度参数。在所研究的方法中，EMWER是多核计算环境中估计选择强度的最有效方法，可以用准确的置信区间估计选择和优势。我们应用EMWER的E&R数据从实验果蝇种群适应热波动的环境，发现一个共同的选择影响许多SNP的等位基因频率在世界性的In（3R）P倒位。此外，该应用程序表明，在这个实验中，许多有益的等位基因是显性的。可用性和实现我们的C++实现的'EMWER'是可在https://github.com/kojikoji/EMWER.Supplementary信息补充数据可在生物信息学在线。
Motivation Evolve and resequence (E&R) experiments show promise in capturing real-time evolution at genome-wide scales, enabling the assessment of allele frequency changes SNPs in evolving populations and thus the estimation of population genetic parameters in the Wright-Fisher model (WF) that quantify the selection on SNPs. Currently, these analyses face two key difficulties: the numerous SNPs in E&R data and the frequent unreliability of estimates. Hence, a methodology for efficiently estimating WF parameters is needed to understand the evolutionary processes that shape genomes.Results We developed a novel method for estimating WF parameters (EMWER), by applying an expectation maximization algorithm to the Kolmogorov forward equation associated with the WF model diffusion approximation. EMWER was used to infer the effective population size, selection coefficients and dominance parameters from E&R data. Of the methods examined, EMWER was the most efficient method for selection strength estimation in multi-core computing environments, estimating both selection and dominance with accurate confidence intervals. We applied EMWER to E&R data from experimental Drosophila populations adapting to thermally fluctuating environments and found a common selection affecting allele frequency of many SNPs within the cosmopolitan In(3R)P inversion. Furthermore, this application indicated that many of beneficial alleles in this experiment are dominant.Availability and implementation Our C++ implementation of 'EMWER' is available at https://github.com/kojikoji/EMWER.Supplementary informationSupplementary data are available at Bioinformatics online.