School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 15, CH-1015, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Mol Ecol Resour. 2015 Jan;15(1):87-98. doi: 10.1111/1755-0998.12280. Epub 2014 Jun 11.
With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these data sets. Here, we compare and analyse four recent approaches based on the Wright-Fisher model for inferring selection coefficients (s) given effective population size (N(e)), with simulated temporal data sets. Furthermore, we demonstrate the advantage of a recently proposed approximate Bayesian computation (ABC)-based method that is able to correctly infer genomewide average N(e) from time-serial data, which is then set as a prior for inferring per-site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time-serial data set of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h).
随着测序技术的新发展，时间采样数据变得更加可用和易于获取。自然而然，人们也在努力从这些数据集推断种群遗传参数。在这里，我们比较和分析了基于 Wright-Fisher 模型的四种最新方法，用于在给定有效种群大小 (N(e))的情况下推断选择系数 (s)，并使用模拟的时间数据集进行了分析。此外，我们还展示了最近提出的基于近似贝叶斯计算 (ABC) 的方法的优势，该方法能够从时间序列数据中正确推断出全基因组平均 N(e)，然后将其作为准确和精确推断每个位点选择系数的先验。我们在一个新软件中实现了这种 ABC 方法，并将其应用于鳞翅目夜蛾 Panaxia dominula 中 medionigra 基因型的经典时间序列数据集。我们通过实现显性比 (h) 的估计器，展示了隐性致死模型是对观察到的等位基因频率变化的最佳解释。
