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Statistical Inference of Selection and Divergence from a Time-Dependent Poisson Random Field Model

机译:从时变泊松随机场模型中选择和发散的统计推断

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摘要

We apply a recently developed time-dependent Poisson random field model to aligned DNA sequences from two related biological species to estimate selection coefficients and divergence time. We use Markov chain Monte Carlo methods to estimate species divergence time and selection coefficients for each locus. The model assumes that the selective effects of non-synonymous mutations are normally distributed across genetic loci but constant within loci, and synonymous mutations are selectively neutral. In contrast with previous models, we do not assume that the individual species are at population equilibrium after divergence. Using a data set of 91 genes in two Drosophila species, D. melanogaster and D. simulans, we estimate the species divergence time (or 1.68 million years, assuming the haploid effective population size years) and a mean selection coefficient per generation . Although the average selection coefficient is positive, the magnitude of the selection is quite small. Results from numerical simulations are also presented as an accuracy check for the time-dependent model.
机译:我们应用最近开发的时间相关的泊松随机场模型来对齐来自两个相关生物物种的DNA序列,以估计选择系数和发散时间。我们使用马尔可夫链蒙特卡罗方法来估计每个基因座的物种发散时间和选择系数。该模型假设非同义突变的选择性作用通常在整个遗传基因座上分布,但在基因座内保持恒定,并且同义突变是选择性中性的。与以前的模型相比,我们不假设个体物种在发散后处于种群平衡状态。使用两个果蝇D. melanogaster和D. simulans的91个基因的数据集,我们估计了物种的发散时间(或假定为单倍体有效种群大小的年份为168万年)和每代的平均选择系数。尽管平均选择系数为正,但选择幅度很小。数值模拟的结果也作为与时间相关的模型的准确性检查提供。

著录项

  • 作者

    Amei, Amei; Sawyer, Stanley;

  • 作者单位
  • 年度 2012
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类

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