Centre for Computational Systems Biology, ISTBI, Fudan University, 220 Handan Road, Shanghai 200433, PR China.
Centre for Computational Systems Biology, ISTBI, Fudan University, 220 Handan Road, Shanghai 200433, PR China.
Biosystems. 2023 Sep;231:104982. doi: 10.1016/j.biosystems.2023.104982. Epub 2023 Jul 23.
In this work we present a systematic mathematical approximation scheme that exposes the way that information, about the evolutionary forces of selection and random genetic drift, is encoded within gene-frequency trajectories. We determine approximate, time-dependent, gene-frequency trajectory statistics, assuming additive selection. We use the probability of fixation to test and illustrate the approximation scheme introduced. For the case where the strength of selection and the effective population size have constant values, we show how a standard diffusion approximation result, for the probability of fixation, systematically emerges when increasing numbers of approximate trajectory statistics are taken into account. We then provide examples of how time-dependent parameters influence gene-frequency statistics.
在这项工作中，我们提出了一种系统的数学逼近方案，揭示了信息，关于选择和随机遗传漂变的进化力量，是如何编码在基因频率轨迹中的。我们确定了近似的、时变的、基因频率轨迹统计数据，假设了加性选择。我们使用固定概率来测试和说明所引入的近似方案。对于选择强度和有效种群大小具有恒定值的情况，我们展示了当考虑越来越多的近似轨迹统计数据时，固定概率的标准扩散近似结果是如何系统地出现的。然后，我们提供了一些示例，说明时变参数如何影响基因频率统计数据。
