Pandemic Sciences Institute and Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK.
Biomathematics and Statistics Scotland, The James Hutton Institute, Edinburgh EH9 3FD, UK.
Genes (Basel). 2023 Sep 2;14(9):1751. doi: 10.3390/genes14091751.
In the diffusion approximation of the neutral Wright-Fisher model, the expected time until fixation or loss of a neutral allele is proportional to the initial entropy of the distribution of the allele in the population. No explanation is known for this coincidence. In this paper, we show that the rate of entropy dissipation is proportional to the number of segregating alleles. Since the final fixed state has zero entropy, the expected lifetime of segregating alleles is proportional to the initial entropy in the system. We show that classical formulae on the average time to loss of segregating alleles and the expected time to fixation of the last segregating allele stem from these properties of the diffusion process. We also extend our results to the case of population size changing in time. The dissipation of heterozygosity and entropy shows that superlinear population growth leads to infinite expected fixation times, i.e., neutral alleles in fast-growing populations could segregate forever without ever becoming fixed or disappearing by genetic drift.
在中性 Wright-Fisher 模型的扩散近似中,中性等位基因固定或丢失的预期时间与等位基因在群体中的分布初始熵成正比。对于这种巧合,目前还没有解释。在本文中,我们证明了熵耗散率与分离等位基因的数量成正比。由于最终固定状态的熵为零,因此分离等位基因的预期寿命与系统中的初始熵成正比。我们表明,关于分离等位基因丢失的平均时间和最后一个分离等位基因固定的预期时间的经典公式源于扩散过程的这些性质。我们还将我们的结果扩展到群体大小随时间变化的情况。杂合性和熵的耗散表明,超线性种群增长导致固定时间的无穷大,即在快速增长的种群中,中性等位基因可能永远不会固定或因遗传漂变而消失。