Data from: Predictions of single-nucleotide polymorphism differentiation between two populations in terms of mutual information

Mutual information (I) provides a robust measure of genetic differentiation for the purposes of estimating dispersal between populations. At present, however, there is little predictive theory for I. The growing importance in population biology of analyses of single-nucleotide and other single feature polymorphisms (SFPs) is a potent reason for developing an analytic theory for I with respect to a single locus. This study represents a first step towards such a theory. We present theoretical predictions of I between two populations with respect to a single haploid biallelic locus. Dynamical and steady-state forecasts of I are derived from a Wright-Fisher model with symmetric mutation between alleles and symmetric dispersal between populations. Analytical predictions of a simple Taylor approximation to I are in good agreement with numerical simulations of I and with data on I from SFP analyses of dispersal experiments on Drosophila fly populations. The theory presented here also provides a basis for the future inclusion of selection effects and extension to multi-allelic loci.

互信息（Mutual Information, I）是一种用于估算种群间扩散水平的稳健遗传分化测度。然而目前针对该指标的预测性理论仍较为匮乏。当前，单核苷酸多态性及其他单特征多态性（Single Feature Polymorphisms, SFPs）分析在种群生物学中的重要性与日俱增，这为构建针对单基因座的互信息解析理论提供了重要契机。本研究即为该理论构建迈出了第一步。我们针对单倍体双等位基因座，推导了两个种群间互信息的理论预测结果。该研究基于赖特-费希尔模型（Wright-Fisher Model），纳入等位基因间的对称突变与种群间的对称扩散过程，由此得到互信息的动态变化与稳态预测。我们通过对互信息进行简单泰勒近似得到的解析预测结果，与互信息的数值模拟结果以及果蝇种群扩散实验的单特征多态性分析数据均具有良好的一致性。本文提出的理论框架同时为后续纳入选择效应以及拓展至多等位基因座的研究提供了理论基础。