Schrempf Dominik, Hobolth Asger
Institut für Populationsgenetik, Vetmeduni Vienna, Austria; Vienna Graduate School of Population Genetics, Austria.
Bioinformatics Research Center, Aarhus University, Denmark.
Theor Popul Biol. 2017 Apr;114:88-94. doi: 10.1016/j.tpb.2016.12.001. Epub 2016 Dec 29.
Recently, Burden and Tang (2016) provided an analytical expression for the stationary distribution of the multivariate neutral Wright-Fisher model with low mutation rates. In this paper we present a simple, alternative derivation that illustrates the approximation. Our proof is based on the discrete multivariate boundary mutation model which has three key ingredients. First, the decoupled Moran model is used to describe genetic drift. Second, low mutation rates are assumed by limiting mutations to monomorphic states. Third, the mutation rate matrix is separated into a time-reversible part and a flux part, as suggested by Burden and Tang (2016). An application of our result to data from several great apes reveals that the assumption of stationarity may be inadequate or that other evolutionary forces like selection or biased gene conversion are acting. Furthermore we find that the model with a reversible mutation rate matrix provides a reasonably good fit to the data compared to the one with a non-reversible mutation rate matrix.
最近,伯登和唐(2016年)给出了具有低突变率的多元中性赖特-费希尔模型平稳分布的解析表达式。在本文中,我们给出了一个简单的替代推导,用以说明这种近似。我们的证明基于离散多元边界突变模型,该模型有三个关键要素。首先,解耦的莫兰模型用于描述遗传漂变。其次,通过将突变限制在单态来假设低突变率。第三,如伯登和唐(2016年)所建议的,突变率矩阵被分为时间可逆部分和通量部分。我们的结果应用于几种大猩猩的数据表明,平稳性假设可能不充分,或者存在其他进化力量,如选择或偏向基因转换在起作用。此外,我们发现与具有不可逆突变率矩阵的模型相比,具有可逆突变率矩阵的模型对数据的拟合相当好。