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评估时间序列进化分析中的遗传漂变。

Evaluating genetic drift in time-series evolutionary analysis.

作者信息

R Nené Nuno, Mustonen Ville, J R Illingworth Christopher

机构信息

Department of Genetics, University of Cambridge, Cambridge, UK.

Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK; Department of Biosciences, Department of Computer Science, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland.

出版信息

J Theor Biol. 2018 Jan 21;437:51-57. doi: 10.1016/j.jtbi.2017.09.021. Epub 2017 Sep 25.

Abstract

The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for describing evolutionary trajectories in a finite population. This was found by evaluating its performance against a Gaussian model of allele frequency propagation. However, we note a range of circumstances under which standard Wright-Fisher drift cannot be correctly identified.

摘要

赖特-费希尔模型是描述有限种群规模进化系统行为最流行的种群模型。人们通常使用近似方法,但该模型本身很少根据时间分辨基因组数据进行检验。在此,我们评估在似然框架下它能在多大程度上被推断为正确模型。给定来自一项进化实验的全基因组数据,我们验证赖特-费希尔漂变模型是描述有限种群进化轨迹的更好选择。这是通过将其性能与等位基因频率传播的高斯模型进行比较评估得出的。然而,我们注意到在一系列情况下,标准的赖特-费希尔漂变无法被正确识别。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85be/5703635/0ef0ca5888de/gr1.jpg

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