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Maximum Likelihood Implementation of an Isolation-with-Migration Model with Three Species for Testing Speciation with Gene Flow

机译:具有基因流测试物种的具有三种物种的带迁移隔离模型的最大似然实现

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We implement an isolation with migration model for three species, with migration occurring between two closely related species while an out-group species is used to provide further information concerning gene trees and model parameters. The model is implemented in the likelihood framework for analyzing multilocus genomic sequence alignments, with one sequence sampled from each of the three species. The prior distribution of gene tree topology and branch lengths at every locus is calculated using a Markov chain characterization of the genealogical process of coalescent and migration, which integrates over the histories of migration events analytically. The likelihood function is calculated by integrating over branch lengths in the gene trees (coalescent times) numerically. We analyze the model to study the gene tree-species tree mismatch probability and the time to the most recent common ancestor at a locus. The model is used to construct a likelihood ratio test (LRT) of speciation with gene flow. We conduct computer simulations to evaluate the LRT and found that the test is in general conservative, with the false positive rate well below the significance level. For the test to have substantial power, hundreds of loci are needed. Application of the test to a human–chimpanzee–gorilla genomic data set suggests gene flow around the time of speciation of the human and the chimpanzee.
机译:我们对三个物种实施了带迁移模型的隔离,其中迁移发生在两个紧密相关的物种之间,而外群物种用于提供有关基因树和模型参数的更多信息。该模型在可能性框架中实现,用于分析多基因座基因组序列比对,并从三个物种的每一个中采样一个序列。使用聚结和迁移的族谱过程的马尔可夫链特征计算基因树拓扑结构和每个位置的分支长度的先验分布,该特征可分析性地整合了迁移事件的历史记录。通过对基因树的分支长度(聚结时间)进行数值积分来计算似然函数。我们分析该模型,以研究基因树种与树种的不匹配概率以及在某个地点到最近的共同祖先的时间。该模型用于构建具有基因流的物种形成的似然比检验(LRT)。我们进行了计算机仿真以评估LRT,发现该测试通常是保守的,其误报率远低于显着性水平。为了使测试具有强大的功能,需要数百个基因座。该测试在人类-黑猩猩-大猩猩基因组数据集上的应用表明,在人类和黑猩猩形成物种的那段时间,基因流不断。

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  • 来源
    《Molecular Biology and Evolution》 |2012年第10期|p.3131-3142|共12页
  • 作者单位

    1School of Mathematical Sciences, Peking University, Beijing, China 2National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, 100190, Beijing, China 3Center for Computational and Evolutionary Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China 4Computational Biochemistry Research Group, ETH Zurich, Zurich, Switzerland 5Department of Biology, Galton Laboratory, University College London, London, United Kingdom;

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