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首页> 外文期刊>Systematic Biology >Delimiting Species Using Single-Locus Data and the Generalized Mixed Yule Coalescent Approach: A Revised Method and Evaluation on Simulated Data Sets
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Delimiting Species Using Single-Locus Data and the Generalized Mixed Yule Coalescent Approach: A Revised Method and Evaluation on Simulated Data Sets

机译:使用单基因座数据和广义混合Yule合并方法定界物种:一种修正的方法和对模拟数据集的评估

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DNA barcoding-type studies assemble single-locus data from large samples of individuals and species, and have provided new kinds of data for evolutionary surveys of diversity An important goal of many such studies is to delimit evolutionarily significant species units, especially in biodiversity surveys from environmental DNA samples. The Generalized Mixed Yule Coalescent (GMYC) method is a likelihood method for delimiting species by fitting within- and between-species branching models to reconstructed gene trees. Although the method has been widely used, it has not previously been described in detail or evaluated fully against simulations of alternative scenarios of true patterns of population variation and divergence between species. Here, we present important reformulations to the GMYC method as originally specified, and demonstrate its robustness to a range of departures from its simplifying assumptions. The main factor affecting the accuracy of delimitation is the mean population size of species relative to divergence times between them. Other departures from the model assumptions, such as varying population sizes among species, alternative scenarios for speciation and extinction, and population growth or subdivision within species, have relatively smaller effects. Our simulations demonstrate that support measures derived from the likelihood function provide a robust indication of when the model performs well and when it leads to inaccurate delimitations. Finally, the so-called single-threshold version of the method outperforms the multiple-threshold version of the method on simulated data: we argue that this might represent a fundamental limit due to the nature of evidence used to delimit species in this approach. Together with other studies comparing its performance relative to other methods, our findings support the robustness of GMYC as a tool for delimiting species when only single-locus information is available.
机译:DNA条形码类型研究从大量个体和物种样本中收集了单基因座数据,并为多样性的进化调查提供了新种类的数据。许多此类研究的重要目标是划定具有进化意义的物种单位,尤其是在环境DNA样本。通用混合Yule合并(GMYC)方法是一种通过将物种内和物种间分支模型拟合到重构基因树来界定物种的可能性方法。尽管该方法已被广泛使用,但以前并未对其进行详细描述或针对种群真实变异和物种间趋异模式的替代方案进行完整评估。在此,我们对最初指定的GMYC方法进行了重要的重新表述,并展示了其在一定程度上偏离其简化假设的鲁棒性。影响定界准确性的主要因素是物种的平均种群大小相对于它们之间的分歧时间。与模型假设的其他偏离,例如物种间种群数量的变化,物种形成和灭绝的替代方案以及物种内种群增长或细分的影响相对较小。我们的模拟表明,从似然函数得出的支持量度可以很好地表明模型何时运行良好以及何时导致不正确的定界。最后,在模拟数据上,该方法的所谓单阈值版本优于该方法的多阈值版本:我们认为,由于用于定界此物种的证据的性质,这可能代表了一个基本限制。与其他研究比较其相对于其他方法的性能的研究一起,我们的研究结果支持GMYC作为仅用于单个位置信息的定界物种的工具的鲁棒性。

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