Delimiting species using single-locus data and the Generalized Mixed Yule Coalescent approach: a revised method and evaluation on simulated data sets.
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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DOI：
10.1093/sysbio/syt033
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发表时间：
2013-09
影响因子：
6.5
通讯作者：
Barraclough TG
中科院分区：
文献类型：
--
作者：
Fujisawa T;Barraclough TG
DNA条形码型研究从大量个体和物种样本中收集单位点数据，并为多样性的进化调查提供了新的数据种类。许多这类研究的一个重要目标是划分进化上重要的物种单位，特别是在生物多样性调查中从环境DNA样本。GMYC方法是一种通过拟合种内和种间分支模型重构基因树来划分物种的似然方法。尽管该方法已被广泛使用，但尚未对其进行详细描述或对种群变异和物种间分化的真实模式的替代情景模拟进行充分评估。在这里，我们提出了最初指定的GMYC方法的重要重新表述，并证明了其对一系列偏离其简化假设的鲁棒性。影响划界精度的主要因素是物种的平均种群大小相对于它们之间的分化时间。其他偏离模型假设的因素，如物种间不同的种群规模、物种形成和灭绝的不同情景、物种内的种群增长或细分，影响相对较小。我们的模拟表明，来自似然函数的支持度量提供了一个稳健的指示，说明模型何时表现良好，何时导致不准确的划界。最后，该方法的所谓单阈值版本在模拟数据上优于该方法的多阈值版本：我们认为，由于该方法中用于划分物种的证据的性质，这可能代表了一个基本限制。与其他比较其相对于其他方法的性能的研究一起，我们的发现支持GMYC在只有单位点信息时作为划分物种的工具的稳健性。[集群;合并的;DNA;系谱;中性的;物种形成;物种。)
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. [Clusters; coalescent; DNA; genealogical; neutral; speciation; species.]
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影响因子：
6.5
作者：
De Queiroz, Kevin
通讯作者：
De Queiroz, Kevin
DOI：
10.1073/pnas.91.14.6491
发表时间：
1994-07-05
影响因子：
11.1
作者：
BROWER, AVZ
通讯作者：
BROWER, AVZ
影响因子：
6.5
作者：
Camargo, Arley;Avila, Luciano J.;Sites, Jack W., Jr.
通讯作者：
Sites, Jack W., Jr.
影响因子：
5.8
作者：
Bortolussi, N;Durand, E;François, O
通讯作者：
François, O
影响因子：
2
作者：
Barraclough, TG;Herniou, E
通讯作者：
Herniou, E