Kennedy Martyn, Holland Barbara R, Gray Russell D, Spencer Hamish G
Allan Wilson Centre for Molecular Ecology and Evolution, Department of Zoology, University of Otago, Dunedin, New Zealand.
Syst Biol. 2005 Aug;54(4):620-33. doi: 10.1080/106351591007462.
Long-branch attraction is a well-known source of systematic error that can mislead phylogenetic methods; it is frequently invoked post hoc, upon recovering a different tree from the one expected based on prior evidence. We demonstrate that methods that do not force the data onto a single tree, such as spectral analysis, Neighbor-Net, and consensus networks, can be used to detect conflicting signals within the data, including those caused by long-branch attraction. We illustrate this approach using a set of taxa from three unambiguously monophyletic families within the Pelecaniformes: the darters, the cormorants and shags, and the gannets and boobies. These three families are universally acknowledged as forming a monophyletic group, but the relationship between the families remains contentious. Using sequence data from three mitochondrial genes (12S, ATPase 6, and ATPase 8) we demonstrate that the relationship between these three families is difficult to resolve because they are separated by a short internal branch and there are conflicting signals due to long-branch attraction, which are confounded with nonhomogeneous sequence evolution across the different genes. Spectral analysis, Neighbor-Net, and consensus networks reveal conflicting signals regarding the placement of one of the darters, with support found for darter monophyly, but also support for a conflicting grouping with the outgroup, pelicans. Furthermore, parsimony and maximum-likelihood analyses produced different trees, with one of the two most parsimonious trees not supporting the monophyly of the darters. Monte Carlo simulations, however, were not sensitive enough to reveal long-branch attraction unless the branches are longer than those actually observed. These results indicate that spectral analysis, Neighbor-Net, and consensus networks offer a powerful approach to detecting and understanding the source of conflicting signals within phylogenetic data.
长枝吸引是一种众所周知的系统误差来源，它会误导系统发育方法；在根据先前证据得到的树与预期的树不同时，人们经常事后援引这一概念。我们证明，不将数据强制置于单一树的方法，如光谱分析、邻接网络和共识网络，可用于检测数据中的冲突信号，包括由长枝吸引引起的信号。我们使用鹈形目三个明确单系科的一组分类群来说明这种方法：蛇鹈科、鸬鹚科和鲣鸟科。这三个科被普遍认为构成一个单系类群，但科之间的关系仍存在争议。利用来自三个线粒体基因（12S、ATP酶6和ATP酶8）的序列数据，我们证明这三个科之间的关系难以解决，因为它们被一个短的内部分支隔开，并且由于长枝吸引存在冲突信号，这些信号与不同基因间的非均匀序列进化相混淆。光谱分析、邻接网络和共识网络揭示了关于一种蛇鹈位置的冲突信号，既支持蛇鹈的单系性，也支持与外类群鹈鹕的冲突分组。此外，简约分析和最大似然分析产生了不同的树，两个最简约树中的一个不支持蛇鹈的单系性。然而，蒙特卡洛模拟不够敏感，无法揭示长枝吸引，除非分支比实际观察到的更长。这些结果表明，光谱分析、邻接网络和共识网络为检测和理解系统发育数据中冲突信号的来源提供了一种有力方法。
