UMR CNRS 7207 "Centre de Recherches sur la Paléobiodiversité et les Paléoenvironnements," Muséum National d'Histoire Naturelle, Département Histoire de la Terre, Bâtiment de Géologie, Case Postale 48, 43 Rue Buffon, F-75231 Paris Cedex 05, France.
Syst Biol. 2011 Oct;60(5):630-44. doi: 10.1093/sysbio/syr024. Epub 2011 Mar 28.
Despite the recent surge of interest in studying the evolution of development, surprisingly little work has been done to investigate the phylogenetic signal in developmental characters. Yet, both the potential usefulness of developmental characters in phylogenetic reconstruction and the validity of inferences on the evolution of developmental characters depend on the presence of such a phylogenetic signal and on the ability of our coding scheme to capture it. In a recent study, we showed, using simulations, that a new method (called the continuous analysis) using standardized time or ontogenetic sequence data and squared-change parsimony outperformed event pairing and event cracking in analyzing developmental data on a reference phylogeny. Using the same simulated data, we demonstrate that all these coding methods (event pairing and standardized time or ontogenetic sequence data) can be used to produce phylogenetically informative data. Despite some dependence between characters (the position of an event in an ontogenetic sequence is not independent of the position of other events in the same sequence), parsimony analysis of such characters converges on the correct phylogeny as the amount of data increases. In this context, the new coding method (developed for the continuous analysis) outperforms event pairing; it recovers a lower proportion of incorrect clades. This study thus validates the use of ontogenetic data in phylogenetic inference and presents a simple coding scheme that can extract a reliable phylogenetic signal from these data.
尽管最近人们对研究发育进化的兴趣大增,但令人惊讶的是,很少有人致力于研究发育特征中的系统发育信号。然而,发育特征在系统发育重建中的潜在有用性以及对发育特征进化推断的有效性都取决于是否存在这种系统发育信号,以及我们的编码方案是否能够捕捉到这种信号。在最近的一项研究中,我们使用模拟表明,一种新的方法(称为连续分析),使用标准化时间或个体发育序列数据和平方变化简约法,在分析参考系统发育树上的发育数据方面优于事件配对和事件破解。使用相同的模拟数据,我们证明所有这些编码方法(事件配对和标准化时间或个体发育序列数据)都可用于生成具有系统发育信息的数据。尽管字符之间存在一定的依赖性(事件在个体发育序列中的位置与同一序列中其他事件的位置不独立),但随着数据量的增加,简约分析可以收敛到正确的系统发育树上。在这种情况下,新的编码方法(为连续分析而开发)优于事件配对;它恢复了较低比例的错误分支。因此,这项研究验证了在系统发育推断中使用个体发育数据的合理性,并提出了一种简单的编码方案,可以从这些数据中提取可靠的系统发育信号。