Zhou Yan, Rodrigue Nicolas, Lartillot Nicolas, Philippe Hervé
Canadian Institute for Advanced Research, Département de Biochimie, Université de Montréal, Succursale Centre-Ville, Montréal, Québec H3C3J7, Canada.
BMC Evol Biol. 2007 Nov 1;7:206. doi: 10.1186/1471-2148-7-206.
The evolutionary rate at a given homologous position varies across time. When sufficiently pronounced, this phenomenon - called heterotachy - may produce artefactual phylogenetic reconstructions under the commonly used models of sequence evolution. These observations have motivated the development of models that explicitly recognize heterotachy, with research directions proposed along two main axes: 1) the covarion approach, where sites switch from variable to invariable states; and 2) the mixture of branch lengths (MBL) approach, where alignment patterns are assumed to arise from one of several sets of branch lengths, under a given phylogeny.
Here, we report the first statistical comparisons contrasting the performance of covarion and MBL modeling strategies. Using simulations under heterotachous conditions, we explore the properties of three model comparison methods: the Akaike information criterion, the Bayesian information criterion, and cross validation. Although more time consuming, cross validation appears more reliable than AIC and BIC as it directly measures the predictive power of a model on 'future' data. We also analyze three large datasets (nuclear proteins of animals, mitochondrial proteins of mammals, and plastid proteins of plants), and find the optimal number of components of the MBL model to be two for all datasets, indicating that this model is preferred over the standard homogeneous model. However, the covarion model is always favored over the optimal MBL model.
We demonstrated, using three large datasets, that the covarion model is more efficient at handling heterotachy than the MBL model. This is probably due to the fact that the MBL model requires a serious increase in the number of parameters, as compared to two supplementary parameters of the covarion approach. Further improvements of the both the mixture and the covarion approaches might be obtained by modeling heterogeneous behavior both along time and across sites.
给定同源位置的进化速率会随时间变化。当这种现象足够明显时——称为异速进化——在常用的序列进化模型下可能会产生人为的系统发育重建。这些观察结果推动了明确识别异速进化的模型的发展，研究方向主要沿着两个主轴提出：1）协变位点模型，其中位点从可变状态转变为不变状态；2）分支长度混合（MBL）模型，在给定的系统发育下，比对模式被假定为由几组分支长度中的一组产生。
在此，我们报告了首次对协变位点模型和MBL建模策略的性能进行对比的统计分析。利用异速进化条件下的模拟，我们探索了三种模型比较方法的特性：赤池信息准则、贝叶斯信息准则和交叉验证。虽然交叉验证耗时更多，但它似乎比AIC和BIC更可靠，因为它直接测量模型对“未来”数据的预测能力。我们还分析了三个大型数据集（动物的核蛋白、哺乳动物的线粒体蛋白和植物的质体蛋白），并发现所有数据集的MBL模型的最佳成分数量均为两个，这表明该模型优于标准的齐次模型。然而，协变位点模型总是比最优的MBL模型更受青睐。
我们利用三个大型数据集证明，协变位点模型在处理异速进化方面比MBL模型更有效。这可能是由于与协变位点模型的两个补充参数相比，MBL模型需要大幅增加参数数量。通过对沿时间和跨位点的异质性行为进行建模，可能会进一步改进混合模型和协变位点模型。
