Department of Biology, University of Kentucky, Lexington, KY 40506, USA.
Mol Phylogenet Evol. 2012 Oct;65(1):194-202. doi: 10.1016/j.ympev.2012.06.003. Epub 2012 Jun 15.
Here I advocate the utility of Bayesian concordance analysis as a mechanism for exploring the magnitude and source of phylogenetic signal in concatenated mitogenomic phylogenetic studies. While typically applied to the study of independently evolving gene trees, Bayesian concordance analysis can also be applied to linked, but individually analyzed, gene regions using a prior probability that reflects the expectation of similar phylogenetic reconstructions. For true branches in the mitogenomic tree, concordance factors should represent the number of gene regions that contain phylogenetic signal for a particular clade. As a demonstration of the application of Bayesian concordance analysis to empirical data, I analyzed two different salamander (Hynobiidae and Plethodontidae) mitogenomic data sets using a gene-based partitioning strategy. The results revealed many strongly supported clades in the concatenated trees that have high concordance factors, permitting the inference that these are robustly resolved through phylogenetic signal distributed across the mitogenome. In contrast, a number of strongly supported clades in the concatenated tree received low concordance factors, indicating that their reconstruction is either driven primarily by phylogenetic signal in a small number of gene regions, or that they are inconsistent reconstructions influenced by properties of the data that can produce inaccurate trees (e.g., compositional bias, selection, etc.). Exploration of the Bayesian joint posterior distribution of trees highlighted partitions that contribute phylogenetic information to similar clade reconstructions. This approach was particularly insightful in the hynobiid data, where different combinations of genes were identified that support alternative tree reconstructions. Concatenated analysis of these different subsets of genes highlighted through Bayesian concordance analysis produced strongly supported and contrasting trees, demonstrating the potential for inconsistency in concatenated mitogenomic phylogenetics. The overall results presented here suggest that Bayesian concordance analysis can serve as an effective exploration of the influence of different gene regions in mitogenomic (and other organellar genomic) phylogenetic studies.
在这里,我提倡将贝叶斯一致性分析作为一种机制,用于探索串联线粒体基因组系统发育研究中系统发育信号的大小和来源。虽然贝叶斯一致性分析通常应用于独立进化的基因树研究,但它也可以应用于链接但单独分析的基因区域,使用反映类似系统发育重建预期的先验概率。对于线粒体基因组树中的真实分支,一致性因子应代表包含特定分支系统发育信号的基因区域数量。作为贝叶斯一致性分析在实证数据中的应用的一个演示,我使用基于基因的分区策略分析了两种不同的蝾螈(有尾目和无尾目)线粒体基因组数据集。结果表明,在串联树中,许多强烈支持的分支具有高一致性因子,这表明通过分布在整个线粒体基因组中的系统发育信号稳健地解决了这些分支。相比之下,串联树中许多强烈支持的分支获得了低一致性因子,这表明它们的重建要么主要由少数基因区域的系统发育信号驱动,要么它们是由可能产生不准确树的数据集的特性(如组成偏差、选择等)驱动的不一致重建。对树的贝叶斯联合后验分布的探索突出了对相似分支重建有贡献的分区。这种方法在有尾目数据中特别有见地,其中确定了支持替代树重建的不同基因组合。通过贝叶斯一致性分析突出显示的这些不同基因子集的串联分析产生了强烈支持和对比的树,证明了串联线粒体基因组系统发生学中不一致的可能性。这里提出的总体结果表明,贝叶斯一致性分析可以作为一种有效的方法,用于探索不同基因区域在线粒体基因组(和其他细胞器基因组)系统发育研究中的影响。