Data from: Concordance analysis in mitogenomic phylogenetics

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.

本文主张采用贝叶斯一致性分析(Bayesian concordance analysis)，作为探索串联线粒体基因组系统发育研究中系统发育信号(phylogenetic signal)强弱与来源的有效方法。尽管该方法通常被用于独立进化基因树的相关研究，但贝叶斯一致性分析也可通过设定反映相似系统发育重建结果预期的先验概率(prior probability)，应用于经独立分析的连锁基因区域。对于线粒体基因组系统发育树中的真实分支，一致性因子(concordance factors)应指代携带特定单系群(clade)系统发育信号的基因区域数量。为展示贝叶斯一致性分析在实证数据中的应用场景，本文采用基于基因的分区策略，对两类蝾螈——小鲵科(Hynobiidae)与无肺螈科(Plethodontidae)的线粒体基因组数据集展开分析。分析结果显示，串联进化树中存在多个一致性因子较高且得到强烈支持的单系群，据此可推断这些类群的系统发育关系是通过分布于整个线粒体基因组的系统发育信号得到稳健解析的。与之形成对比的是，串联进化树中部分获得强烈支持的单系群却拥有较低的一致性因子，这表明这些类群的系统发育重建要么主要由少数基因区域的系统发育信号驱动，要么属于存在不一致性的重建结果——这类重建结果易受数据属性影响而生成不准确的系统发育树，例如碱基组成偏倚、选择压力等。对贝叶斯联合后验树分布的探索，凸显了为相似单系群重建提供系统发育信息的基因分区。本研究在小鲵科数据集的分析中发现，不同的基因组合可支持不同的系统发育树重建结果，因此该方法在此类分析中颇具启发性。通过贝叶斯一致性分析筛选出的不同基因子集的串联分析，生成了获得强烈支持但结果相互矛盾的系统发育树，这揭示了串联线粒体基因组系统发育研究中存在不一致性的可能性。本文呈现的整体研究结果表明，贝叶斯一致性分析可有效探究不同基因区域在线粒体基因组及其他细胞器基因组系统发育研究中的影响。