Data from: Phylogenetic assessment of molecular and morphological data for eutherian mammals

The interordinal relationships of eutherian (placental) mammals were evaluated by a phylogenetic analysis of four published data sets (three sequence and one morphological). The nature and degree of support and conflict for particular groups were assessed by separate bootstrap and homogeneity tests that were followed by combined analyses of the sequence and morphological data. Between orders, strong support (i.e., >95% bootstrap scores) was found for a paraphyletic Artiodactyla (relative to Cetacea) and a monophyletic Cetartiodactyla (Artiodactyla and Cetacea) and Paenungulata (Hyracoidea, Proboscidea, and Sirenia). In turn, some reasonable to strong evidence (>85%) was obtained for Hyracoidea with Sirenia, Dermoptera with Scandentia, Glires (Lagomorpha with Rodentia), and Afrotheria (Amblysomus, Macroscelidea, Paenungulata, and Tubulidentata). Otherwise, no other interordinal clades were supported at these reasonable to strong levels. This overall lack of resolution for eutherian interordinal clusters agrees with other studies that further progress will continue to be slow and difficult. Further resolution will require the integration of more recently published data, the continued sampling of taxa and characters, and the use of more powerful methods of data analysis.本研究通过对4套已发表数据集（3套序列数据集与1套形态学数据集）开展系统发育分析，对真兽（胎盘）类哺乳动物（eutherian (placental) mammals）的目间系统发育关系进行了评估。针对各特定类群的支持信号与冲突信号的性质及强度，本研究首先通过独立的自举检验（bootstrap）与同质性检验（homogeneity tests）进行评估，随后对序列数据与形态学数据开展联合分析。在目级阶元之间，并系偶蹄目（Artiodactyla，相对于鲸目Cetacea）、单系鲸偶蹄目（Cetartiodactyla，包含偶蹄目与鲸目）以及近蹄类（Paenungulata，包含蹄兔目Hyracoidea、长鼻目Proboscidea与海牛目Sirenia）获得了较强的支持（自举得分>95%）。此外，蹄兔目与海牛目、皮翼目（Dermoptera）与树鼩目（Scandentia）、啮兔类（Glires，包含兔形目Lagomorpha与啮齿目Rodentia）以及非洲兽总目（Afrotheria，包含金毛鼹属Amblysomus、象鼩目Macroscelidea、近蹄类与管齿目Tubulidentata）获得了中等至较强的证据支持（自举得分>85%）。除此之外，其余所有目间支系均未达到上述中等至较强的支持阈值。真兽类目间聚类整体存在分辨率不足的问题，这一结论与其他相关研究的结论一致，即后续针对该类群系统发育关系的研究进展仍将缓慢且艰难。若要进一步提升系统发育分辨率，则需要整合更多近期发表的研究数据、持续增加类群与性状采样量，并采用更为高效的数据分析方法。