Data from: Novel approaches for phylogenetic inference from morphological data and total-evidence dating in squamate reptiles (lizards, snakes, and amphisbaenians)

Here, I combine previously underutilized models and priors to perform more biologically-realistic phylogenetic inference from morphological data, with an example from squamate reptiles. When coding morphological characters, it is often possible to denote ordered states with explicit reference to observed or hypothetical ancestral conditions. Using this logic, we can integrate across character-state labels and estimate meaningful rates of forward and backwards transitions from plesiomorphy to apomorphy. I refer to this approach as MkA, for 'asymmetric.' The MkA model incorporates the biological reality of limited reversal for many phylogenetically informative characters, and significantly increases likelihoods in the empirical datasets. Despite this, the phylogeny of Squamata remains contentious. Total-evidence analyses using combined morphological and molecular data and the MkA approach tend towards recent consensus estimates supporting a nested Iguania. However, support for this topology is not unambiguous across datasets or analyses, and no mechanism has been proposed to explain the widespread incongruence between partitions, or the hidden support for various topologies in those partitions. Furthermore, different morphological datasets produced by different authors contain both different characters and different states for the same or similar characters, resulting in drastically different placements for many important fossil lineages. Effort is needed to standardize ontology for morphology, resolve incongruence, and estimate a robust phylogeny. The MkA approach provides a preliminary avenue for investigating morphological evolution while accounting for temporal evidence and asymmetry in character-state changes.本研究将此前未被充分利用的模型与先验信息相结合，以基于形态学数据开展更符合生物学现实的系统发育推断（phylogenetic inference），并以有鳞目爬行动物为例展开说明。在编码形态学性状时，通常可以通过明确参照观测到的或假想的祖先状态，来标注有序性状状态。基于这一逻辑，我们可以整合所有性状状态标签，并估算从祖征（plesiomorphy）到衍征（apomorphy）的正向与反向转变的有效速率。本研究将该方法命名为MkA，即“非对称模型”。MkA模型纳入了许多系统发育信息性状存在有限反转的生物学现实，并显著提升了经验数据集的似然值。即便如此，有鳞目的系统发育关系仍存在争议。结合形态学与分子数据并采用MkA方法的总证据分析（total-evidence analyses），倾向于支持近期达成的共识估算结果，即鬣蜥亚目（Iguania）为嵌套类群。然而，不同数据集或分析方法对该拓扑结构的支持并不明确，且目前尚无研究提出可解释数据分区间普遍存在的不一致性，或解释这些分区中对不同拓扑结构的隐性支持的机制。此外，不同研究者构建的形态学数据集不仅性状各异，同一或相似性状的状态定义也存在差异，这导致许多重要化石支系的系统发育位置出现极大分歧。当前亟需开展相关工作，以统一形态学本体（ontology）标准、解决数据不一致性，并构建可靠的系统发育树。MkA方法为研究形态演化提供了一条初步途径，可同时纳入时间证据与性状状态转变的非对称性。