Pyron R Alexander
Department of Biological Sciences, The George Washington University, 2023 G St. NW, Washington, DC, USA.
Syst Biol. 2017 Jan 1;66(1):38-56. doi: 10.1093/sysbio/syw068.
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 backward 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 data sets. Despite this, the phylogeny of Squamata remains contentious. Total-evidence analyses using combined morphological and molecular data and the MkA approach tend toward recent consensus estimates supporting a nested Iguania. However, support for this topology is not unambiguous across data sets 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 data sets 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.
在此,我结合了先前未充分利用的模型和先验知识,以从形态学数据进行更符合生物学实际的系统发育推断,并以有鳞类爬行动物为例。在对形态特征进行编码时,通常可以通过明确参考观察到的或假设的祖先状态来表示有序状态。运用这一逻辑,我们可以整合特征状态标签,并估计从近裔共性到裔征的正向和反向转变的有意义速率。我将这种方法称为MkA,即“不对称”之意。MkA模型纳入了许多系统发育信息特征的有限反转这一生物学现实,并显著提高了实证数据集中的似然性。尽管如此,有鳞目动物的系统发育仍然存在争议。使用形态学和分子数据相结合的全证据分析以及MkA方法倾向于支持近期的共识估计,即支持嵌套的鬣蜥亚目。然而,在不同数据集或分析中,对这种拓扑结构的支持并非明确无误,而且尚未提出任何机制来解释各部分之间广泛存在的不一致性,或这些部分中对各种拓扑结构的隐性支持。此外,不同作者生成的不同形态学数据集既包含不同的特征,也包含相同或相似特征的不同状态,导致许多重要化石谱系的位置截然不同。需要努力规范形态学的本体论,解决不一致性问题,并估计出一个可靠的系统发育。MkA方法为研究形态进化提供了一条初步途径,同时考虑了时间证据和特征状态变化中的不对称性。