ArticleSystematic biology2021
Morphological Characters Can Strongly Influence Early Animal Relationships Inferred from Phylogenomic Data Sets.
Article in Systematic biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Phylogenetic congruence, conflict and consilience between molecular and morphological data.BMC ecology and evolution · 2023Pooled it
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- A new species ofZooKeys · 2026Article
- What We Talk About When We Talk About Microbial Species.Molecular ecology · 2025Review
- Inter-species differences in wound-healing rate: a comparative study involving primates and rodents.Proceedings. Biological sciences · 2025Article
- Toward a Comprehensive Anatomical Matrix for Crown Birds: Phylogenetic Insights from the Pectoral Girdle and Forelimb Skeleton.Integrative organismal biology (Oxford, England) · 2025Article
- Evaluating the Accuracy of Methods for Detecting Correlated Rates of Molecular and Morphological Evolution.Systematic biology · 2023Article
- The Cambrian cirratuliformProceedings. Biological sciences · 2023Article
- Exploring genome gene content and morphological analysis to test recalcitrant nodes in the animal phylogeny.PloS one · 2023Article
- Review
- Comprehensive Species Sampling and Sophisticated Algorithmic Approaches Refute the Monophyly of Arachnida.Molecular biology and evolution · 2022Article
- Six-State Amino Acid Recoding is not an Effective Strategy to Offset Compositional Heterogeneity and Saturation in Phylogenetic Analyses.Systematic biology · 2021Article
- Fossils improve phylogenetic analyses of morphological characters.Proceedings. Biological sciences · 2021Article
- BAD2matrix: Phylogenomic matrix concatenation, indel coding, and more.Applications in plant sciencesArticle
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Authors and funding
5 authors.
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Abstract
There are considerable phylogenetic incongruencies between morphological and phylogenomic data for the deep evolution of animals. This has contributed to a heated debate over the earliest-branching lineage of the animal kingdom: the sister to all other Metazoa (SOM). Here, we use published phylogenomic data sets ($\sim $45,000-400,000 characters in size with $\sim $15-100 taxa) that focus on early metazoan phylogeny to evaluate the impact of incorporating morphological data sets ($\sim $15-275 characters). We additionally use small exemplar data sets to quantify how increased taxon sampling can help stabilize phylogenetic inferences. We apply a plethora of common methods, that is, likelihood models and their "equivalent" under parsimony: character weighting schemes. Our results are at odds with the typical view of phylogenomics, that is, that genomic-scale data sets will swamp out inferences from morphological data. Instead, weighting morphological data 2-10$\times $ in both likelihood and parsimony can in some cases "flip" which phylum is inferred to be the SOM. This typically results in the molecular hypothesis of Ctenophora as the SOM flipping to Porifera (or occasionally Placozoa). However, greater taxon sampling improves phylogenetic stability, with some of the larger molecular data sets ($>$200,000 characters and up to $\sim $100 taxa) showing node stability even with $\geqq100\times $ upweighting of morphological data. Accordingly, our analyses have three strong messages. 1) The assumption that genomic data will automatically "swamp out" morphological data is not always true for the SOM question. Morphological data have a strong influence in our analyses of combined data sets, even when outnumbered thousands of times by molecular data. Morphology therefore should not be counted out a priori. 2) We here quantify for the first time how the stability of the SOM node improves for several genomic data sets when the taxon sampling is increased. 3) The patterns of "flipping points" (i.e., the weighting of morphological data it takes to change the inferred SOM) carry information about the phylogenetic stability of matrices. The weighting space is an innovative way to assess comparability of data sets that could be developed into a new sensitivity analysis tool. [Metazoa; Morphology; Phylogenomics; Weighting.].
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