Evidence map›Paper›PMID 41400012›Full record

ArticleCladistics : the international journal of the Willi Hennig Society2026

Improved taxonomic and gene sampling advance the knowledge of deep relationships within Macrodasyida (Gastrotricha).

Agata Cesaretti, Anush Kosakyan, Francesco Saponi, M Antonio Todaro

Abstract read
In one paragraph

Article in Cladistics : the international journal of the Willi Hennig Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Agata CesarettiDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.ORCID https://orcid.org/0000-0002-3199-9887
Anush KosakyanDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Francesco SaponiDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.
M Antonio TodaroDepartment of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy.

Funding

European Union-NextGenerationEU CN_00000033
6 · The paper itself

Abstract

Advances in Macrodasyida (Gastrotricha) phylogenetics, fuelled by new species discoveries and molecular data, are reshaping taxonomic classifications. Molecular analyses suggest polyphyly in Cephalodasyidae and Macrodasyidae, yet insufficient sampling continues to obscure precise relationships. Our study seeks to enhance the resolution of Macrodasyida's internal phylogeny through expanded taxonomic and molecular sampling. We obtained 63 new sequences from 21 Macrodasyidan species, integrating them with published data. Our dataset includes representatives from nine Macrodasyida families and 21 genera, alongside two chaetonotidans. We analysed the concatenated sequences of three genes (18S, 28S rRNA, COI mtDNA) from 51 terminals using Maximum Parsimony, Maximum Likelihood and Bayesian Inference. Our findings confirm the polyphyly of Cephalodasyidae. Dolichodasys and Paradasys cluster with Redudasyidae, while Cephalodasys and Mesodasys form unrelated lineages. Cephalodasys mahoae is nested within Paradasys rather than Cephalodasys, suggesting an original misidentification. The phylogenetic placement of Pleurodasys remains uncertain. Macrodasyidae is non-monophyletic, with Urodasys forming an independent lineage. The first molecular data ever obtained for Dendrodasys hint that the family Dactylopodolidae is likely polyphyletic as well. We propose an updated classification of Macrodasyida, introducing Mesodasyidae fam. nov., Urodasyidae fam. nov. and Paraurodasys gen. nov. Furthermore, we reassign Dolichodasys and Paradasys to Redudasyidae and Cephalodasys mahoe to Paradasys.

Indexed as

PhylogenyAnimalsBayes TheoremDNA, MitochondrialElectron Transport Complex IVRNA, Ribosomal, 18SRNA, Ribosomal, 28SSequence Analysis, DNADNA, MitochondrialElectron Transport Complex IVRNA, Ribosomal, 18SRNA, Ribosomal, 28S

Identifiers

PMID41400012
PMCPMC12789844

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.