Evidence map›Paper›PMID 28460059›Full record

ArticleMolecular biology and evolution2017

Insights into Ciliary Genes and Evolution from Multi-Level Phylogenetic Profiling.

Yannis Nevers, Megana K Prasad, Laetitia Poidevin, Kirsley Chennen, Alexis Allot, Arnaud Kress, Raymond Ripp, Julie D Thompson, Hélène Dollfus, Olivier Poch and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Molecular biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
7.5field-weighted citation impact, top 3% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

37 citing papers in PubMed, 75 citations in OpenAlex.

  1. Primary cilia: sensors of biliary homeostasis and disease.Nature reviews. Gastroenterology & hepatology · 2026
    Review
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  15. WGS Revealed NovelInternational journal of molecular sciences · 2023
    Article
  16. Phylogenetic profiling in eukaryotes comes of age.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  17. Identification of hidden associations among eukaryotic genes through statistical analysis of coevolutionary transitions.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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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

11 authors at 2 institutions in 1 country.

Yannis NeversComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Megana K PrasadLaboratoire de Génétique Médicale, Institut de Génétique Médicale d'Alsace, INSERM U1112, Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, France.
Laetitia PoidevinComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Kirsley ChennenComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Alexis AllotComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Arnaud KressComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Raymond RippComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Julie D ThompsonComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Hélène DollfusLaboratoire de Génétique Médicale, Institut de Génétique Médicale d'Alsace, INSERM U1112, Université de Strasbourg, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Strasbourg, France.
Olivier PochComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Odile LecompteComplex Systems and Translational Bioinformatics, ICube UMR 7357, Université de Strasbourg, Fédération de Médecine Translationnelle, Strasbourg, France.
Université de Strasbourg · FRInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cilia (flagella) are important eukaryotic organelles, present in the Last Eukaryotic Common Ancestor, and are involved in cell motility and integration of extracellular signals. Ciliary dysfunction causes a class of genetic diseases, known as ciliopathies, however current knowledge of the underlying mechanisms is still limited and a better characterization of genes is needed. As cilia have been lost independently several times during evolution and they are subject to important functional variation between species, ciliary genes can be investigated through comparative genomics. We performed phylogenetic profiling by predicting orthologs of human protein-coding genes in 100 eukaryotic species. The analysis integrated three independent methods to predict a consensus set of 274 ciliary genes, including 87 new promising candidates. A fine-grained analysis of the phylogenetic profiles allowed a partitioning of ciliary genes into modules with distinct evolutionary histories and ciliary functions (assembly, movement, centriole, etc.) and thus propagation of potential annotations to previously undocumented genes. The cilia/basal body localization was experimentally confirmed for five of these previously unannotated proteins (LRRC23, LRRC34, TEX9, WDR27, and BIVM), validating the relevance of our approach. Furthermore, our multi-level analysis sheds light on the core gene sets retained in gamete-only flagellates or Ecdysozoa for instance. By combining gene-centric and species-oriented analyses, this work reveals new ciliary and ciliopathy gene candidates and provides clues about the evolution of ciliary processes in the eukaryotic domain. Additionally, the positive and negative reference gene sets and the phylogenetic profile of human genes constructed during this study can be exploited in future work.

Indexed as

AnimalsCell MovementCiliaCiliopathiesDatabases, Nucleic AcidEukaryotaEukaryotic CellsEvolution, MolecularFlagellaGenomicsHumansPhylogenySequence Analysis, DNAciliopathiesciliumcomparative genomicsevolutionphylogenetic profiling

Identifiers

PMID28460059
PMCPMC5850483
OpenAlexW2609827283

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.