Evidence map›Paper›PMID 40830726›Full record

ArticleNature ecology & evolution2025

EdgeHOG: a method for fine-grained ancestral gene order inference at large scale.

Charles Bernard, Yannis Nevers, Naga Bhushana Rao Karampudi, Kimberly J Gilbert, Clément Train, Alex Warwick Vesztrocy, Natasha Glover, Adrian Altenhoff, Christophe Dessimoz

Abstract read
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In one paragraph

Article in Nature ecology & evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
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

9 authors.

Charles BernardDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Yannis NeversDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-8604-2943
Naga Bhushana Rao KarampudiDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-0503-4301
Kimberly J GilbertDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Clément TrainDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Alex Warwick VesztrocyDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Natasha GloverDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Adrian AltenhoffSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.ORCID http://orcid.org/0000-0001-7492-1273
Christophe DessimozDepartment of Computational Biology, University of Lausanne, Lausanne, Switzerland. christophe.dessimoz@unil.ch.ORCID http://orcid.org/0000-0002-2170-853X

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 205085Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) SNSF grant 205085
6 · The paper itself

Abstract

Ancestral genomes are essential for studying the diversification of life from the last universal common ancestor to modern organisms. Methods have been proposed to infer ancestral gene order, but they lack scalability, limiting the depth to which gene neighbourhood evolution can be traced back. Here we introduce edgeHOG, a tool designed for accurate ancestral gene order inference with linear time complexity. We validated edgeHOG on various benchmarks and applied it to the entire OMA orthology database, encompassing 2,845 extant genomes across all domains of life. We reconstructed ancestral gene order for 1,133 ancestral genomes, including ancestral contigs for the last common ancestor of eukaryotes, dating back around 1.8 billion years, and observed significant functional association among neighbouring genes. EdgeHOG also dates gene adjacencies, allowing the detection of both conserved gene clusters and chromosomal rearrangements.

Indexed as

Evolution, MolecularGenomeSoftwareEukaryotaPhylogeny

Identifiers

PMID40830726
PMCPMC12507687

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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.