Evidence map›Paper›PMID 41292765›Full record

ArticlebioRxiv : the preprint server for biology2025

Genomes from 117 vertebrate species reveal rapidly evolving segmental duplication landscapes.

Alber Aqil, Saiful Islam, Faraz Hach, Ibrahim Numanagić, Naoki Masuda, Omer Gokcumen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Alber AqilDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0002-6784-6495
Saiful IslamInstitute for Artificial Intelligence and Data Science, State University of New York at Buffalo, Buffalo, NY, USA.ORCID 0009-0007-9161-6706
Faraz HachVancouver Prostate Centre, Vancouver, British Columbia, Canada.ORCID 0000-0003-1143-0172
Ibrahim NumanagićDepartment of Computer Science, University of Victoria, Victoria, BC, Canada.ORCID 0000-0002-2970-7937
Naoki MasudaDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.ORCID 0000-0003-1567-801X
Omer GokcumenDepartment of Biological Sciences, State University of New York at Buffalo, Buffalo, NY, USA.ORCID 0000-0003-4371-679X

Funding

DMS/NIGMS 1: Multilayer network approach to tandem repeat variation in genomesR01GM148973 · NIGMS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MASUDA, NAOKI · 2022 to 2024
$444k
NIGMS NIH HHS R01 GM148973
6 · The paper itself

Abstract

Segmental duplications are major drivers of evolutionary innovation, yet their dynamics across vertebrates remain poorly understood. Here, we identify segmental duplications from long-read sequenced genomes of 117 vertebrates and the starfish, generating the largest multi-species dataset of its kind. We find that vertebrate genomes show a higher propensity for tandem duplications than for interspersed duplications. However, when focusing only on subtelomeric regions, avian and mammalian genomes show the opposite propensity toward interspersed duplications. We also observe that, across vertebrates, tandem duplications tend to be larger than interspersed duplications. Next, we construct a segmental duplication network for each species, and use network-derived properties to quantify the duplication landscape for that species. Functional enrichment analysis of hyper-duplicated genes reveals a strong enrichment in platypus for pheromone response, driven by the expansion of the vomeronasal pheromone receptor

Indexed as

biological networksinterspersed duplicationplatypussegmental duplicationsegmental duplication networkstandem duplicationvertebrate evolution

Identifiers

PMID41292765
PMCPMC12642534

What OpenQuestion holds

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LicenceCC BY-ND
Read underepoch 390

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.