Evidence map›Paper›PMID 41755628›Full record

ArticleGenome biology and evolution2026

Genomes From 117 Vertebrate Species Reveal Rapidly Evolving Segmental-Duplication Landscapes.

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

Abstract read
In one paragraph

Article in Genome biology and evolution, 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

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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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Alber AqilGilbert S. Omenn Department 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.
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 MasudaGilbert S. Omenn Department 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 one starfish, generating the largest multispecies 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 metrics to quantify the duplication landscape for that species. We then compute interspecies distances for each metric and find that these distances show at most weak correlations with phylogenetic distance, indicating that segmental-duplication landscapes evolve rapidly. Functional-enrichment analysis of hyperduplicated genes reveals a strong enrichment in platypus for pheromone response, driven by the expansion of the vomeronasal pheromone receptor V1R gene family. Overall, our results uncover the general properties of vertebrate segmental duplications, demonstrate the lability of segmental-duplication landscapes, and highlight the utility of network-based approaches for studying genome evolution.

Indexed as

Evolution, MolecularGenomeSegmental Duplications, GenomicVertebratesAnimalsGene DuplicationHumansPhylogenyPlatypusReceptors, PheromoneStarfishReceptors, Pheromonebiological networksinterspersed duplicationplatypussegmental-duplication networkstandem duplicationvertebrate evolution

Identifiers

PMID41755628
PMCPMC13431229

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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.