Evidence map›Paper›PMID 38632352›Full record

ArticleScientific reports2024

Shark genome size evolution and its relationship with cellular, life-history, ecological, and diversity traits.

Mario Torralba Sáez, Michael Hofreiter, Nicolas Straube

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

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

1 citing paper in PubMed.

  1. Silver chimaera genome highlights lineage-specific sex chromosome and opsin gene evolution in holocephalans.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026
    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

3 authors.

Mario Torralba SáezIchthyology Section, Bavarian State Collection of Zoology (SNSB-ZSM), 81247, Munich, Germany.
Michael HofreiterEvolutionary Adaptive Genomics, Institute for Biochemistry and Biology, University of Potsdam, 14476, Potsdam, Germany.
Nicolas StraubeDepartment of Natural History, University Museum Bergen, University of Bergen (UiB), 5007, Bergen, Norway. Nicolas.Straube@uib.no.

Funding

Deutsche Forschungsgemeinschaft 351649567
6 · The paper itself

Abstract

Among vertebrates, sharks exhibit both large and heterogeneous genome sizes ranging from 2.86 to 17.05 pg. Aiming for a better understanding of the patterns and causalities of shark genome size evolution, we applied phylogenetic comparative methods to published genome-size estimates for 71 species representing the main phylogenetic lineages, life-histories and ecological traits. The sixfold range of genome size variation was strongly traceable throughout the phylogeny, with a major expansion preceding shark diversification during the late Paleozoic and an ancestral state (6.33 pg) close to the present-day average (6.72 pg). Subsequent deviations from this average occurred at higher rates in squalomorph than in galeomorph sharks and were unconnected to evolutionary changes in the karyotype architecture, which were dominated by descending disploidy events. Genome size was positively correlated with cell and nucleus sizes and negatively with metabolic rate. The metabolic constraints on increasing genome size also manifested at higher phenotypic scales, with large genomes associated with slow lifestyles and purely marine waters. Moreover, large genome sizes were also linked to non-placental reproductive modes, which may entail metabolically less demanding embryological developments. Contrary to ray-finned fishes, large genome size was associated neither with the taxonomic diversity of affected clades nor with low genetic diversity.

Indexed as

SharksAnimalsEvolution, MolecularFishesGenome SizePhylogenyVertebrates

Identifiers

PMID38632352
PMCPMC11024215

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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.