Evidence map›Paper›PMID 42806242›Full record

ArticleMolecular ecology2026

Rates of Evolution Differ Between Cell Types Identified by Single-Cell RNAseq in Threespine Stickleback.

Maria L Rodgers, Swapna Subramanian, Lauren E Fuess, Wan He, Samuel V Scarpino, Andrea J Roth-Monzón, Daniel L Jeffries, Martine Seignon, Kathryn Milligan-McClellan, Rebecca Carrier and 2 more

Abstract read
In one paragraph

Article in Molecular ecology, 2026. 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

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

12 authors.

Maria L RodgersDepartment of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA.ORCID https://orcid.org/0000-0002-0271-1303
Swapna SubramanianDepartment of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA.
Lauren E FuessDepartment of Biology, Texas State University, San Marcos, Texas, USA.ORCID https://orcid.org/0000-0003-0197-7326
Wan HeNortheastern University, Institute of Experiential Artificial Intelligence, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0002-6004-4462
Samuel V ScarpinoNortheastern University, Institute of Experiential Artificial Intelligence, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0001-5716-2770
Andrea J Roth-MonzónDepartment of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA.ORCID https://orcid.org/0000-0003-4633-0702
Daniel L JeffriesDivision of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.ORCID https://orcid.org/0000-0003-1701-3978
Martine SeignonThe Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA.
Kathryn Milligan-McClellanDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, Connecticut, USA.ORCID https://orcid.org/0000-0002-8479-0809
Rebecca CarrierDepartment of Chemical Engineering, Northeastern University, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-3002-7098
Natalie C SteinelDepartment of Biological Sciences, University of Massachusetts Lowell, Lowell, Massachusetts, USA.ORCID https://orcid.org/0000-0002-7585-8402
Daniel I BolnickDepartment of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA.ORCID https://orcid.org/0000-0003-3148-6296

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI Paul Robson · 1985 to 2026
$61.9M
Gordon and Betty Moore Foundation GBMF9323National Institute of Allergy and Infectious Diseases 1R01AI123659-01A1NIH HHS P30 CA034196
6 · The paper itself

Abstract

Rates of evolutionary change vary by gene. While some broad gene categories are highly conserved with little divergence over time, others undergo continuous selection pressure and are highly divergent among populations or species. But such comparative evolutionary studies rely on gene ontology categories that are rarely validated in the study's focal species. An alternative is to determine species-specific gene functions using single-cell RNA sequencing (scRNAseq) that identifies cell types and the characteristic genes that each expresses. Here, we combine scRNAseq with evolutionary genomics to understand whether certain cell types exhibit faster evolutionary divergence (using their characteristic genes) than other types of cells (using intestine, head kidney, liver and gill tissues from an emerging model organism, the threespine stickleback). Merging scRNAseq with population genomic data, we show that cell types differ in the rate at which their characteristic genes evolve, as measured by allele frequency divergence among many populations (F

Indexed as

Evolution, MolecularSingle-Cell AnalysisSmegmamorphaAnimalsGene FrequencyGenetics, PopulationRNA-SeqSelection, GeneticSequence Analysis, RNASingle-Cell Gene Expression Analysisevolutionary ratesGasterosteus aculeatusimmunitysingle‐cell sequencing

Identifiers

PMID42806242
PMCPMC13619858

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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.