Evidence map›Paper›PMID 40038570›Full record

ArticleBMC biology2025

The interplay between epigenomic and transcriptomic variation during ecotype divergence in stickleback.

Man Luo, Junjie Zhao, Juha Merilä, Rowan D H Barrett, Baocheng Guo, Juntao Hu

Abstract read
In one paragraph

Article in BMC biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Man Luo *Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
Junjie Zhao *Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China.
Juha MeriläEcological Genetics Research Unit, Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.
Rowan D H BarrettDepartment of Biology, McGill University, Quebec, Canada.
Baocheng GuoKey Laboratory of Animal Biodiversity Conservation and Integrated Pest Management & Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, China. guobaocheng@ioz.ac.cn.
Juntao HuMinistry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Center for Evolutionary Biology, School of Life Sciences, Fudan University, Shanghai, China. juntao_hu@fudan.edu.cn.

Funding

Academy of Finland 129662, 134728 and 218343National Natural Science Foundation of China 32161160321, 31672273 and 32022009National Natural Science Foundation of China 32170417Shanghai Sailing Program 21YF1403200
6 · The paper itself

Abstract

backgroundPopulations colonizing contrasting environments are likely to undergo adaptive divergence and evolve ecotypes with locally adapted phenotypes. While diverse molecular mechanisms underlying ecotype divergence have been identified, less is known about their interplay and degree of divergence.

resultsHere we integrated epigenomic and transcriptomic data to explore the interactions among gene expression, alternative splicing, DNA methylation, and microRNA expression to gauge the extent to which patterns of divergence at the four molecular levels are aligned in a case of postglacial divergence between marine and freshwater ecotypes of nine-spined sticklebacks (Pungitius pungitius). Despite significant genome-wide associations between epigenomic and transcriptomic variation, we found largely non-parallel patterns of ecotype divergence across epigenomic and transcriptomic levels, with predominantly nonoverlapping (ranging from 43.40 to 87.98%) sets of differentially expressed, spliced and methylated genes, and candidate genes targeted by differentially expressed miRNA between the ecotypes. Furthermore, we found significant variation in the extent of ecotype divergence across different molecular mechanisms, with differential methylation and differential splicing showing the highest and lowest extent of divergence between ecotypes, respectively. Finally, we found a significant enrichment of genes associated with ecotype divergence in differential methylation.

conclusionsOur results suggest a nuanced relationship between epigenomic and transcriptomic processes, with alignment at the genome-wide level masking relatively independent effects of different molecular mechanisms on ecotype divergence at the gene level.

Indexed as

EcotypeEpigenesis, GeneticGenetic VariationSmegmamorphaTranscriptomeAlternative SplicingAnimalsDNA MethylationEpigenomicsMicroRNAsMicroRNAsAdaptive divergenceAlternative splicingDNA methylationGene expressionMicroRNAPungitius pungitius

Identifiers

PMID40038570
PMCPMC11881503

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.