Evidence map›Paper›PMID 41359035›Full record

ArticleNucleic acids research2026

SEdb 3.0: a comprehensive super-enhancer database across multiple species.

Shuang Song, Liyuan Liu, Chenchen Feng, Liyuan Xie, Guorui Zhang, Yuexin Zhang, Yichen Gao, Mingxue Yin, Xiuyun Tang, Wenya Pei and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

13 authors.

Shuang SongThe First Affiliated Hospital and Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Liyuan LiuThe First Affiliated Hospital and Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Chenchen FengSchool of Computer, University of South China, Hengyang, Hunan 421001, China.
Liyuan XieSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing100029, China.
Guorui ZhangThe First Affiliated Hospital and Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Yuexin ZhangThe First Affiliated Hospital and Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Yichen GaoSchool of Computer, University of South China, Hengyang, Hunan 421001, China.
Mingxue YinSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing100029, China.ORCID 0009-0001-7724-1019
Xiuyun TangInsititute of Biochemistry and Molecular Biology, Hengyang Medical College, University of South China, Hengyang, Hunan 421001, China.
Wenya PeiInsititute of Biochemistry and Molecular Biology, Hengyang Medical College, University of South China, Hengyang, Hunan 421001, China.
Chao SongThe First Affiliated Hospital and Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Runping LiuSchool of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing100029, China.
Chunquan LiThe First Affiliated Hospital and Hunan Provincial Key Laboratory of Multi-omics and Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.ORCID 0000-0002-4700-5496

Funding

Clinical Research 4310 Program of the University of South China 20224310NHYCG05National Natural Science Foundation of China 62171166National Natural Science Foundation of China 62302206National Natural Science Foundation of China 62572223Natural Science Foundation of Hunan Province 2023JJ30536Natural Science Foundation of Hunan Province 2023JJ40594Natural Science Foundation of Hunan Province 2025JJ50105Noncommunicable Chronic Diseases-National Science and Technology 2024ZD0530800Scientific research Project of the Education Department of Hunan Province 24B0417The Innovation Platform and Talent Program 2023TP1047The science and technology innovation Program of Hunan Province 2024RC1062The science and technology innovation Program of Hunan Province 2024RC3212
6 · The paper itself

Abstract

Super-enhancers (SEs) are key DNA cis-regulatory elements that play a central role in regulating tissue/cell-specific gene expression, thereby maintaining cellular identity and function. SEdb 3.0 (http://www.licpathway.net/sedb) provides an extensively updated resource of SEs and their regulatory annotations across multiple species. The current version of SEdb now curates 3 478 186 SEs from 5387 H3K27ac ChIP-seq samples across four species. Compared to SEdb 2.0, it has achieved a two-fold expansion in human and mouse SE entries while newly incorporating Arabidopsis thaliana and maize data, significantly enhancing both the database's scale and its utility in plant research. Furthermore, abundant (epi)genomic features have been added, such as enhancer RNAs (eRNAs), binding sites of transcription co-factors (TcoFs), and chromatin regulators (CRs). The inclusion of eRNAs provides insights into SE transcriptional activity. Mapping TcoF binding sites highlights their roles in mediating enhancer-promoter looping and stabilizing transcriptional complexes at SEs. The integration of CRs uncovers how SEs are associated with histone modifications and chromatin remodeling, which are critical for maintaining an open chromatin state. Collectively, these annotations not only reveal the diverse mechanisms by which SEs exert regulatory functions but also enable more detailed investigations into their biological significance and functional roles. Meanwhile, existing annotations have been substantially expanded, such as an approximately five-fold increase in transcription factor (TF) ChIP-seq data, a 2.3-fold rise in TF motifs, and a roughly 1.8-fold growth in SE-associated eQTL-gene regulatory pairs. SEdb 3.0 introduces two advanced inference strategies for associating genes with SEs. Moreover, two newly developed analysis tools are provided in SEdb 3.0, including SE blast alignment analysis and SE-driven core TF enrichment analysis. In summary, SEdb 3.0 represents a significant upgrade over SEdb 2.0, with a substantial expansion in SE coverage across multiple species, alongside enhanced functional annotations encompassing SE upstream/downstream regulatory information, thereby offering a more comprehensive and user-friendly platform for exploring the biological roles of SEs.

Indexed as

Databases, GeneticEnhancer Elements, GeneticAnimalsArabidopsisBinding SitesChromatinGene Expression RegulationHistonesHumansMiceMolecular Sequence AnnotationSoftwareTranscription FactorsZea maysChromatinHistonesTranscription Factors

Identifiers

PMID41359035
PMCPMC12807715

What OpenQuestion holds

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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.