Multi‐omics analysis reveals the functional transcription and potential translation of enhancers
Open accessAbstract
Enhancer can transcribe RNAs, however, most of them were neglected in traditional RNA‐seq analysis workflow. Here, we developed a Pipeline for Enhancer Transcription (PET, http://fun-science.club/PET) for quantifying enhancer RNAs (eRNAs) from RNA‐seq. By applying this pipeline on lung cancer samples and cell lines, we showed that the transcribed enhancers are enriched with histone marks and transcription factor motifs (JUNB, Hand1‐Tcf3 and GATA4). By training a machine learning model, we demonstrate that enhancers can predict prognosis better than their nearby genes. Integrating the Hi‐C, ChIP‐seq and RNA‐seq data, we observe that transcribed enhancers associate with cancer hallmarks or oncogenes, among which LcsMYC‐1 (Lung cancer‐specific MYC eRNA‐1) potentially supports MYC expression. Surprisingly, a significant proportion of transcribed enhancers contain small protein‐coding open reading frames (sORFs) and can be translated into microproteins. Our study provides a computational method for eRNA quantification and deepens our understandings of the DNA, RNA and protein nature of enhancers.
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Total RNA-seq can detect more eRNAs than polyA RNA-seq because not all eRNAs are polyadenylated.
“Given that not all eRNAs are polyadenylated, total RNA-seq, compared to polyA RNA-seq, can detect more eRNAs (78, 79).”
From Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains (2025) · cites this paper as [79]
In the comparison of sequencing methods (Figure 1 discussion; page not provided), total RNA-seq detected slightly more eRNAs than polyA RNA-seq in K562 cells (3,809 versus 3,613). The paper does not establish that incomplete polyadenylation caused this difference; it concludes that there was no large difference in eRNA quantification between the methods. (LLM, conf=0.88)
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“Given that not all eRNAs are polyadenylated, total RNA-seq, compared to polyA RNA-seq, can detect more eRNAs ( 78 , 79 ).”
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Self-citationZhang, R., Chen, Z., Li, T., Feng, D., Liu, X., Wang, X., Han, H., Lei, Y., Li, X., Li, B., et al. (2025) · Briefings in Functional Genomics · doi:10.1093/bfgp/elaf007 · Cited by 2 · see citing works
Multi-Omics Data Analysis for Cancer Research: Colorectal Cancer, Liver Cancer and Lung Cancer
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Enhancer RNAs contribute to genome reprogramming driven by a GATA3 noncoding variant in leukaemia
Barbosa, T. C., Poubel, C. P., Maciel, A. L. T., Blunck, C. B., Santos, R., Boroni, M., Mansur, M. B., & Emerenciano, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-10262-0
Deciphering the eRNA landscape and revealing target aberrant pathways in prostate cancer
Yu, C., Wen, Y. H., Li, Y., Song, B., Hu, Y., Meng, Z., Yan, Z., Du, W., & Rong, H. (2026) · BMC Cancer · doi:10.1186/s12885-026-15675-2
- Authors
- Wu, Y., Yang, Y., Gu, H., Tao, B., Zhang, E., Wei, J., Wang, Z., Liu, A., Sun, R., Chen, M., Fan, Y., & Mao, R.
- Affiliations
- Nantong University (CN)
- First Affiliated Hospital of Zhengzhou University (CN)
- Department of Respiratory Medicine Nantong Sixth People's Hospital Nantong Jiangsu China
- Corresponding author
- Fan, Yihui
- Mao, Renfang
- ORCID
- Venue
- International Journal of Cancer
- Publisher
- Wiley
- Published
- 2020-07
- Volume
- 147
- Issue
- 8
- Pages
- 2210-2224
- ISSN
- 0020-7136 (ISSN-L)
- 1097-0215
- OpenAlex
- W3037502154
- Cited by
- 18
- References
- 73
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 4 · 2022: 3 · 2021: 1 · 2020: 1
- FWCI
- 0.73
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Journal of Cancer (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (30801350, 81600386, 81641164, 31770935)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- enhancer RNA, enhancer transcription, lung cancer, histone modifications, transcription factor binding motifs, prognostic factors, c-Myc, small open reading frames, microproteins, cancer hallmarks, multi-omics integration
- MeSH terms
- A549 Cells, Enhancer Elements, Genetic, HeLa Cells, Humans, RNA, Transcription Factors, Transcription, Genetic, Protein Biosynthesis, Genes, myc, Open Reading Frames, K562 Cells, Cell Line, Tumor, Hep G2 Cells, MCF-7 Cells
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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