Non-coding RNA regulatory networks
Open accessAbstract
It is well established that the vast majority of human RNA transcripts do not encode for proteins and that non-coding RNAs regulate cell physiology and shape cellular functions. A subset of them is involved in gene regulation at different levels, from epigenetic gene silencing to post-transcriptional regulation of mRNA stability. Notably, the aberrant expression of many non-coding RNAs has been associated with aggressive pathologies. Rapid advances in network biology indicates that the robustness of cellular processes is the result of specific properties of biological networks such as scale-free degree distribution and hierarchical modularity, suggesting that regulatory network analyses could provide new insights on gene regulation and dysfunction mechanisms. In this study we present an overview of public repositories where non-coding RNA-regulatory interactions are collected and annotated, we discuss unresolved questions for data integration and we recall existing resources to build and analyse networks.
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Noncoding RNAs may influence the pathophysiology of depression by regulating neuronal function, neurotransmitter release, and microglia.
“ncRNAs may influence the pathophysiology of depression by regulating neuronal function, neurotransmitter release, and microglia (Fig. 4).213,221,222”
From Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential (2023) · cites this paper as [221]
Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
Most mammalian mRNAs are conserved targets of microRNAs
Friedman, R. C., Farh, K. K.-H., Burge, C. B., & Bartel, D. P. (2009) · Genome Research · doi:10.1101/gr.082701.108 · Cited by 8,462 · see citing works
Network biology: understanding the cell's functional organization
Barabási, A.-L., & Oltvai, Z. N. (2004) · Nature Reviews Genetics · doi:10.1038/nrg1272 · Cited by 7,903 · see citing works
Circular RNAs are abundant, conserved, and associated with ALU repeats
Jeck, W. R., Sorrentino, J. A., Wang, K., Slevin, M. K., Burd, C. E., Liu, J., Marzluff, W. F., & Sharpless, N. E. (2013) · RNA · doi:10.1261/rna.035667.112 · Cited by 4,388 · see citing works
Long Noncoding RNA as Modular Scaffold of Histone Modification Complexes
Tsai, M.-C., Manor, O., Wan, Y., Mosammaparast, N., Wang, J. K., Lan, F., Shi, Y., Segal, E., & Chang, H. Y. (2010) · Science · doi:10.1126/science.1192002 · Cited by 3,290 · cited 1× · see citing works
“Several studies have shown that lncRNAs, such as Hotair, exert their function by binding to transcription regulation proteins, including histone modification enzymes and chromatin remodelling factors [19], but they can also regulate mRNAs by complementary binding (antisense lncRNAs) and binding to microRNAs (Figure 1).”
BackgroundHITS-CLIP yields genome-wide insights into brain alternative RNA processing
Licatalosi, D. D., Mele, A., Fak, J. J., Ule, J., Kayikci, M., Chi, S. W., Clark, T. A., Schweitzer, A. C., Blume, J. E., Wang, X., et al. (2008) · Nature · doi:10.1038/nature07488 · Cited by 1,352 · see citing works
CLIP Identifies Nova-Regulated RNA Networks in the Brain
Ule, J., Jensen, K. B., Ruggiu, M., Mele, A., Ule, A., & Darnell, R. B. (2003) · Science · doi:10.1126/science.1090095 · Cited by 1,120 · see citing works
MicroRNAs in the p53 network: micromanagement of tumour suppression
Hermeking, H. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3318 · Cited by 518 · see citing works
Cross-linking, ligation, and sequencing of hybrids reveals RNA–RNA interactions in yeast
Kudla, G., Granneman, S., Hahn, D., Beggs, J. D., & Tollervey, D. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017386108 · Cited by 308 · see citing works
Expanding the p53 regulatory network: LncRNAs take up the challenge
Grossi, E., Sánchez, Y., & Huarte, M. (2016) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2015.07.011 · Cited by 78 · see citing works
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Yuan, M., Yang, B., Rothschild, G., Mann, J. J., Sanford, L. D., Tang, X., Huang, C., Wang, C., & Zhang, W. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01519-z · Cited by 246 · see citing works
“213,221,222 miRNAs and the development of depression MicroRNA molecules are highly conserved small (21 – 24 nucleotides) RNA molecules.”
Background
- Authors
- Panni, S., Lovering, R. C., Porras, P., & Orchard, S.
- Affiliations
- University of Calabria (IT)
- University College London (GB)
- European Bioinformatics Institute (GB)
- Corresponding author
- Panni, Simona
- Venue
- Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 1863
- Issue
- 6
- Pages
- 194417
- ISSN
- 1874-9399 (ISSN-L)
- OpenAlex
- W2971402453
- Cited by
- 479
- References
- 11
- Citations by year
- 2026: 25 · 2025: 67 · 2024: 115 · 2023: 98 · 2022: 111 · 2021: 58 · 2020: 5
- FWCI
- 4.23
- Type
- journal article
- Language
- en
- Open access
- green
- discovery.ucl.ac.uk
- Locations
- Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Archive of Doctoral Theses and Digital Collections (University of Calabria) (submittedVersion)
- Funders
- COST
- University College London Hospitals Biomedical Research Centre
- Alzheimer's Research UK (ARUK-NAS2017A-1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- non-coding RNA, gene regulatory networks, post-transcriptional regulation, mRNA stability, epigenetic silencing, scale-free networks, network modularity, data integration, network biology
- MeSH terms
- RNA, Circular, Gene Expression Regulation, Transcription, Genetic, RNA, Untranslated, MicroRNAs, RNA, Long Noncoding
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