EyeLncDB: A curated database of human long non-coding RNAs related to eye diseases
Journal of Ophthalmic and Optometric Sciences,
Vol. 5 No. 1 (2021),
19 October 2022
,
Page 1-11
https://doi.org/10.22037/joos.v5i1.37854
Abstract
Background: Eye diseases (EDs) are disorders of the ocular system, causing visual damage and sightlessness. Different studies have specified a wide range of biological functions of LncRNAs; consequently, their dysfunction directs to several diseases such as EDs. Growing evidence suggests that LncRNAs might be a new class of molecules for disease diagnosis and treatment in the future. Due to the importance and the detection of a large number of LncRNAs, genome-wide analyses are essential to identify which LncRNAs are associated with different diseases. For this purpose, it is vital to collect experimentally validated LncRNAs and predict novel LncRNAs associated with various eye diseases in a systematic manner.
Material and methods: In the present study, researchers attempted to expand the current data using a powerful bioinformatics pipeline. We integrated the different resources of eye-related LncRNA information to provide a customized entry point for LncRNA-target research.
Results: As a result, 429 mRNAs related to 25 humans EDs were identified, and 151 new experimentally validated physical interactions associated with these mRNA were identified. Finally, after organizing all the identified LncRNAs, respectively, 1038 and 89 experimentally validated and predicted LncRNAs were obtained.
Conclusion: Here, we propose EyeLncDB (http://eyelncedb.databanks.behrc.ir/), a web-based platform of eye-related validated LncRNA data that contains the mentioned integrated information. EyeLncDB provides information on LncRNA-related diseases, pathways, genes, and targets with external links to the original data sources.
- Biomarker
- Web-Based Platform
- Eye Diseases (EDs)
- LncRNA
How to Cite
References
Ackland P, Resnikoff S, Bourne R. World blindness and visual impairment: Despite many successes, the problem is growing. Community Eye Health Journal. 2018;30(100):71–3.
Flaxman SR, Bourne RRA, Resnikoff S, Ackland P, Braithwaite T, Cicinelli M V., et al. Global causes of blindness and distance vision impairment 1990–2020: a systematic review and meta-analysis. Lancet Glob Health. 2017;5(12):e1221–34.
Alaei S, Sadeghi B, Najafi A, Masoudi-Nejad A. LncRNA and mRNA integration network reconstruction reveals novel key regulators in esophageal squamous-cell carcinoma. Genomics. 2019 Jan 1;111(1):76–89.
Mortezaei Z, Lanjanian H, Masoudi-Nejad A. Candidate novel long noncoding RNAs, MicroRNAs and putative drugs for Parkinson’s disease using a robust and efficient genome-wide association study. Genomics [Internet]. 2017 Jul 1 [cited 2022 Oct 23];109(3–4):158–64. Available from: https://pubmed.ncbi.nlm.nih.gov/28235564/
Wang Y, Sun X. The functions of LncRNA in the heart. Diabetes Res Clin Pract. 2020;168:108249.
Yang G, Lu X, Yuan L. LncRNA: A link between RNA and cancer. Biochim Biophys Acta Gene Regul Mech. 2014;1839(11):1097–109.
Jiang MC, Ni JJ, Cui WY, Wang BY, Zhuo W. Emerging roles of lncRNA in cancer and therapeutic opportunities. Am J Cancer Res. 2019;9(7):1354–66.
Zheng M, Zheng Y, Gao M, Ma H, Zhang X, Li Y, et al. Expression and clinical value of lncRNA MALAT1 and lncRNA ANRIL in glaucoma patients. Exp Ther Med. 2019;1329–35.
Gong W, Zhu G, Li J, Yang X. LncRNA MALAT1 promotes the apoptosis and oxidative stress of human lens epithelial cells via p38MAPK pathway in diabetic cataract. Diabetes Res Clin Pract. 2018;144:314–21.
Wapinski O, Chang HY. Long noncoding RNAs and human disease. Trends Cell Biol. 2011;21(6):354–61.
Kouhsar M, Azimzadeh Jamalkandi S, Moeini A, Masoudi-Nejad A. Detection of novel biomarkers for early detection of Non-Muscle-Invasive Bladder Cancer using Competing Endogenous RNA network analysis. Scientific Reports 2019 9:1 [Internet]. 2019 Jun 10 [cited 2021 Dec 31];9(1):1–15. Available from: https://www.nature.com/articles/s41598-019-44944-3
Motieghader H, Kouhsar M, Najafi A, Sadeghi B, Masoudi-Nejad A. mRNA-miRNA bipartite network reconstruction to predict prognostic module biomarkers in colorectal cancer stage differentiation. Mol Biosyst [Internet]. 2017 [cited 2022 Oct 23];13(10):2168–80. Available from: https://pubmed.ncbi.nlm.nih.gov/28861579/
Liu C, Bai B, Skogerbø G, Cai L, Deng W, Zhang Y, et al. NONCODE: An integrated knowledge database of non-coding RNAs. Nucleic Acids Res. 2005;33(DATABASE ISS.):112–5.
Masoudi-Sobhanzadeh Y, Omidi Y, Amanlou M, Masoudi-Nejad A. DrugR+: A comprehensive relational database for drug repurposing, combination therapy, and replacement therapy. Comput Biol Med. 2019 Jun 1;109:254–62.
Chen G, Wang Z, Wang D, Qiu C, Liu M, Chen X, et al. LncRNADisease: A database for long-non-coding RNA-associated diseases. Nucleic Acids Res. 2013;41(D1):983–6.
Ma L, Cao J, Liu L, Du Q, Li Z, Zou D, et al. Lncbook: A curated knowledgebase of human long non-coding rnas. Nucleic Acids Res. 2019;47(D1):D128–34.
Zhang Y, Xue Z, Guo F, Yu F, Xu L, Chen H. Nc2Eye: A Curated ncRNAomics Knowledgebase for Bridging Basic and Clinical Research in Eye Diseases. Front Cell Dev Biol. 2020;8(February):1–6.
Ahmadi H, Ahmadi A, Azimzadeh-Jamalkandi S, Shoorehdeli MA, Salehzadeh-Yazdi A, Bidkhori G, et al. HomoTarget: A new algorithm for prediction of microRNA targets in Homo sapiens. Genomics. 2013 Feb 1;101(2):94–100.
Hooshmand SA, Zarei Ghobadi M, Hooshmand SE, Azimzadeh Jamalkandi S, Alavi SM, Masoudi-Nejad A. A multimodal deep learning-based drug repurposing approach for treatment of COVID-19. Mol Divers [Internet]. 2021 Aug 1 [cited 2022 Oct 23];25(3):1717–30. Available from: https://pubmed.ncbi.nlm.nih.gov/32997257/
Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: New perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017;45(D1):D353–61.
Masoudi-Nejad A, Goto S, Endo TR, Kanehisa M. KEGG bioinformatics resource for plant genomics research. Methods Mol Biol [Internet]. 2007 Nov 1 [cited 2022 Oct 23];406:437–58. Available from: https://pubmed.ncbi.nlm.nih.gov/18287706/
Masoudi-Nejad A, Goto S, Jauregui R, Ito M, Kawashima S, Moriya Y, et al. EGENES: Transcriptome-Based Plant Database of Genes with Metabolic Pathway Information and Expressed Sequence Tag Indices in KEGG. Plant Physiol [Internet]. 2007 Jun 7 [cited 2022 Oct 23];144(2):857–66. Available from: https://academic.oup.com/plphys/article/144/2/857/6106967
Piñero J, Queralt-Rosinach N, Bravo À, Deu-Pons J, Bauer-Mehren A, Baron M, et al. DisGeNET: A discovery platform for the dynamical exploration of human diseases and their genes. Database. 2015;2015:1–17.
Hamosh A, Scott AF, Amberger J, Valle D, McKusick VA. Online Mendelian Inheritance in Man (OMIM). Hum Mutat. 2000;15(1):57–61.
Croft D, O’Kelly G, Wu G, Haw R, Gillespie M, Matthews L, et al. Reactome: A database of reactions, pathways and biological processes. Nucleic Acids Res. 2011;39(SUPPL. 1):691–7.
Bateman A, Martin MJ, O’Donovan C, Magrane M, Apweiler R, Alpi E, et al. UniProt: A hub for protein information. Nucleic Acids Res. 2015;43(D1):D204–12.
Wu T, Wang J, Liu C, Zhang Y, Shi B, Zhu X, et al. NPInter: the noncoding RNAs and protein related biomacromolecules interaction database. Nucleic Acids Res. 2006;34(Database issue):150–2.
Ghasemi M, Seidkhani H, Tamimi F, Rahgozar M, Masoudi-Nejad A. Centrality Measures in Biological Networks. undefined. 2014 Aug 27;9(4):426–41.
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