Biology:MicroRNA and microRNA target database

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This microRNA database and microRNA targets databases is a compilation of databases and web portals and servers used for microRNAs and their targets. MicroRNAs (miRNAs) represent an important class of small non-coding RNAs (ncRNAs) that regulate gene expression by targeting messenger RNAs.[1]

microRNA target gene databases

Name Description type Link References
StarBase starBase is designed for decoding miRNA-lncRNA, miRNA-mRNA, miRNA-circRNA, miRNA-pseudogene, miRNA-sncRNA, protein-lncRNA, protein-sncRNA, protein-mRNA and protein-pseudogene interactions and ceRNA networks from 108 CLIP-Seq (HITS-CLIP, PAR-CLIP, iCLIP, CLASH) datasets. It also provides Pan-Cancer Analysis for microRNAs, lncRNAs, circRNAs and protein-coding genes from 6000 tumor samples. database website [2][3]
StarScan StarScan is developed for scanning small RNA (miRNA, piRNA, siRNA) mediated RNA cleavage events in lncRNA, circRNA, mRNA and pseudo genes from degradome sequencing data. web-based software website [4]
Cupid Cupid is a method for simultaneous prediction of miRNA-target interactions and their mediated competing endogenous RNA (ceRNA) interactions. It is an integrative approach significantly improves on miRNA-target prediction accuracy as assessed by both mRNA and protein level measurements in breast cancer cell lines. Cupid is implemented in 3 steps: Step 1: re-evaluate candidate miRNA binding sites in 3' UTRs. Step2: interactions are predicted by integrating information about selected sites and the statistical dependency between the expression profiles of miRNA and putative targets. Step 3: Cupid assesses whether inferred targets compete for predicted miRNA regulators. * Only the source code for step 3 is provided. software (MATLAB) website [5]
TargetScan Predicts biological targets of miRNAs by searching for the presence of sites that match the seed region of each miRNA. In flies and nematodes, predictions are ranked based on the probability of their evolutionary conservation. In zebrafish, predictions are ranked based on site number, site type, and site context, which includes factors that influence target-site accessibility. In mammals, the user can choose whether the predictions should be ranked based on the probability of their conservation or on site number, type, and context. In mammals and nematodes, the user can choose to extend the predictions beyond conserved sites and consider all sites. database, webserver website [6][7][8][9][10][11]
TarBase A comprehensive database of experimentally supported animal microRNA targets database website [12]
Diana-microT DIANA-microT 3.0 is an algorithm based on several parameters calculated individually for each microRNA and it combines conserved and non-conserved microRNA recognition elements into a final prediction score. webserver webserver [13]
miRecords an integrated resource for microRNA-target interactions. database website [14]
PicTar PicTar is Combinatorial microRNA target predictions. database, webserver, predictions website [15]
PITA PITA, incorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition. webserver, predictions predictions [16]
RepTar
RNA22
miRTarBase The experimentally validated microRNA-target interactions database. As a database, miRTarBase has accumulated more than three hundred and sixty thousand miRNA-target interactions (MTIs), which are collected by manually surveying pertinent literature after NLP of the text systematically to filter research articles related to functional studies of miRNAs. Generally, the collected MTIs are validated experimentally by reporter assay, western blot, microarray and next-generation sequencing experiments. While containing the largest amount of validated MTIs, the miRTarBase provides the most updated collection by comparing with other similar, previously developed databases. database website [17][18][19][20]
miRwalk Aggregates and compare results from other miRNA-to-mRNA databases database, webserver [1] [21]
MBSTAR Multiple Instance approach for finding out true or functional microRNA binding sites. webserver, predictions predictions [22]
.

microRNA databases

Name Description type Link References
deepBase deepBase is a database for annotating and discovering small and long ncRNAs (microRNAs, siRNAs, piRNAs...) from high-throughput deep sequencing data. database website [23]
miRBase miRBase database is a searchable database of published miRNA sequences and annotation. database website [24]
microRNA.org microRNA.org is a database for Experimentally observed microRNA expression patterns and predicted microRNA targets & target downregulation scores. database website [25]
miRGen 4.0 DIANA-miRGen v4: indexing promoters and regulators for more than 1500 microRNAs database website [26]
miRNAMap miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes database website [27]
PMRD PMRD: plant microRNA database database website [28]
TargetScan TargetScan7.0 classifies microRNAs according to their level of conservation (i.e., species-specific, conserved among mammals, or broadly conserved among vertebrates) and aggregates them into families based upon their seed sequence. It also annotates conserved isomiRs using small RNA sequencing datasets.[10] database website [10]
VIRmiRNA VIRmiRNA is the first dedicated resource on experimental viral miRNA and their targets. This resource also provides inclusive knowledge about anti-viral miRNAs known to play role in antiviral immunity of host. Database website [29]

References

  1. Bartel, D. P. (2009). "MicroRNAs: Target Recognition and Regulatory Functions". Cell 136 (2): 215–233. doi:10.1016/j.cell.2009.01.002. PMID 19167326. 
  2. Yang, J. -H.; Li, J. -H.; Shao, P.; Zhou, H.; Chen, Y. -Q.; Qu, L. -H. (2010). "StarBase: A database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data". Nucleic Acids Research 39 (Database issue): D202–D209. doi:10.1093/nar/gkq1056. PMID 21037263. 
  3. Li, JH; Liu, S; Zhou, H; Qu, LH; Yang, JH (Jan 1, 2014). "starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data.". Nucleic Acids Research 42 (1): D92-7. doi:10.1093/nar/gkt1248. PMID 24297251. 
  4. Liu, S; Li, JH; Wu, J; Zhou, KR; Zhou, H; Yang, JH; Qu, LH (18 May 2015). "StarScan: a web server for scanning small RNA targets from degradome sequencing data.". Nucleic Acids Research 43 (W1): W480-6. doi:10.1093/nar/gkv524. PMID 25990732. 
  5. Chiu, Hua-Sheng; Llobet-Navas, David; Yang, Xuerui; Chung, Wei-Jen; Ambesi-Impiombato, Alberto; Iyer, Archana; Kim, Hyunjae "Ryan"; Seviour, Elena G. et al. (February 2015). "Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks". Genome Research 25 (2): 257–67. doi:10.1101/gr.178194.114. PMID 25378249. PMC 4315299. http://genome.cshlp.org/content/25/2/257. 
  6. Lewis, BP; Burge CB; Bartel DP (Jan 14, 2005). "Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets". Cell 120 (1): 15–20. doi:10.1016/j.cell.2004.12.035. PMID 15652477. 
  7. Grimson, A; Farh, KK; Johnston, WK; Garrett-Engele, P; Lim, LP; Bartel, DP (Jul 6, 2007). "MicroRNA targeting specificity in mammals: determinants beyond seed pairing.". Molecular Cell 27 (1): 91–105. doi:10.1016/j.molcel.2007.06.017. PMID 17612493. 
  8. Friedman, RC; Farh, KK; Burge, CB; Bartel, DP (January 2009). "Most mammalian mRNAs are conserved targets of microRNAs.". Genome Research 19 (1): 92–105. doi:10.1101/gr.082701.108. PMID 18955434. 
  9. Garcia, DM; Baek, D; Shin, C; Bell, GW; Grimson, A; Bartel, DP (Sep 11, 2011). "Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other microRNAs.". Nature Structural & Molecular Biology 18 (10): 1139–46. doi:10.1038/nsmb.2115. PMID 21909094. PMC 3190056. http://dspace.mit.edu/bitstream/1721.1/82943/1/Bartel_Weak%20seed-pairing.pdf. 
  10. 10.0 10.1 10.2 Agarwal, Vikram; Bell, George W.; Nam, Jin-Wu; Bartel, David P. (2015-08-12). "Predicting effective microRNA target sites in mammalian mRNAs". eLife 4: e05005. doi:10.7554/eLife.05005. ISSN 2050-084X. PMID 26267216. 
  11. Agarwal, V; Subtelny, AO; Thiru, P; Ulitsky, I; Bartel, DP (4 October 2018). "Predicting microRNA targeting efficacy in Drosophila.". Genome Biology 19 (1): 152. doi:10.1186/s13059-018-1504-3. PMID 30286781. 
  12. "TarBase: A comprehensive database of experimentally supported animal microRNA targets.". RNA 12 (2): 192–197. 2006. doi:10.1261/rna.2239606. PMID 16373484. 
  13. "Accurate microRNA target prediction correlates with protein repression levels.". BMC Bioinformatics 10: 295. 2009. doi:10.1186/1471-2105-10-295. PMID 19765283. 
  14. "miRecords: an integrated resource for microRNA-target interactions.". Nucleic Acids Res. 37 (Database issue): D105-110. 2009. doi:10.1093/nar/gkn851. PMID 18996891. 
  15. "Combinatorial microRNA target predictions.". Nat Genet 37 (5): 495–500. 2005. doi:10.1038/ng1536. PMID 15806104. 
  16. "The role of site accessibility in microRNA target recognition.". Nat Genet 39 (10): 1278–84. 2007. doi:10.1038/ng2135. PMID 17893677. 
  17. "miRTarBase: a database curates experimentally validated microRNA-target interactions.". Nucleic Acids Research 39 (Database issue): D163-9. 2011. doi:10.1093/nar/gkq1107. PMID 21071411. 
  18. "miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions.". Nucleic Acids Research 42 (Database issue): D78-85. 2014. doi:10.1093/nar/gkt1266. PMID 24304892. 
  19. "miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database.". Nucleic Acids Research 44 (Database issue): D239-47. 2016. doi:10.1093/nar/gkv1258. PMID 26590260. 
  20. "miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.". Nucleic Acids Research 46 (Database issue): D296-302. 2018. doi:10.1093/nar/gkt1266. PMID 29126174. 
  21. "miRWalk-database: prediction of possible miRNA binding sites by "walking" the genes of three genomes". Journal of Biomedical Informatics 44 (5): 839–47. 2011. doi:10.1016/j.jbi.2011.05.002. PMID 21605702. 
  22. "MBSTAR: multiple instance learning for predicting specific functional binding sites in microRNA targets.". Sci. Rep. 5: 8004. 2015. doi:10.1038/srep08004. PMID 25614300. Bibcode2015NatSR...5E8004B. 
  23. "deepBase: a database for deeply annotating and mining deep sequencing data.". Nucleic Acids Res. 38 (Database issue): D123-130. 2010. doi:10.1093/nar/gkp943. PMID 19966272. 
  24. "miRBase: tools for microRNA genomics.". Nucleic Acids Res. 36 (Database issue): D154–D158. 2008. doi:10.1093/nar/gkm952. PMID 17991681. 
  25. "The microRNA.org resource: targets and expression.". Nucleic Acids Res. 36 (Database issue): D149-153. 2007. doi:10.1093/nar/gkm995. PMID 18158296. 
  26. "DIANA-miRGen v4: indexing promoters and regulators for more than 1500 microRNAs". Nucleic Acids Res 49 (D1): D151-159. 2021. doi:10.1093/nar/gkaa1060. PMID 33245765. 
  27. "miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes.". Nucleic Acids Res. 34 (Database issue): D135-139. 2006. doi:10.1093/nar/gkj135. PMID 16381831. 
  28. "PMRD: plant microRNA database.". Nucleic Acids Res. 38 (Database issue): D806-813. 2010. doi:10.1093/nar/gkp818. PMID 19808935. 
  29. Qureshi, Abid; Thakur, Nishant; Monga, Isha; Thakur, Anamika; Kumar, Manoj (2014-01-01). "VIRmiRNA: a comprehensive resource for experimentally validated viral miRNAs and their targets". Database: The Journal of Biological Databases and Curation 2014: bau103. doi:10.1093/database/bau103. ISSN 1758-0463. PMID 25380780. 

Further reading

External links