MicroRNA and microRNA target database

From Wikipedia, the free encyclopedia

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[edit]

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 A database of inverse miRNA target predictions, based on the RepTar algorithm that is independent of evolutionary conservation considerations and is not limited to seed pairing sites. database website [17]
RNA22 The first link (predictions) provides RNA22 predictions for all protein coding transcripts in human, mouse, roundworm, and fruit fly. It allows you to visualize the predictions within a cDNA map and also find transcripts where multiple miR's of interest target. The second web-site link (custom) first finds putative microRNA binding sites in the sequence of interest, then identifies the targeted microRNA. webserver, predictions predictions custom [18]
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 [19][20][21][22]
miRwalk Aggregates and compare results from other miRNA-to-mRNA databases database, webserver [1] [23]
MBSTAR Multiple Instance approach for finding out true or functional microRNA binding sites. webserver, predictions predictions [24]
.

microRNA databases[edit]

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 [25]
miRBase miRBase database is a searchable database of published miRNA sequences and annotation. database website [26]
microRNA.org microRNA.org is a database for Experimentally observed microRNA expression patterns and predicted microRNA targets & target downregulation scores. database website [27]
miRGen 4.0 DIANA-miRGen v4: indexing promoters and regulators for more than 1500 microRNAs database website [28]
miRNAMap miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes database website [29]
PMRD PMRD: plant microRNA database database website [30]
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 [31]

References[edit]

  1. ^ Bartel, D. P. (2009). "MicroRNAs: Target Recognition and Regulatory Functions". Cell. 136 (2): 215–233. doi:10.1016/j.cell.2009.01.002. PMC 3794896. 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. PMC 3013664. 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. PMC 3964941. 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. PMC 4489260. 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.; Luo, Zijun; Sehgal, Vasudha; Moss, Tyler; Lu, Yiling; Ram, Prahlad; Silva, José; Mills, Gordon B.; Califano, Andrea; Sumazin, Pavel (February 2015). "Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks". Genome Research. 25 (2): 257–67. doi:10.1101/gr.178194.114. PMC 4315299. PMID 25378249.
  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. PMC 3800283. 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. PMC 2612969. 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" (PDF). Nature Structural & Molecular Biology. 18 (10): 1139–46. doi:10.1038/nsmb.2115. PMC 3190056. PMID 21909094.
  10. ^ a b c 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. PMC 4532895. 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. PMC 6172730. PMID 30286781.
  12. ^ Sethupathy P, Corda B, Hatzigeorgiou AG (2006). "TarBase: A comprehensive database of experimentally supported animal microRNA targets". RNA. 12 (2): 192–197. doi:10.1261/rna.2239606. PMC 1370898. PMID 16373484.
  13. ^ Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Simossis VA, Sethupathy P, Vergoulis T, Koziris N, Sellis T, Tsanakas P, Hatzigeorgiou AG (2009). "Accurate microRNA target prediction correlates with protein repression levels". BMC Bioinformatics. 10: 295. doi:10.1186/1471-2105-10-295. PMC 2752464. PMID 19765283.
  14. ^ Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T (2009). "miRecords: an integrated resource for microRNA-target interactions". Nucleic Acids Res. 37 (Database issue): D105-110. doi:10.1093/nar/gkn851. PMC 2686554. PMID 18996891.
  15. ^ Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, Rajewsky N (2005). "Combinatorial microRNA target predictions". Nat Genet. 37 (5): 495–500. doi:10.1038/ng1536. PMID 15806104. S2CID 22672750.
  16. ^ Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E (2007). "The role of site accessibility in microRNA target recognition". Nat Genet. 39 (10): 1278–84. doi:10.1038/ng2135. PMID 17893677. S2CID 1721807.
  17. ^ Elefant, Naama; Berger Amnon; Shein Harel; Hofree Matan; Margalit Hanah; Altuvia Yael (Jan 2011). "RepTar: a database of predicted cellular targets of host and viral miRNAs". Nucleic Acids Res. 39 (Database issue). England: D188-94. doi:10.1093/nar/gkq1233. PMC 3013742. PMID 21149264.
  18. ^ Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, Lim B, Rigoutsos I (2006). "A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes" (PDF). Cell. 126 (6): 1203–17. doi:10.1016/j.cell.2006.07.031. PMID 16990141. S2CID 12749133.
  19. ^ Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, Tsai WT, Chen GZ, Lee CJ, Chiu CM, Chien CH, Wu MC, Huang CY, Tsou AP, Huang HD (2011). "miRTarBase: a database curates experimentally validated microRNA-target interactions". Nucleic Acids Research. 39 (Database issue): D163-9. doi:10.1093/nar/gkq1107. PMC 3013699. PMID 21071411.
  20. ^ Hsu SD, Tseng YT, Shrestha S, Lin YL, Khaleel A, Chou CH, Chu CF, Huang HY, Lin CM, Ho SY, Jian TY, Lin FM, Chang TH, Weng SL, Liao KW, Liao IE, Liu CC, Huang HD (2014). "miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions". Nucleic Acids Research. 42 (Database issue): D78-85. doi:10.1093/nar/gkt1266. PMC 3965058. PMID 24304892.
  21. ^ Chou CH, Chang NW, Shrestha S, Hsu SD, Lin YL, Lee WH, Yang CD, Hong HC, Wei TY, Tu SJ, Tsai TR, Ho SY, Jian TY, Wu HY, Chen PR, Lin NC, Huang HT, Yang TL, Pai CY, Tai CS, Chen WL, Huang CY, Liu CC, Weng SL, Liao KW, Hsu WL, Huang HD (2016). "miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database". Nucleic Acids Research. 44 (Database issue): D239-47. doi:10.1093/nar/gkv1258. PMC 4702890. PMID 26590260.
  22. ^ Chou CH, Shrestha S, Yang CD, Chang NW, Lin YL, Liao KW, Huang WC, Sun TH, Tu SJ, Lee WH, Chiew MY, Tai CS, Wei TY, Tsai TR, Huang HT, Wang CY, Wu HY, Ho SY, Chen PR, Chuang CH, Hsieh PJ, Wu YS, Chen WL, Li MJ, Wu YC, Huang XY, Ng FL, Buddhakosai W, Huang PC, Lan KC, Huang CY, Weng SL, Cheng YN, Liang C, Hsu WL, Huang HD (2018). "miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions". Nucleic Acids Research. 46 (Database issue): D296-302. doi:10.1093/nar/gkt1266. PMC 5753222. PMID 29126174.
  23. ^ Dweep H, Sticht C, Pandey P, Gretz N (2011). "miRWalk-database: prediction of possible miRNA binding sites by "walking" the genes of three genomes". Journal of Biomedical Informatics. 44 (5): 839–47. doi:10.1016/j.jbi.2011.05.002. PMID 21605702.
  24. ^ Bandyopadhyay S, Ghosh D, Mitra R, Zhao Z (2015). "MBSTAR: multiple instance learning for predicting specific functional binding sites in microRNA targets". Sci. Rep. 5: 8004. Bibcode:2015NatSR...5E8004B. doi:10.1038/srep08004. PMC 4648438. PMID 25614300.
  25. ^ Yang JH, Shao P, Zhou H, Chen YQ, Qu LH (2010). "deepBase: a database for deeply annotating and mining deep sequencing data". Nucleic Acids Res. 38 (Database issue): D123-130. doi:10.1093/nar/gkp943. PMC 2808990. PMID 19966272.
  26. ^ Griffiths-Jones S, Saini HK, van Dongen S, Enright AJ (2008). "miRBase: tools for microRNA genomics". Nucleic Acids Res. 36 (Database issue): D154–D158. doi:10.1093/nar/gkm952. PMC 2238936. PMID 17991681.
  27. ^ Betel D, Wilson M, Gabow A, Marks DS, Sander C (2007). "The microRNA.org resource: targets and expression". Nucleic Acids Res. 36 (Database issue): D149-153. doi:10.1093/nar/gkm995. PMC 2238905. PMID 18158296.
  28. ^ Perdikopanis N, Georgakilas GK, Grigoriadis D, Pierros V, Kavakiotis I, Alexiou P, Hatzigeorgiou A (2021). "DIANA-miRGen v4: indexing promoters and regulators for more than 1500 microRNAs". Nucleic Acids Res. 49 (D1): D151-159. doi:10.1093/nar/gkaa1060. PMC 7778932. PMID 33245765.
  29. ^ Hsu PW, Huang HD, Hsu SD, Lin LZ, Tsou AP, Tseng CP, Stadler PF, Washietl S, Hofacker IL (2006). "miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes". Nucleic Acids Res. 34 (Database issue): D135-139. doi:10.1093/nar/gkj135. PMC 1347497. PMID 16381831.
  30. ^ Zhang Z, Yu J, Li D, Zhang Z, Liu F, Zhou X, Wang T, Ling Y, Su Z (2010). "PMRD: plant microRNA database". Nucleic Acids Res. 38 (Database issue): D806-813. doi:10.1093/nar/gkp818. PMC 2808885. PMID 19808935.
  31. ^ 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. PMC 4224276. PMID 25380780.

Further reading[edit]

External links[edit]

Retrieved from "https://en.wikipedia.org/w/index.php?title=MicroRNA_and_microRNA_target_database&oldid=1188063497"