Skip to main content

Advertisement

SpringerLink
Log in

miRNAs target databases: developmental methods and target identification techniques with functional annotations

  • Review
  • Published:
Cellular and Molecular Life Sciences Aims and scope Submit manuscript

Abstract

Purpose

microRNA (miRNA) regulates diverse biological mechanisms and metabolisms in plants and animals. Thus, the discoveries of miRNA has revolutionized the life sciences and medical research.The miRNA represses and cleaves the targeted mRNA by binding perfect or near perfect or imperfect complementary base pairs by RNA-induced silencing complex (RISC) formation during biogenesis process. One miRNA interacts with one or more mRNA genes and vice versa, hence takes part in causing various diseases. In this paper, the different microRNA target databases and their functional annotations developed by various researchers have been reviewed. The concurrent research review aims at comprehending the significance of miRNA and presenting the existing status of annotated miRNA target resources built by researchers henceforth discovering the knowledge for diagnosis and prognosis.

Methods and results

This review discusses the applications and developmental methodologies for constructing target database as well as the utility of user interface design. An integrated architecture is drawn and a graphically comparative study of present status of miRNA targets in diverse diseases and various biological processes is performed. These databases comprise of information such as miRNA target-associated disease, transcription factor binding sites (TFBSs) in miRNA genomic locations, polymorphism in miRNA target, A-to-I edited target, Gene Ontology (GO), genome annotations, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, target expression analysis, TF–miRNA and miRNA–mRNA interaction networks, drugs–targets interactions, etc.

Conclusion

miRNA target databases contain diverse experimentally and computationally predicted target through various algorithms. The comparison of various miRNA target database has been performed on various parameters. The computationally predicted target databases suffer from false positive information as there is no common theory for prediction of miRNA targets. The review conclusion emphasizes the need of more intelligent computational improvement for the miRNA target identification, their functional annotations and datasbase development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 16:281–297. doi:10.1016/S0092-8674(04)00045-5

    Article  Google Scholar 

  2. Almeida MI, Reis RM, Calin GA (2011) MicroRNA history: discovery, recent applications and next frontiers. Mutat Res 717:1–8. doi:10.1016/j.mrfmmm.2011.03.009

    Article  CAS  PubMed  Google Scholar 

  3. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854. Doi:10.1016/0092-8674(93)90529-Y

    Article  CAS  PubMed  Google Scholar 

  4. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE et al (2000) The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditiselegans. Nature 403:901–906. doi:10.1038/35002607

    Article  CAS  PubMed  Google Scholar 

  5. Brennecke J, Hipfner DR, Stark A, Russell RB, Cohen SM (2003) Bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila. Cell 113:25–36. doi:10.1016/S0092-8674(03)00231-9

    Article  CAS  PubMed  Google Scholar 

  6. Ambros V (2004) The functions of animal micrornas. Nature 431(350):355. doi:10.1038/nature02871

    Google Scholar 

  7. Du T, Zamore PD (2007) Beginning to understand microrna function. Cell Res 17:661–663. doi:10.1038/cr.2007.67

    Article  CAS  PubMed  Google Scholar 

  8. Bushati N, Cohen SM (2007) Microrna functions. Annu Rev Cell Dev Bi 23:175–205.doi:10.1146/annurev.cellbio.23.090506.123406

    Article  CAS  Google Scholar 

  9. Khraiwesh B, Zhu JK, Zhu J (2012) Role of miRNAs and siRNAs in biotic and abiotic stress responses of plants. Biochimica Biophysica Acta 1819:137–148. doi:10.1016/j.bbagrm.2011.05.001.

    Article  CAS  Google Scholar 

  10. Kloosterman WP, Plasterk RH (2006) The diverse functions of MicroRNAs in animal development and disease. Dev Cell 11:441–450. doi:10.1016/j.devcel.2006.09.009

    Article  CAS  PubMed  Google Scholar 

  11. Jacobsen A, Silber J, Harinath G, Huse JT, Schultz N, Sander C (2013) Analysis of microRNA-target interactions across diverse cancer types. Nat Struct Mol Biol 20:1325–1332. doi:10.1038/nsmb.2678

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Eckardt NA (2012) A microRNA cascade in plant defense. Plant Cell 24:840–840. doi:10.1105/tpc.112.240311

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Singh Y, Kaul V, Mehra A, Chatterjee S, Tousif S, Dwivedi VP et al (2013) Mycobacterium tuberculosis controls microRNA-99b (miR-99b) expression in infected murine dendritic cells to modulate host immunity. J Biol Chem 288(7):5056–5061. doi:10.1074/jbc.C112.439778

    Article  CAS  PubMed  Google Scholar 

  14. Jansson MD, Lund AH (2012) MicroRNA and cancer. Mol Oncol 6:590–610. doi:10.1016/j.molonc.2012.09.006

    Article  CAS  PubMed  Google Scholar 

  15. Kumar P, Dezso Z, MacKenzie C, Oestreicher J, Agoulnik S et al (2013) Circulating miRNA Biomarkers for Alzheimer’s disease. PLoS ONE 8:e69807. doi:10.1371/journal.pone.0069807

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bej S, Basak J (2014) MicroRNAs: the potential biomarkers in plant stress response. Am J Plant Sci 5:748–759. doi:10.4236/ajps.2014.55089.

    Article  CAS  Google Scholar 

  17. Nelson PT, Wang WX, Bernard WR (2008) MicroRNAs (miRNAs) in neurodegenerative diseases. Brain Pathol 18:130–138. doi:10.1111/j.1750-3639.2007.00120.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Qu Z, Li W, Fu B (2014) MicroRNAs in Autoimmune Diseases. BioMed Res Int 2014:8. doi:10.1155/2014/527895

    Google Scholar 

  19. Shantikumar S, Caporali A, Emanueli C (2011) Role of miRNA in diabetes and its cardiovascular complications. Cardiovasc Res 93:583–593 doi:10.1093/cvr/cvr300

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Mao Y, Mohan R, Zhang S, Tang X (2013) MicroRNAs as pharmacological targets in diabetes. Pharmaco Res 75:37–47. doi:10.1016/j.phrs.2013.06.005

    Article  CAS  Google Scholar 

  21. Pauley KM, Cha S, Chan EK (2009) MicroRNA in autoimmunity and autoimmune diseases. J Autoimmun 32:189–194. doi:10.1016/j.jaut.2009.02.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Farazi TA, Hoell JI, Morozov et al (2013) MicroRNAs in human cancer. Adv Exp Med Biol 774:1–20. doi:10.1007/978-94-007-5590-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Duskova K, Nagilla P, Le H, Iyer P, Thalamuthu A et al (2013) MicroRNA regulation and its effects on cellular transcriptome in human immunodeficiency virus-1 (HIV-1) infected individuals with distinct viral load and CD4 cell counts. BMC Infect Dis 13:250. doi:10.1186/1471-2334-13-250

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lindsay MA (2003) Target discovery. Nat Rev Drug Discov 2:831–838. doi:10.1038/nrd1202

    Article  CAS  PubMed  Google Scholar 

  25. Yang Y, Adelstein SJ, Kassis AI (2009) Target discovery from data mining approaches. Drug Discov Today 14:147–154. doi:10.1016/j.drudis.2008.12.005

    Article  PubMed  Google Scholar 

  26. Ji X, Takahashi R, Hiura Y, Hirokawa G, Fukushima Y, Iwai N (2009) Plasma miR-208 as biomarker of myocardial injury. Clin Chem 55:1944–1949. doi:10.1373/clinchem.2009.125310

    Article  CAS  PubMed  Google Scholar 

  27. Hulanicka M, Garncarz M, Parzeniecka-Jaworska M, Jank M (2014) Plasma miRNAs as potential biomarkers of chronic degenerative valvular disease in Dachshunds. BMC Vet Res 10:205–208. doi:10.1186/s12917-014-0205-8

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Spadaro PA, Bredy TW (2012) Emerging role of non-coding RNA in neural plasticity cognitive function and neuropsychiatric disorders. Front Genet 3:132. doi:10.3389/fgene.2012.00132

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Finnegan EF, Pasquinelli AE (2013) MicroRNA biogenesis: regulating the regulators. Crit Rev Biochem Mol Biol 48:51–68. doi:10.3109/10409238.2012.738643

    Article  CAS  PubMed  Google Scholar 

  30. Ekimler S. Sahin K (2014) Computational methods for MicroRNA target prediction. Genes 5: 671–68. doi:10.3390/genes5030671.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Dimitrov R (2014) microRNA gene finding and target prediction—basic principles and challenges. MOJ Proteomics Bioinform 1:00024. doi:10.15406/mojpb.2014.01.00024.

    Article  Google Scholar 

  32. Dónal C, Schaefer A (2012) General principals of miRNA biogenesis and regulation in the brain. Neuropsychopharmacol 38: 39–54. doi:10.1038/npp.2012.87.

    Google Scholar 

  33. Voinnet O (2009) Origin, biogenesis and activity of plant microRNAs. Cell 136:669–687. doi:10.1016/j.cell.2009.01.046

    Article  CAS  PubMed  Google Scholar 

  34. Martinez-Sanchez A, Murphy CL (2013) MicroRNA target identification—experimental approaches. Biology 2:189–205. doi:10.3390/biology2010189.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Thomson DW, Bracken CP, Goodall GJ (2014) Experimental strategies for microRNA target identification. Nucleic Acids Res 39:6845–6853. doi:10.1093/nar/gkr330

    Article  CAS  Google Scholar 

  36. Ahmadi H, Ahmadi A, Azimzadeh-Jamalkandi S, Shoorehdeli MA, Salehzadeh-Yazdi A et al (2013) Homotarget: a new algorithm for prediction of microRNA targets in Homo sapiens. Genomics 101:94–100. doi:10.1016/j.ygeno.2012.11.005

    Article  CAS  PubMed  Google Scholar 

  37. Reyes-Herrera PH, Ficarra E (2012) One Decade of development and evolution of MicroRNA target prediction algorithms. Genom Proteom Bioinform 10:254–263. Doi:10.1016/j.gpb.2012.10.001

    Article  Google Scholar 

  38. Srivastava PK, Moturu TR, Pandey P, Baldwin IT, Pandey SP (2014) A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction. BMC Genom 15 :348.doi:10.1186/1471-2164-15-348

  39. Peterson SM, Thompson JA, Ufkin ML, Sathyanarayana P et al (2014) Common features of microRNA target prediction tools. Front Genet 5:13 doi:10.3389/fgene.2014.00023

    Article  CAS  Google Scholar 

  40. Dai X, Zhao PX (2011) psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res 39:W155–W159. doi:10.1093/nar/gkr319

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wu HJ, Ma YK, Chen T, Wang M, Wang XJ (2012) PsRobot: a web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40:W22–W28. doi:10.1093/nar/gks554

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bonnet E, He Y, Billiau K, Van de Peer Y(2010) TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics 26:1566–1568. doi:10.1093/bioinformatics/btq233

  43. Bonnet E, Wuyts J, Rouzé P, Van de Peer Y (2004) Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativaidentifies important target genes. PNAS 101:11511–11516. doi:10.1073/pnas.0404025101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhang Y (2005) miRU: an automated plant miRNA target prediction server. Nucleic Acids Res 33:W701–W704. doi:10.1093/nar/gki383

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM et al (2007) High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PLoS One 2:e219. doi:10.1371/journal.pone.0000219

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Allen E, Xie Z, Gustafson AM, Carrington JC (2005) microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell 121:207–221. doi:10.1016/j.cell.2005.04.004

    Article  CAS  PubMed  Google Scholar 

  47. Xie F, Zhang B (2010) Target-align: a tool for plant microRNA target identification. Bioinformatics 26(23):3002–3003. doi:10.1093/bioinformatics/btq568

    Article  CAS  PubMed  Google Scholar 

  48. Sun YH, Lu S, Shi R, Chiang VL (2011) Computational Prediction of Plant miRNATargets. Methods Mol Biol 744:175–186. doi:10.1007/978-1-61779-123-9_12

    Article  CAS  PubMed  Google Scholar 

  49. Jha A, Shankar R (2011) Employing machine learning for reliable miRNA target identification in plants. BMC Genomics 12:636. doi:10.1186/1471-2164-12-636

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are MicroRNA targets. Cell 120:15–20. doi:10.1016/j.cell.2004.12.035

    Article  CAS  PubMed  Google Scholar 

  51. Friedman RC, Farh KK, Burge CB, David P Bartel (2009) Most mammalian mRNAs are conserved targets of MicroRNAs. Genome Res 19:92–105. doi:10.1101/gr.082701.108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP (2007) MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell 27:91–105. doi:10.1016/j.molcel.2007.06.017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. García DM, Baek D, Shin C, Bell GW, Grimson A, Bartel DP (2011) Weak seed-pairing stability and high target-site abundance decrease the proficiency of lsy-6 and other miRNAs. Nat Struct Mol Biol 18:1139–1146. doi:10.1038/nsmb.2115

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Krüger, Rehmsmeier M (2006) RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 34:W451–W454. doi:10.1093/nar/gkl243

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS (2003) MicroRNA targets in drosophila. Genome Biol 5:R1. doi:10.1186/gb-2003-5-1-r1

    Article  PubMed  PubMed Central  Google Scholar 

  56. Johnes-Rahoades MW, Bartel DP (2004) Computational identification of plant microRNAsand their targets, inducing a stress-induced miRNA. Mol Cell 14:787–799. doi:10.1016/j.molcel.2004.05.027

    Article  Google Scholar 

  57. Adai A, Cameron J, Sizolwenkosi M, Sarah A, Varun M, Vicki V, Venkatesan S (2005) Computational prediction of miRNAs in Arabidopsis thaliana. Genome Res 15:78–91. doi:10.1101/gr.2908205

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Grün D, Wang YL, Langenberger D, Gunsalus KC, Rajewsky N (2005) microRNA target predictions across seven drosophila species and comparison to mammalian targets. PLoS Comput Biol 1:e13. doi:10.1371/journal.pcbi.0010013

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Anders G, Mackowiak SD, Jens M, Maaskola J, Kuntzagk A, Rajewsky N et al (2012) doRiNA: a database of RNA interactions in post-transcriptional regulation. Nucleic Acids Res 40:D180–D186. doi:10.1093/nar/gkr1007

    Article  CAS  PubMed  Google Scholar 

  60. Krek A, Grun D, Poy M, Wolf R, Rosenberg L et al (2005) Combinatorial microRNA target predictions. Nat Genet 37:495–500. doi:10.1038/ng1536

    Article  CAS  PubMed  Google Scholar 

  61. Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL et al (2006) A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell 126:1203–1217. doi:10.1016/j.cell.2006.07.031

    Article  CAS  PubMed  Google Scholar 

  62. Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E (2007) The role of site accessibility in microRNA target recognition. Nat Genet 39:1278–1284. doi:10.1038/ng2135

    Article  CAS  PubMed  Google Scholar 

  63. Gaidatzis D, Van Nimwegen E, Hausser J, Zavolan M (2007) Inference of miRNA targets using evolutionary conservation and pathway analysis. BMC Bioinformatics 8:69. doi:10.1186/1471-2105-8-69

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Maragkakis M, Reczko M, Simossis VA, Alexiou P P, Papadopoulos GL et al (2009) DIANA-microT web server: elucidating microRNA functions through target prediction. Nucleic Acids Res 37:W273–W276. doi:10.1093/nar/gkp292

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. RusINov V, Baev V, Minkov IN, Tabler M (2005) MicroInspector: a web tool for detection of miRNA binding sites in an RNA sequence. Nucleic Acids Res 33:W696–W700. doi:10.1093/nar/gki364

    Article  CAS  Google Scholar 

  66. Stark A, Brennecke J, Bushati N, Russell RB, Cohen SM (2005) Animal MicroRNAs confer robustness to gene expression and have a significant impact on 3′UTR evolution. Cell 123:1133–1146. doi:10.1016/j.cell.2005.11.023

    Article  CAS  PubMed  Google Scholar 

  67. Hammell M, Dang L, Zhang L, Lee A, Carmack CS et al (2008) mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein–enriched transcripts. Nat methods 5:813–819. doi:10.1038/nmeth.1247

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Hsu JB, Chiu CM, Hsu SD, Huang WY, Chien CH, Lee TY, Huang HD (2011) miRTar: an integrated system for identifying miRNA-target interactions in human. BMC Bioinform 12:300. doi:10.1186/1471-2105-12-300

    Article  CAS  Google Scholar 

  69. Saetrom O, Snove O Jr, Saetrom P (2005) Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms. RNA 11:995–1003. doi:10.1261/rna.7290705

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Huang JC, Babak T, Corson TW, Chua G, Khan S et al (2007) Using expression profiling data to identify human microRNA, targets. Nat Methods 4:1045–1049. doi:10.1038/nmeth1130

    Article  CAS  PubMed  Google Scholar 

  71. Kim SK, Nam JW, Rhee JK, Lee WJ, Zhang BT (2006) miTarget: microRNA target gene prediction using a support vector machine. BMC Bioinform 7:411. doi:10.1186/1471-2105-7-411

    Article  CAS  Google Scholar 

  72. Sturm M, Hackenberg M, Langenberger D, Frishman D (2010) TargetSpy: a supervised machine learning approach for microRNA target prediction. BMC Bioinform 11:292. doi:10.1186/1471-2105-11-292

    Article  CAS  Google Scholar 

  73. Bandyopadhyay S, Mitra R (2009) TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples. Bioinformatics 25:2625–2631. doi:10.1093/bioinformatics/btp503

    Article  CAS  PubMed  Google Scholar 

  74. Yang Y, Wang YP, Li KB (2008) MiRTif: a support vector machine-based microRNA target interaction filter. BMC Bioinform 9:S4. doi:10.1186/1471-2105-9-S12-S4

    Article  CAS  Google Scholar 

  75. Yan X, Chao T, Tu K, Zhang Y, Xie Lu, Gong Y, Yuan J, Qiang B, Peng X (2007) Improving the prediction of human microRNA target genes by using ensemble algorithm. FEBS Lett 581:1587–1593. doi:10.1016/j.febslet.2007.03.022

    Article  CAS  PubMed  Google Scholar 

  76. Wang X, El Naqa IM (2008) Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics 24:325–332. doi:10.1093/bioinformatics/btm595

    Article  PubMed  CAS  Google Scholar 

  77. Chandra V, devi GR, Nair AS, Pillai SS, Pillai RM (2010) MTar: a computational microRNA target prediction architecture for human transcriptome. BMC Bioinform 11:S2. doi:10.1186/1471-2105-11-S1-S2

    Article  CAS  Google Scholar 

  78. Betel D, Koppal A, Agius P, Sander C, Leslie C (2010) Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol 11:R90. doi:10.1186/gb-2010-11-8-r90

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  79. Friedman Y, Karsenty S, Linial M (2014) miRror-Suite: decoding coordinated regulation by microRNAs. Database(Oxford): bau043 doi:10.1093/database/bau043

  80. Friedman I, Naamati G, Linial M (2010) MiRror: a combinatorial analysis web tool for ensembles of microRNAs and their targets. Bioinformatics 26(15):1920–1921. doi:10.1093/bioinformatics/btq298

    Article  CAS  PubMed  Google Scholar 

  81. Reyes-Herrera PH, Ficarra E, Acquaviva A, Macii E (2011) miREE: miRNA recognition elements ensemble. BMC Bioinform 12:454. doi:10.1186/1471-2105-12-454

    Article  Google Scholar 

  82. Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G et al (2012) Tarbase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 40:D222–D229. doi:10.1093/nar/gkr1161

    Article  CAS  PubMed  Google Scholar 

  83. Papadopoulos GL, Reczko M, Simossis VA, Sethupathy P, Hatzigeorgiou AG (2009) The database of experimentally supported targets: a functional update of TarBase. Nucleic Acids Res 37:D155–D158. doi:10.1093/nar/gkn809

    Article  CAS  PubMed  Google Scholar 

  84. Sethupathy P, Corda B, Hatzigeorgiou AG (2006) TarBase: a comprehensive database of experimentally supported animal microRNA targets. RNA 12:192–197. doi:10.1261/rna.2239606

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. LeeYJ, Kim V, Muth DC, Witwer KW (2015) Validated MicroRNA target databases: an evaluation. Drug Dev Res 76: 389–396. doi:10.1002/ddr.21278.

    Article  CAS  Google Scholar 

  86. 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:D105–D110. doi:10.1093/nar/gkn851

    Article  CAS  PubMed  Google Scholar 

  87. Nam S, Kim B, Shin S, Lee S (2008) miRGator: an integrated system for functional annotation of microRNAs. Nucleic Acids Res 36(Database issue):D159–D164. doi:10.1093/nar/gkm829

    CAS  PubMed  Google Scholar 

  88. Cho S, Jun Y, Lee S, Choi HS, Jung S, Jang Y, Park C, Kim S, Lee S, Kim W (2011) miRGator v2.0: an integrated system for functional investigation of microRNAs. Nucleic Acids Res 39(Database issue):D158–D162. doi:10.1093/nar/gkq1094

    Article  CAS  PubMed  Google Scholar 

  89. Cho S, Jang I, Jun Y, Yoon S et al (2013) miRGator v3.0: a microRNA portal for deep sequencing, expression profiling, and mRNA targeting. Nucleic Acids Res 41(Database issue):D252–D257. doi:10.1093/nar/gks1168

    Article  CAS  PubMed  Google Scholar 

  90. Dweep H, Sticht C, Pandey P, Gretz N (2011) miRWalk—database: prediction of possible miRNA binding sites by “walking” the genes of three genomes. J Biomed Inform 44:839–847. doi:10.1016/j.jbi.2011.05.002

    Article  CAS  PubMed  Google Scholar 

  91. Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, Tsai WT et al (2011) miRTarBase: a database curates experimentally validated microRNA—target interactions. Nucleic Acids Res 39:D163–D169. doi:10.1093/nar/gkq1107

    Article  CAS  PubMed  Google Scholar 

  92. Hsu SD, Tseng YT, Shrestha S, Lin YL, Khaleel A, Chou CH, Chu CF et al (2014) miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions. Nucleic Acids Res 42:D78–D85. doi:10.1093/nar/gkt1266

    Article  CAS  PubMed  Google Scholar 

  93. Naeem H, Kuffner R, Csaba G, Zimmer R (2010) miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature. BMC Bioinformatics 11:135. doi:10.1186/1471-2105-11-135

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  94. Yang JH, Li, JH Shao P, Zhou H, Chen YQ, Qu LH (2011) starBase: a database for exploring microRNA–mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data. Nucleic Acids Res 39:D202–D209. doi:10.1093/nar/gkq1056

    Article  CAS  PubMed  Google Scholar 

  95. Li JH, Liu S, Zhou H, Qu LH, Yang JH (2014) starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res 42(D1):D92–D97. doi:10.1093/nar/gkt1248

    Article  CAS  PubMed  Google Scholar 

  96. Sun X, Dong B, Yin L, Zhang R, Du W, Liu D et al (2013) PMTED: a plant microRNA target expression database. BMC Bioinform 14:174. doi:10.1093/nar/gkq1107

    Article  CAS  Google Scholar 

  97. Pio G, Ceci M, Malerba D, D Elia D (2015) ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks. BMC Bioinform 16:S7. doi:10.1186/1471-2105-16-S9-S7

    Article  Google Scholar 

  98. Pio G, Ceci M, D’Elia D, Malerba D (2014) Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach. BMC Bioinform 15:S4. doi:10.1186/1471-2105-15-S1-S4

    Article  CAS  Google Scholar 

  99. Pio G, Ceci M, D’Elia D, Loglisci C, Malerba D (2013) A novel biclustering algorithm for the discovery of meaningful biological correlations between miRNAs and mRNAs. BMC Bioinform 14:S8. doi:10.1186/1471-2105-14-S7-S8

    Article  Google Scholar 

  100. Pio G, Ceci M, D’Elia D, Loglisci C, Malerba D (2013) HOCCLUS2: a biclustering algorithm for the discovery of miRNA:mRNA regulatory modules. Italian Symposium on Advanced Database Systems (SEBD)

  101. Pio G, Ceci M, D’Elia D, Loglisci C, Malerba D 2012 Hierarchical and Overlapping Co-Clustering of mRNA:miRNA. Interactions European Conference on Artificial Intelligence (ECAI)

  102. Pio G, Ceci M, D’Elia D, Malerba D (2014) Network reconstruction for the identification of miRNA:mRNA interaction networks. Machine Learning and Knowledge Discovery in Databases, ECML-PKDD-LNCS 8726:pp 508–511.

  103. Guo ZW, Xie C, Yang JR, Li JH, Yang JH, Zheng L (2015) MtiBase: a database for decoding microRNA target sites located within CDS and 5′UTR regions from CLIP-Seq and expression profile datasets. Database: (Journal of Biological Databases Curation) 2015:bav102. doi:10.1093/database/bav102

    Google Scholar 

  104. Wang X (2008) miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA 14:1012–1017. doi:10.1261/rna.965408

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Betel D, Wilson M, Gabow A, Marks DS, Sander C (2008) The microRNA.org resource: targets and expression. Nucleic Acids Res 36:D149–D153. doi:10.1093/nar/gkm995

    Article  CAS  PubMed  Google Scholar 

  106. Betel D, Koppal A, Agius P, Sander C, Leslie C (2010) mirSVR predicted target site scoring method: comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol 11:R90. doi:10.1186/gb-2010-11-8-r90

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  107. Gennarino VA, Sardiello M, Mutarelli M, Dharmalingam G, Maselli V et al (2011) HOCTAR database: a unique resource for microRNA target prediction. Gene 480:51–58. doi:10.1016/j.gene.2011.03.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Gennarino VA, Sardiello M, Avellino R, Meola N, Maselli V, Anand S, Cutillo L, Ballabio A, Banfi S (2008) MicroRNA target prediction by expression analysis of host genes. Genome Res 19:481–490; Published in Advance December 16, 2008. doi:10.1101/gr.084129.108.

    Article  CAS  Google Scholar 

  109. Elefant N, Berger A, Shein H, Hofree M, Margalit H, Altuvia Y (2011) RepTar: a database of predicted cellular targets of host and viral miRNAs. Nucleic Acids Res 39:D188–D194. doi:10.1093/nar/gkq1233

    Article  CAS  PubMed  Google Scholar 

  110. Piriyapongsa J, Bootchai C, Ngamphiw C, Tongsima S (2012) microPIR: an integrated database of MicroRNA target sites within human promoter sequences. PLoS One 7:e33888. doi:10.1371/journal.pone.0033888

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Kumar A, Wong AK, Tizard ML, Moore RJ, Lefèvre C (2012) miRNA_targets: a database for miRNA target predictions in coding and non-coding regions of mRNAs. Genomics 100:352–356. doi:10.1016/j.ygeno.2012.08.006

    Article  CAS  PubMed  Google Scholar 

  112. Rukov JL, Wilentzik R, Jaffe I, Vinther J, Shomron N (2013) Pharmaco-miR: linking microRNAs and drug effects. Brief Bioinform 15:648–659. doi:10.1093/bib/bbs082

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  113. Ru Y, Kechris KJ, Tabakoff B, Hoffman P, Radcliffe RA, Bowler B et al (2014) The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations. Nucleic Acids Res 42:e133. doi:10.1093/nar/gku631

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Wang J, Lu M, Qiu C, Cui Q (2010) TransmiR: a transcription factor–microRNA regulation database. Nucleic Acids Res (2010) 38: D119–D122. doi:10.1093/nar/gkp803.

    Article  CAS  PubMed  Google Scholar 

  115. Bandyopadhyay S, Bhattacharyya M (2010) PuTmiR: a database for extracting neighboring transcription factors of human microRNAs. BMC Bioinform 11:190. doi:10.1186/1471-2105-11-190

    Article  CAS  Google Scholar 

  116. Bruno AE, Li L, Kalabus JL, Pan Y, Yu A, Hu Z (2012) miRdSNP: a database of disease-associated SNPs and microRNA target sites on 3′UTRs of human genes. BMC Genomics 13:44. doi:10.1186/1471-2164-13-44

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Bao L, Zhou M, Wu L, Lu L, Goldowitz D, Williams RW, Cui Y (2007) PolymiRTS Database: linking polymorphisms in microRNA target sites with complex traits. Nucleic Acids Res. 35: D51–D54. doi:10.1093/nar/gkl797

    Article  CAS  PubMed  Google Scholar 

  118. Ziebarth JD, Bhattacharya A, Chen A, Cui Y (2012) PolymiRTS Database 2.0: linking polymorphisms in microRNA target sites with human diseases and complex traits. Nucleic Acids Res 40:D216–D221. doi:10.1093/nar/gkr1026

    Article  CAS  PubMed  Google Scholar 

  119. Bhattacharya A, Ziebarth JD, Cui Y (2014) PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways. Nucleic Acids Res 42:D86–D91. doi:10.1093/nar/gkt1028

    Article  CAS  PubMed  Google Scholar 

  120. Laganà A, Paone A, Veneziano D, Cascione L, Gasparini P et al (2012) miR-EdiTar: A database of predicted A-to-I edited miRNA target sites. Bioinformatics 28:3166–3168. doi:10.1093/bioinformatics/bts589

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  121. Hsu PW, Lin LZ, Hsu SD, Hsu JB, Huang HD (2007) ViTa: prediction of host microRNAs targets on viruses. Nucleic Acids Res 35:D381–D385. doi:10.1093/nar/gkl1009

    Article  CAS  PubMed  Google Scholar 

  122. Li SC, Shiau CK, Lin WC (2008) Vir-Mir db: prediction of viral microRNA candidate hairpins. Nucleic Acids Res 36:D184–D189. doi:10.1093/nar/gkm610

    Article  CAS  PubMed  Google Scholar 

  123. Li SC, Pan CY, Lin WC (2006) Bioinformatic discovery of microRNA precursors from human ESTs and introns. BMC Genomics 7(1):164. doi:10.1186/1471-2164-7-164

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The author would like to avail the opportunity to thank the MANIT BHOPAL and Ministry of HRD, Government of India who furnished the support infrastructure to make this article a reality. The author expresses sincere, warm and heartfelt thanks towards Mr. Dinesh Sharma, English Language coach, Professional Trainer, and mentor of English and Business Communication, who put sincere and concentrated efforts to edit the language of this manuscript with utmost dedication and patience.

Author information

Authors and Affiliations

  1. Department of Biological Science and Engineering, Maulana Azad National Institute of Technology, Bhopal, 462003, India

    Nagendra Kumar Singh

Authors
  1. Nagendra Kumar Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nagendra Kumar Singh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singh, N.K. miRNAs target databases: developmental methods and target identification techniques with functional annotations. Cell. Mol. Life Sci. 74, 2239–2261 (2017). https://doi.org/10.1007/s00018-017-2469-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00018-017-2469-1

Keywords

Search

Navigation