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Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources

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Bioinformatics in MicroRNA Research

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1617))

Abstract

MicroRNA (miRNA) mediated silencing and repression of mRNA molecules requires complementary base pairing between the “seed” region of the miRNA and the “seed match” region of target mRNAs. While this mechanism is fairly well understood, accurate prediction of valid miRNA targets remains challenging due to factors such as imperfect sequence specificity, target site availability, and the thermodynamic stability of the mRNA structure itself. As knowledge of what genes are being targeted by each miRNA is arguably the most important facet of miRNA biology, many approaches have been developed to address the need for reliable prediction and ranking of putative targets, with most using a combination of various strategies such as evolutionary conservation, statistical inference, and distinct features of the target sequences themselves. This chapter reviews the pros and cons of a number of different prediction algorithms, showcases some databases that store experimentally validated miRNA targets, and also provides a case study that profiles some of the potential microRNA–mRNA interactions predicted by each methodology for various human genes.

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References

  1. 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 

  2. Kozomara A, Griffiths-Jones S (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42:D68–D73. doi:10.1093/nar/gkt1181

    Article  CAS  PubMed  Google Scholar 

  3. Wu S, Huang S, Ding J et al (2010) Multiple microRNAs modulate p21Cip1/Waf1 expression by directly targeting its 3′ untranslated region. Oncogene 29:2302–2308. doi:10.1038/onc.2010.34

    Article  CAS  PubMed  Google Scholar 

  4. Selbach M, Schwanhäusser B, Thierfelder N et al (2008) Widespread changes in protein synthesis induced by microRNAs. Nature 455:58–63. doi:10.1038/nature07228

    Article  CAS  PubMed  Google Scholar 

  5. Barbato C, Arisi I, Frizzo ME et al (2009) Computational challenges in miRNA target predictions: to be or not to be a true target? J Biomed Biotechnol 2009:803069. doi:10.1155/2009/803069

    PubMed  PubMed Central  Google Scholar 

  6. He L, Hannon GJ (2004) MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet 5:522–531. doi:10.1038/nrg1379

    Article  CAS  PubMed  Google Scholar 

  7. Bartel DP (2009) MicroRNAs: target recognition and regulatory functions. Cell 136:215–233. doi:10.1016/j.cell.2009.01.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Brennecke J, Stark A, Russell RB, Cohen SM (2005) Principles of MicroRNA–target recognition. PLoS Biol 3:e85. doi:10.1371/journal.pbio.0030085

    Article  PubMed  PubMed Central  Google Scholar 

  9. Didiano D, Hobert O (2006) Perfect seed pairing is not a generally reliable predictor for miRNA-target interactions. Nat Struct Mol Biol 13:849–851. doi:10.1038/nsmb1138

    Article  CAS  PubMed  Google Scholar 

  10. Doench JG, Sharp PA (2004) Specificity of microRNA target selection in translational repression. Genes Dev 18:504–511. doi:10.1101/gad.1184404

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Grimson A, Farh KK-H, Johnston WK et al (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 

  12. Baek D, Villén J, Shin C et al (2008) The impact of microRNAs on protein output. Nature 455:64–71. doi:10.1038/nature07242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Miranda KC, Huynh T, Tay Y 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 

  14. Wen J, Parker BJ, Jacobsen A, Krogh A (2011) MicroRNA transfection and AGO-bound CLIP-seq data sets reveal distinct determinants of miRNA action. RNA 17:820–834. doi:10.1261/rna.2387911

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Coronnello C, Benos PV (2013) ComiR: combinatorial microRNA target prediction tool. Nucleic Acids Res 41:W159–W164. doi:10.1093/nar/gkt379

    Article  PubMed  PubMed Central  Google Scholar 

  16. Paraskevopoulou MD, Georgakilas G, Kostoulas N et al (2013) DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Res 41:W169–W173. doi:10.1093/nar/gkt393

    Article  PubMed  PubMed Central  Google Scholar 

  17. 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  Google Scholar 

  18. Gennarino VA, Sardiello M, Mutarelli M 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 

  19. 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. doi:10.1038/srep08004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Thadani R, Tammi MT (2006) MicroTar: predicting microRNA targets from RNA duplexes. BMC Bioinformatics 7(Suppl 5):S20. doi:10.1186/1471-2105-7-S5-S20

    Article  PubMed  PubMed Central  Google Scholar 

  21. John B, Enright AJ, Aravin A et al (2004) Human microRNA targets. PLoS Biol 2:e363. doi:10.1371/journal.pbio.0020363

    Article  PubMed  PubMed Central  Google Scholar 

  22. Laganà A, Forte S, Russo F et al (2010) Prediction of human targets for viral-encoded microRNAs by thermodynamics and empirical constraints. J RNAi Gene Silencing 6:379–385

    PubMed  PubMed Central  Google Scholar 

  23. Vejnar CE, Zdobnov EM (2012) MiRmap: comprehensive prediction of microRNA target repression strength. Nucleic Acids Res 40:11673–11683. doi:10.1093/nar/gks901

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Kumar A, Wong AK-L, Tizard ML et al (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 

  25. Gumienny R, Zavolan M (2015) Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G. Nucleic Acids Res 43:1380–1391. doi:10.1093/nar/gkv050

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Filshtein TJ, Mackenzie CO, Dale MD et al (2014) OrbId: origin-based identification of microRNA targets. Mob Genet Elements 2:184–192. doi:10.4161/mge.21617

    Article  Google Scholar 

  27. Šulc M, Marín RM, Robins HS, Vaníček J (2015) PACCMIT/PACCMIT-CDS: identifying microRNA targets in 3′ UTRs and coding sequences. Nucleic Acids Res 43:W474–W479. doi:10.1093/nar/gkv457

    Article  PubMed  PubMed Central  Google Scholar 

  28. Krek A, Grün D, Poy MN et al (2005) Combinatorial microRNA target predictions. Nat Genet 37:495–500. doi:10.1038/ng1536

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  30. Loher P, Rigoutsos I (2012) Interactive exploration of RNA22 microRNA target predictions. Bioinformatics 28:3322–3323. doi:10.1093/bioinformatics/bts615

    Article  CAS  PubMed  Google Scholar 

  31. Kruger J, 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  Google Scholar 

  32. Agarwal V, Bell GW, Nam J-W, Bartel DP (2015) Predicting effective microRNA target sites in mammalian mRNAs. eLife. doi:10.7554/eLife.05005

    Google Scholar 

  33. 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 

  34. Schirle NT, Sheu-Gruttadauria J, MacRae IJ (2014) Structural basis for microRNA targeting. Science 346:608–613. doi:10.1126/science.1258040

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Nielsen CB, Shomron N, Sandberg R et al (2007) Determinants of targeting by endogenous and exogenous microRNAs and siRNAs. RNA 13:1894–1910. doi:10.1261/rna.768207

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Friedman RC, Farh KK-H, Burge CB, Bartel DP (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 

  37. Robins H, Press WH (2005) Human microRNAs target a functionally distinct population of genes with AT-rich 3′ UTRs. Proc Natl Acad Sci 102:15557–15562. doi:10.1073/pnas.0507443102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Hausser J, Zavolan M (2014) Identification and consequences of miRNA-target interactions—beyond repression of gene expression. Nat Rev Genet 15:599–612. doi:10.1038/nrg3765

    Article  CAS  PubMed  Google Scholar 

  39. Majoros WH, Ohler U (2007) Spatial preferences of microRNA targets in 3′ untranslated regions. BMC Genomics 8:152. doi:10.1186/1471-2164-8-152

    Article  PubMed  PubMed Central  Google Scholar 

  40. Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31:3406–3415. doi:10.1093/nar/gkg595

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Zuker M, Stiegler P (1981) Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res 9:133–148. doi:10.1093/nar/9.1.133

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Lewis BP, Shih I, Jones-Rhoades MW et al (2003) Prediction of mammalian microRNA targets. Cell 115:787–798

    Article  CAS  PubMed  Google Scholar 

  43. 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 

  44. Roberts JT, Cooper EA, Favreau CJ et al (2013) Continuing analysis of microRNA origins: formation from transposable element insertions and noncoding RNA mutations. Mob Genet Elements 3:e27755. doi:10.4161/mge.27755

    Article  PubMed  Google Scholar 

  45. Roberts JT, Cardin SE, Borchert GM (2014) Burgeoning evidence indicates that microRNAs were initially formed from transposable element sequences. Mob Genet Elements 4:e29255. doi:10.4161/mge.29255

    Article  PubMed  PubMed Central  Google Scholar 

  46. Boser BE, Guyon IM, Vapnik VN (1992) A training algorithm for optimal margin classifiers. In: Proceedings of the 5th annual ACM workshop on computational learning theory, Pittsburgh, PA, 27–29 July 1992. ACM, New York, pp 144–152. ISBN:0-89791-497-X. doi:10.1145/130385.130401

  47. Wong N, Wang X (2015) miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res 43:D146–D152. doi:10.1093/nar/gku1104

    Article  PubMed  Google Scholar 

  48. 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  Google Scholar 

  49. Hsu S-D, Tseng Y-T, Shrestha S 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 

  50. Vlachos IS, Paraskevopoulou MD, Karagkouni D et al (2015) DIANA-TarBase v7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions. Nucleic Acids Res 43:D153–D159. doi:10.1093/nar/gku1215

    Article  PubMed  Google Scholar 

  51. Borchert GM, Gilmore BL, Spengler RM et al (2009) Adenosine deamination in human transcripts generates novel microRNA binding sites. Hum Mol Genet 18:4801–4807. doi:10.1093/hmg/ddp443

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Yang X, Zhang H, Li L (2012) Alternative mRNA processing increases the complexity of microRNA-based gene regulation in Arabidopsis. Plant J 70:421–431. doi:10.1111/j.1365-313X.2011.04882.x

    Article  CAS  PubMed  Google Scholar 

  53. Clark PM, Loher P, Quann K et al (2014) Argonaute CLIP-seq reveals miRNA targetome diversity across tissue types. Sci Rep 4:5947. doi:10.1038/srep05947

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Lee I, Ajay SS, Jong IY et al (2009) New class of microRNA targets containing simultaneous 5′-UTR and 3′-UTR interaction sites. Genome Res 19:1175–1183. doi:10.1101/gr.089367.108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Jalali S, Bhartiya D, Lalwani MK et al (2013) Systematic transcriptome wide analysis of lncRNA-miRNA interactions. PLoS One 8:e53823. doi:10.1371/journal.pone.0053823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Biology, University of South Alabama, Mobile, AL, 36688, USA

    Justin T. Roberts & Glen M. Borchert Ph.D.

  2. Department of Pharmacology, University of South Alabama, Mobile, AL, 36688, USA

    Glen M. Borchert Ph.D.

Authors
  1. Justin T. Roberts
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  2. Glen M. Borchert Ph.D.
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Corresponding author

Correspondence to Glen M. Borchert Ph.D. .

Editor information

Editors and Affiliations

  1. School of Computing, University of South Alabama, Mobile, Alabama, USA

    Jingshan Huang

  2. Department of Pharmacology, University of South Alabama, Mobile, Alabama, USA

    Glen M. Borchert

  3. Department of Computer and Information Science, University of Oregon, Eugene, Oregon, USA

    Dejing Dou

  4. Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, Kansas, USA

    Jun (Luke) Huan

  5. School of Bioengineering, Qilu University of Technology, Jinan, Shandong, China

    Wenjun Lan

  6. Mitchel Cancer Institute, University of South Alabama, Mobile, Alabama, USA

    Ming Tan

  7. Department of Endocrinology, First Affiliated Hospital, Kunming Medical University, Kunming, Yunnan, China

    Bin Wu

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Roberts, J.T., Borchert, G.M. (2017). Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources. In: Huang, J., et al. Bioinformatics in MicroRNA Research. Methods in Molecular Biology, vol 1617. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7046-9_8

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  • DOI: https://doi.org/10.1007/978-1-4939-7046-9_8

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7044-5

  • Online ISBN: 978-1-4939-7046-9

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