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isoTar: Consensus Target Prediction with Enrichment Analysis for MicroRNAs Harboring Editing Sites and Other Variations

  • Rosario Distefano
  • Giovanni NigitaEmail author
  • Dario Veneziano
  • Giulia Romano
  • Carlo M. Croce
  • Mario Acunzo
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1970)

Abstract

MicroRNAs (miRNAs) are small noncoding RNA molecules (sncRNAs) involved in gene expression regulation. Having been widely studied during last two decades, they have been associated with several diseases, including cancer. Recent improvements in high throughput sequencing technologies have revealed a more complex miRNAome, due to miRNA sequence modification phenomena, such as RNA editing and isomiRs. As a result, a new class of tools is necessary in order to appropriately investigate this emerging complexity. To address such need, we developed isoTar, a high-performance Web-based containerized application designed for miRNA consensus targeting prediction and functional enrichment analyses. In the present chapter, we provide an overview of isoTar (https://ncrnaome.osumc.edu/isotar/), as well as benchmarks and a guide to its usage.

Key words

A-to-I RNA editing Editome IsomiRs ADAR 

References

  1. 1.
    Ha M, Kim VN (2014) Regulation of microRNA biogenesis. Nat Rev Mol Cell Biol 15:509–524. https://doi.org/10.1038/nrm3838CrossRefPubMedGoogle Scholar
  2. 2.
    Han J, Lee Y, Yeom K-H et al (2004) The Drosha-DGCR8 complex in primary microRNA processing. Genes Dev 18:3016–3027. https://doi.org/10.1101/gad.1262504CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Yi R, Qin Y, Macara IG, Cullen BR (2003) Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs. Genes Dev 17:3011–3016. https://doi.org/10.1101/gad.1158803CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Bohnsack MT, Czaplinski K, Gorlich D (2004) Exportin 5 is a RanGTP-dependent dsRNA-binding protein that mediates nuclear export of pre-miRNAs. RNA 10:185–191. https://doi.org/10.1261/rna.5167604CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Macrae IJ, Zhou K, Li F et al (2006) Structural basis for double-stranded RNA processing by Dicer. Science 311:195–198. https://doi.org/10.1126/science.1121638CrossRefPubMedGoogle Scholar
  6. 6.
    Nishikura K (2016) A-to-I editing of coding and non-coding RNAs by ADARs. Nat Rev Mol Cell Biol 17:83–96. https://doi.org/10.1038/nrm.2015.4CrossRefPubMedGoogle Scholar
  7. 7.
    Nigita G, Veneziano D, Ferro A (2015) A-to-I RNA editing: current knowledge sources and computational approaches with special emphasis on non-coding RNA molecules. Front Bioeng Biotechnol 3:37. https://doi.org/10.3389/fbioe.2015.00037CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Zhou H, Arcila ML, Li Z et al (2012) Deep annotation of mouse iso-miR and iso-moR variation. Nucleic Acids Res 40:5864–5875. https://doi.org/10.1093/nar/gks247CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Neilsen CT, Goodall GJ, Bracken CP (2012) IsomiRs – the overlooked repertoire in the dynamic microRNAome. Trends Genet 28:544–549. https://doi.org/10.1016/j.tig.2012.07.005CrossRefPubMedGoogle Scholar
  10. 10.
    Yang W, Chendrimada TP, Wang Q et al (2006) Modulation of microRNA processing and expression through RNA editing by ADAR deaminases. Nat Struct Mol Biol 13:13–21. https://doi.org/10.1038/nsmb1041CrossRefPubMedGoogle Scholar
  11. 11.
    Kawahara Y, Zinshteyn B, Sethupathy P et al (2007) Redirection of silencing targets by adenosine-to-inosine editing of miRNAs. Science 315:1137–1140. https://doi.org/10.1126/science.1138050CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Nigita G, Acunzo M, Romano G et al (2016) microRNA editing in seed region aligns with cellular changes in hypoxic conditions. Nucleic Acids Res 44:6298–6308. https://doi.org/10.1093/nar/gkw532CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Kozomara A, Griffiths-Jones S (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42:D68–D73. https://doi.org/10.1093/nar/gkt1181CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Magee RG, Telonis AG, Loher P et al (2018) Profiles of miRNA isoforms and tRNA fragments in prostate cancer. Sci Rep 8:5314. https://doi.org/10.1038/s41598-018-22488-2CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Merkel D (2014) Docker: lightweight Linux containers for consistent development and deployment. Linux J 2014:2Google Scholar
  16. 16.
    Spurlock J (2013) Bootstrap: responsive web development. O'Reilly Media, Inc, Newton, MAGoogle Scholar
  17. 17.
    De Volder K (2006) JQuery: a generic code browser with a declarative configuration language. In: Practical aspects of declarative languages. Springer, Berlin, Heidelberg, Berlin, Heidelberg, pp 88–102Google Scholar
  18. 18.
    Bardou P, Mariette J, Escudié F et al (2014) jvenn: an interactive Venn diagram viewer. BMC Bioinformatics 15:293. https://doi.org/10.1186/1471-2105-15-293CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Vejnar CE, Zdobnov EM (2012) MiRmap: comprehensive prediction of microRNA target repression strength. Nucleic Acids Res 40:11673–11683. https://doi.org/10.1093/nar/gks901CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    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. https://doi.org/10.1016/j.cell.2004.12.035CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Kertesz M, Iovino N, Unnerstall U et al (2007) The role of site accessibility in microRNA target recognition. Nat Genet 39:1278–1284. https://doi.org/10.1038/ng2135CrossRefGoogle Scholar
  22. 22.
    Heyne S, Costa F, Rose D, Backofen R (2012) GraphClust: alignment-free structural clustering of local RNA secondary structures. Bioinformatics 28:i224–i232. https://doi.org/10.1093/bioinformatics/bts224CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    John B, Enright AJ, Aravin A et al (2004) Human microRNA targets. PLoS Biol 2:e363. https://doi.org/10.1371/journal.pbio.0020363CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Marín RM, Vanícek J (2011) Efficient use of accessibility in microRNA target prediction. Nucleic Acids Res 39:19–29. https://doi.org/10.1093/nar/gkq768CrossRefPubMedGoogle Scholar
  25. 25.
    Sherry ST, Ward MH, Kholodov M et al (2001) dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 29:308–311CrossRefGoogle Scholar
  26. 26.
    Harris MA, Clark J, Ireland A et al (2004) The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res 32:D258–D261. https://doi.org/10.1093/nar/gkh036CrossRefPubMedGoogle Scholar
  27. 27.
    Croft D, Mundo AF, Haw R et al (2014) The Reactome pathway knowledgebase. Nucleic Acids Res 42:D472–D477. https://doi.org/10.1093/nar/gkt1102CrossRefPubMedGoogle Scholar
  28. 28.
    Fabregat A, Sidiropoulos K, Garapati P et al (2016) The reactome pathway knowledgebase. Nucleic Acids Res 44:D481–D487. https://doi.org/10.1093/nar/gkv1351CrossRefPubMedGoogle Scholar
  29. 29.
    Fabregat A, Jupe S, Matthews L et al (2018) The reactome pathway knowledgebase. Nucleic Acids Res 46:D649–D655. https://doi.org/10.1093/nar/gkx1132CrossRefPubMedGoogle Scholar
  30. 30.
    Kanehisa M, Goto S (2000) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27–30CrossRefGoogle Scholar
  31. 31.
    Haibao T, Klopfenstein D, Pedersen B, et al (2015) GOATOOLS: tools for gene ontology. doi: https://doi.org/10.5281/zenodo.31628
  32. 32.
    Schröder MS, Gusenleitner D, Quackenbush J et al (2013) RamiGO - an R/Bioconductor package providing an AmiGO Visualize interface. Bioinformatics 29:666–668. https://doi.org/10.1093/bioinformatics/bts708CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Gentleman RC, Carey VJ, Bates DM et al (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5:R80. https://doi.org/10.1186/gb-2004-5-10-r80CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Rosario Distefano
    • 1
  • Giovanni Nigita
    • 1
    Email author
  • Dario Veneziano
    • 1
  • Giulia Romano
    • 2
  • Carlo M. Croce
    • 1
  • Mario Acunzo
    • 2
  1. 1.Department of Cancer Biology and Genetics, Comprehensive Cancer CenterThe Ohio State UniversityColumbusUSA
  2. 2.Division of Pulmonary Diseases and Critical Care MedicineVirginia Commonwealth UniversityRichmondUSA

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