Skip to main content

An Overview of miRNA and miRNA Target Analysis Tools

  • Protocol
  • First Online:
Plant MicroRNAs

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1932))

Abstract

microRNA molecules have been shown to play various significant roles in many physiological and pathophysiological processes in living organisms. The tremendous interest in these molecules has led to the significant development and constant release of a number of computational tools useful for basic as well as advanced miRNA-related analyses. These approaches have various constantly evolving utilities, such as detection, target prediction, functional annotation, and many others. In this chapter, we provide an overview of several computational tools useful for broadly defined plant miRNA analysis.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

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(5):843–854

    Article  CAS  PubMed  Google Scholar 

  2. Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G (2000) The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403:901–906

    Article  CAS  PubMed  Google Scholar 

  3. Zhang B, Wang Q, Pan X (2007) MicroRNAs and their regulatory roles in animals and plants. J Cell Physiol 210:279–289

    Article  CAS  PubMed  Google Scholar 

  4. Bushati N, Cohen SM (2007) microRNA functions. Annu Rev Cell Dev Biol 23:175–205

    Article  CAS  PubMed  Google Scholar 

  5. Dugas DV, Bartel B (2004) MicroRNA regulation of gene expression in plants. Curr Opin Plant Biol 7:512–520

    Article  CAS  PubMed  Google Scholar 

  6. Kruszka K, Pieczynski M, Windels D, Bielewicz D, Jarmolowski A, Szweykowska-Kulinska Z, Vazquez F (2012) Role of microRNAs and other sRNAs of plants in their changing environments. J Plant Physiol 169:1664–1672

    Article  CAS  PubMed  Google Scholar 

  7. Islam W, Islam SU, Qasim M, Wang L (2017) Host-Pathogen interactions modulated by small RNAs. RNA Biol 14:891–904

    Article  PubMed  PubMed Central  Google Scholar 

  8. Komiya R (2017) Biogenesis of diverse plant phasiRNAs involves an miRNA-trigger and Dicer-processing. J Plant Res 130:17–23

    Article  CAS  PubMed  Google Scholar 

  9. Lukasik A, Zielenkiewicz P (2016) Plant microRNAs-novel players in natural medicine? Int J Mol Sci 18:9

    Article  PubMed Central  Google Scholar 

  10. Rajendiran A, Chatterjee A, Pan A (2018) Computational approaches and related tools to identify microRNAs in a species: a bird’s eye view. Interdiscip Sci 10(3):616–635. https://doi.org/10.1007/s12539-017-0223-x

    Article  CAS  PubMed  Google Scholar 

  11. Akhtar MM, Micolucci L, Islam MS, Olivieri F, Procopio AD (2016) Bioinformatic tools for microRNA dissection. Nucleic Acids Res 44:24–44

    Article  CAS  PubMed  Google Scholar 

  12. Aghaee-Bakhtiari SH, Arefian E, Lau P (2018) miRandb: a resource of online services for miRNA research. Brief Bioinform 19(2):254–262. https://doi.org/10.1093/bib/bbw109

    Article  PubMed  Google Scholar 

  13. Riffo-Campos AL, Riquelme I, Brebi-Mieville P (2016) Tools for sequence-based miRNA target prediction: what to choose? Int J Mol Sci 17:1987

    Article  PubMed Central  Google Scholar 

  14. Singh NK (2017) microRNAs databases: developmental methodologies, structural and functional annotations. Interdiscip Sci 9:357–377

    Article  CAS  PubMed  Google Scholar 

  15. Kleftogiannis D, Korfiati A, Theofilatos K, Likothanassis S, Tsakalidis A, Mavroudi S (2013) Where we stand, where we are moving: surveying computational techniques for identifying miRNA genes and uncovering their regulatory role. J Biomed Inform 46:563–573

    Article  PubMed  Google Scholar 

  16. Shukla V, Varghese VK, Kabekkodu SP, Mallya S, Satyamoorthy K (2017) A compilation of Web-based research tools for miRNA analysis. Brief Funct Genomics 16(5):249–273. https://doi.org/10.1093/bfgp/elw042

    Article  PubMed  Google Scholar 

  17. Bonnal RJ, Rossi RL, Carpi D, Ranzani V, Abrignani S, Pagani M (2015) miRiadne: a web tool for consistent integration of miRNA nomenclature. Nucleic Acids Res 43:W487–W492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Henry VJ, Bandrowski AE, Pepin AS, Gonzalez BJ, Desfeux A (2014) OMICtools: an informative directory for multi-omic data analysis. Database 2014:bau069

    Article  PubMed  PubMed Central  Google Scholar 

  19. Lukasik A, Wojcikowski M, Zielenkiewicz P (2016) Tools4miRs – one place to gather all the tools for miRNA analysis. Bioinformatics 32:2722–2724

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wu J, Liu Q, Wang X, Zheng J, Wang T, You M, Sheng Sun Z, Shi Q (2013) mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing. RNA Biol 10:1087–1092

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Friedlander MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N (2008) Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol 26:407–415

    Article  PubMed  Google Scholar 

  22. Yang X, Li L (2011) miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants. Bioinformatics 27:2614–2615

    Article  CAS  PubMed  Google Scholar 

  23. Kozomara A, Birgaoanu M, Griffiths-Jones S (2018) miRBase: from microRNA sequences to function. Nucleic Acids Res. https://doi.org/10.1093/nar/gky1141

    Article  PubMed Central  Google Scholar 

  24. Rueda A, Barturen G, Lebron R, Gomez-Martin C, Alganza A, Oliver JL, Hackenberg M (2015) sRNAtoolbox: an integrated collection of small RNA research tools. Nucleic Acids Res 43:W467–W473

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Gomez-Martin C, Lebron R, Rueda A, Oliver JL, Hackenberg M (2017) sRNAtoolboxVM: small RNA analysis in a virtual machine. Methods Mol Biol 1580:149–174

    Article  CAS  PubMed  Google Scholar 

  26. Zhang B, Pan X, Cannon CH, Cobb GP, Anderson TA (2006) Conservation and divergence of plant microRNA genes. Plant J 46:243–259

    Article  CAS  PubMed  Google Scholar 

  27. Chorostecki U, Moro B, Rojas AML, Debernardi JM, Schapire AL, Notredame C, Palatnik JF (2017) Evolutionary footprints reveal insights into plant microRNA biogenesis. Plant Cell 29:1248–1261

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Wheeler BM, Heimberg AM, Moy VN, Sperling EA, Holstein TW, Heber S, Peterson KJ (2009) The deep evolution of metazoan microRNAs. Evol Dev 11:50–68

    Article  CAS  PubMed  Google Scholar 

  29. Friedman RC, Farh KK, Burge CB, Bartel DP (2009) Most mammalian mRNAs are conserved targets of microRNAs. Genome Res 19:92–105

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297

    Article  CAS  PubMed  Google Scholar 

  31. Neilsen CT, Goodall GJ, Bracken CP (2012) IsomiRs--the overlooked repertoire in the dynamic microRNAome. Trends Genet 28:544–549

    Article  CAS  PubMed  Google Scholar 

  32. Ahmed F, Senthil-Kumar M, Lee S, Dai X, Mysore KS, Zhao PX (2014) Comprehensive analysis of small RNA-seq data reveals that combination of miRNA with its isomiRs increase the accuracy of target prediction in Arabidopsis thaliana. RNA Biol 11:1414–1429

    Article  PubMed  Google Scholar 

  33. Sablok G, Srivastva AK, Suprasanna P, Baev V, Ralph PJ (2015) isomiRs: increasing evidences of isomiRs complexity in plant stress functional biology. Front Plant Sci 6:949

    Article  PubMed  PubMed Central  Google Scholar 

  34. Cloonan N, Wani S, Xu Q, Gu J, Lea K, Heater S, Barbacioru C, Steptoe AL, Martin HC, Nourbakhsh E, Krishnan K, Gardiner B, Wang X, Nones K, Steen JA, Matigian NA, Wood DL, Kassahn KS, Waddell N, Shepherd J, Lee C, Ichikawa J, McKernan K, Bramlett K, Kuersten S, Grimmond SM (2011) MicroRNAs and their isomiRs function cooperatively to target common biological pathways. Genome Biol 12:R126

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Pantano L, Estivill X, Marti E (2010) SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells. Nucleic Acids Res 38:e34

    Article  PubMed  Google Scholar 

  36. Yang K, Sablok G, Qiao G, Nie Q, Wen X (2017) isomiR2Function: an integrated workflow for identifying microRNA variants in plants. Front Plant Sci 8:322

    PubMed  PubMed Central  Google Scholar 

  37. Zhang Y, Zang Q, Zhang H, Ban R, Yang Y, Iqbal F, Li A, Shi Q (2016) DeAnnIso: a tool for online detection and annotation of isomiRs from small RNA sequencing data. Nucleic Acids Res 44:W166–W175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhang Y, Xu B, Yang Y, Ban R, Zhang H, Jiang X, Cooke HJ, Xue Y, Shi Q (2012) CPSS: a computational platform for the analysis of small RNA deep sequencing data. Bioinformatics 28:1925–1927

    Article  CAS  PubMed  Google Scholar 

  39. Achkar NP, Cambiagno DA, Manavella PA (2016) miRNA biogenesis: a dynamic pathway. Trends Plant Sci 21:1034–1044

    Article  CAS  PubMed  Google Scholar 

  40. Voinnet O (2009) Origin, biogenesis, and activity of plant microRNAs. Cell 136:669–687

    Article  CAS  PubMed  Google Scholar 

  41. Tav C, Tempel S, Poligny L, Tahi F (2016) miRNAFold: a web server for fast miRNA precursor prediction in genomes. Nucleic Acids Res 44:W181–W184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Tempel S, Tahi F (2012) A fast ab-initio method for predicting miRNA precursors in genomes. Nucleic Acids Res 40:e80

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Yu L, Shao C, Ye X, Meng Y, Zhou Y, Chen M (2016) miRNA digger: a comprehensive pipeline for genome-wide novel miRNA mining. Sci Rep 6:18901

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Ma X, Shao C, Jin Y, Wang H, Meng Y (2014) Long non-coding RNAs: a novel endogenous source for the generation of Dicer-like 1-dependent small RNAs in Arabidopsis thaliana. RNA Biol 11:373–390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Meng Y, Gou L, Chen D, Wu P, Chen M (2010) High-throughput degradome sequencing can be used to gain insights into microRNA precursor metabolism. J Exp Bot 61:3833–3837

    Article  CAS  PubMed  Google Scholar 

  46. Gudys A, Szczesniak MW, Sikora M, Makalowska I (2013) HuntMi: an efficient and taxon-specific approach in pre-miRNA identification. BMC Bioinformatics 14:83

    Article  PubMed  PubMed Central  Google Scholar 

  47. Pasquinelli AE (2012) MicroRNAs and their targets: recognition, regulation and an emerging reciprocal relationship. Nat Rev Genet 13:271–282

    Article  CAS  PubMed  Google Scholar 

  48. Huntzinger E, Izaurralde E (2011) Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Nat Rev Genet 12:99–110

    Article  CAS  PubMed  Google Scholar 

  49. Liu Q, Wang F, Axtell MJ (2014) Analysis of complementarity requirements for plant microRNA targeting using a Nicotiana benthamiana quantitative transient assay. Plant Cell 26:741–753

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Peterson SM, Thompson JA, Ufkin ML, Sathyanarayana P, Liaw L, Congdon CB (2014) Common features of microRNA target prediction tools. Front Genet 5:23

    Article  PubMed  PubMed Central  Google Scholar 

  51. Dai X, Zhao PX (2011) psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res 39:W155–W159

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. 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

    Article  CAS  PubMed  Google Scholar 

  53. Franco-Zorrilla JM, Valli A, Todesco M, Mateos I, Puga MI, Rubio-Somoza I, Leyva A, Weigel D, Garcia JA, Paz-Ares J (2007) Target mimicry provides a new mechanism for regulation of microRNA activity. Nat Genet 39:1033–1037

    Article  CAS  PubMed  Google Scholar 

  54. 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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Yu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16:284–287

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Zagganas K, Vergoulis T, Paraskevopoulou MD, Vlachos IS, Skiadopoulos S, Dalamagas T (2017) BUFET: boosting the unbiased miRNA functional enrichment analysis using bitsets. BMC Bioinformatics 18:399

    Article  PubMed  PubMed Central  Google Scholar 

  57. Bleazard T, Lamb JA, Griffiths-Jones S (2015) Bias in microRNA functional enrichment analysis. Bioinformatics 31:1592–1598

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Busk PK (2014) A tool for design of primers for microRNA-specific quantitative RT-qPCR. BMC Bioinformatics 15:29

    Article  PubMed  PubMed Central  Google Scholar 

  59. Balcells I, Cirera S, Busk PK (2011) Specific and sensitive quantitative RT-PCR of miRNAs with DNA primers. BMC Biotechnol 11:70

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Cirera S, Busk PK (2014) Quantification of miRNAs by a simple and specific qPCR method. Methods Mol Biol 1182:73–81

    Article  PubMed  Google Scholar 

  61. Ossowski S, Schwab R, Weigel D (2008) Gene silencing in plants using artificial microRNAs and other small RNAs. Plant J 53:674–690

    Article  CAS  PubMed  Google Scholar 

  62. Patel P, Ramachandruni SD, Kakrana A, Nakano M, Meyers BC (2016) miTRATA: a web-based tool for microRNA truncation and tailing analysis. Bioinformatics 32:450–452

    Article  CAS  PubMed  Google Scholar 

  63. Li J, Yang Z, Yu B, Liu J, Chen X (2005) Methylation protects miRNAs and siRNAs from a 3′-end uridylation activity in Arabidopsis. Curr Biol 15:1501–1507

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Yang Z, Ebright YW, Yu B, Chen X (2006) HEN1 recognizes 21-24 nt small RNA duplexes and deposits a methyl group onto the 2′ OH of the 3′ terminal nucleotide. Nucleic Acids Res 34:667–675

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Zhai J, Zhao Y, Simon SA, Huang S, Petsch K, Arikit S, Pillay M, Ji L, Xie M, Cao X, Yu B, Timmermans M, Yang B, Chen X, Meyers BC (2013) Plant microRNAs display differential 3′ truncation and tailing modifications that are ARGONAUTE1 dependent and conserved across species. Plant Cell 25:2417–2428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Zhai J, Meyers BC (2012) Deep sequencing from hen1 mutants to identify small RNA 3′ modifications. Cold Spring Harb Symp Quant Biol 77:213–219

    Article  CAS  PubMed  Google Scholar 

  67. Van Peer G, Lefever S, Anckaert J, Beckers A, Rihani A, Van Goethem A, Volders PJ, Zeka F, Ongenaert M, Mestdagh P, Vandesompele J (2014) miRBase Tracker: keeping track of microRNA annotation changes. Database 2014:bau080

    PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Piotr Zielenkiewicz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

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

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Lukasik, A., Zielenkiewicz, P. (2019). An Overview of miRNA and miRNA Target Analysis Tools. In: de Folter, S. (eds) Plant MicroRNAs. Methods in Molecular Biology, vol 1932. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9042-9_5

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-9042-9_5

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-9041-2

  • Online ISBN: 978-1-4939-9042-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics