Skip to main content
SpringerLink
Log in

An Introduction to Methods for Discovery and Functional Analysis of MicroRNAs in Plants

  • Protocol
  • First Online:
Book cover Plant MicroRNAs

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

Abstract

MicroRNAs play important roles in posttranscriptional regulation of plant development, metabolism, and abiotic stress responses. The recent generation of massive amounts of small RNA sequence data, along with development of bioinformatic tools to identify miRNAs and their mRNA targets, has led to an explosion of newly identified putative miRNAs in plants. Genome editing techniques like CRISPR-Cas9 will allow us to study the biological role of these potential novel miRNAs by efficiently targeting both the miRNA and its mRNA target. In this chapter, we review bioinformatic tools and experimental methods for the identification and functional characterization of miRNAs and their target mRNAs in plants.

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

Access this chapter

Log in via an institution
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. Chen X (2009) Small RNAs and their roles in plant development. Annu Rev Cell Dev Biol 25:21–44

    Article  PubMed  PubMed Central  Google Scholar 

  2. Bulgakov VP, Avramenko TV (2015) New opportunities for the regulation of secondary metabolism in plants: focus on microRNAs. Biotechnol Lett 37:1719–1727

    Article  CAS  PubMed  Google Scholar 

  3. Sunkar R, Li Y-F, Jagadeeswaran G (2012) Functions of microRNAs in plant stress responses. Trends Plant Sci 17:196–203

    Article  CAS  PubMed  Google Scholar 

  4. Yu Y, Jia T, Chen X (2017) The ‘how’ and ‘where’ of plant microRNAs. New Phytol 216:1002–1017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Park W, Li J, Song R et al (2002) CARPEL FACTORY, a Dicer homolog, and HEN1, a novel protein, act in microRNA metabolism in Arabidopsis thaliana. Curr Biol 12:1484–1495

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Vazquez F, Gasciolli V, Crété P, Vaucheret H (2004) The nuclear dsRNA binding protein HYL1 is required for microRNA accumulation and plant development, but not posttranscriptional transgene silencing. Curr Biol 14:346–351

    Article  CAS  PubMed  Google Scholar 

  7. Yang L, Liu Z, Lu F et al (2006) SERRATE is a novel nuclear regulator in primary microRNA processing in Arabidopsis. Plant J 47:841–850

    Article  CAS  PubMed  Google Scholar 

  8. 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 

  9. Baumberger N, Baulcombe DC (2005) Arabidopsis ARGONAUTE1 is an RNA Slicer that selectively recruits microRNAs and short interfering RNAs. Proc Natl Acad Sci U S A 102:11928–11933

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yoshikawa M, Peragine A, Park MY, Poethig RS (2005) A pathway for the biogenesis of trans-acting siRNAs in Arabidopsis. Genes Dev 19:2164–2175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Fei Q, Xia R, Meyers BC (2013) Phased, secondary, small interfering RNAs in posttranscriptional regulatory networks. Plant Cell 25:2400–2415

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Chávez Montes RAC, Rosas-Cárdenas FF, De Paoli E et al (2014) Sample sequencing of vascular plants demonstrates widespread conservation and divergence of microRNAs. Nat Commun 5:3722

    Article  PubMed  Google Scholar 

  13. You C, Cui J, Wang H et al (2017) Conservation and divergence of small RNA pathways and microRNAs in land plants. Genome Biol 18:158

    Article  PubMed  PubMed Central  Google Scholar 

  14. Cuperus JT, Fahlgren N, Carrington JC (2011) Evolution and functional diversification of MIRNA genes. Plant Cell 23:431–442

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. McConnell JR, Barton MK (1998) Leaf polarity and meristem formation in Arabidopsis. Development 125:2935–2942

    CAS  PubMed  Google Scholar 

  16. McConnell JR, Emery J, Eshed Y et al (2001) Role of PHABULOSA and PHAVOLUTA in determining radial patterning in shoots. Nature 411:709–713

    Article  CAS  PubMed  Google Scholar 

  17. Aukerman MJ, Sakai H (2003) Regulation of flowering time and floral organ identity by a MicroRNA and its APETALA2-like target genes. Plant Cell 15:2730–2741

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Palatnik JF, Allen E, Wu X et al (2003) Control of leaf morphogenesis by microRNAs. Nature 425:257–263

    Article  CAS  PubMed  Google Scholar 

  19. Emery JF, Floyd SK, Alvarez J et al (2003) Radial patterning of Arabidopsis shoots by class III HD-ZIP and KANADI genes. Curr Biol 13:1768–1774

    Article  CAS  PubMed  Google Scholar 

  20. Reinhart BJ, Weinstein EG, Rhoades MW et al (2002) MicroRNAs in plants. Genes Dev 16:1616–1626

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Llave C, Kasschau KD, Rector MA, Carrington JC (2002) Endogenous and silencing-associated small RNAs in plants. Plant Cell 14:1605–1619

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Lu C, Tej SS, Luo S et al (2005) Elucidation of the small RNA component of the transcriptome. Science 309:1567–1569

    Article  CAS  PubMed  Google Scholar 

  23. Rhoades MW, Reinhart BJ, Lim LP et al (2002) Prediction of plant microRNA targets. Cell 110:513–520

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  25. Jones-Rhoades MW, Bartel DP (2004) Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell 14:787–799

    Article  CAS  PubMed  Google Scholar 

  26. Wang X, Zhang J, Li F et al (2005) MicroRNA identification based on sequence and structure alignment. Bioinformatics 21:3610–3614

    Article  CAS  PubMed  Google Scholar 

  27. Adai A, Johnson C, Mlotshwa S et al (2005) Computational prediction of miRNAs in Arabidopsis thaliana. Genome Res 15:78–91

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Moxon S, Schwach F, Dalmay T et al (2008) A toolkit for analysing large-scale plant small RNA datasets. Bioinformatics 24:2252–2253

    Article  CAS  PubMed  Google Scholar 

  29. Mendes ND, Freitas AT, Sagot MF (2009) Current tools for the identification of miRNA genes and their targets. Nucleic Acids Res 37:2419–2433

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Williams PH, Eyles R, Weiller G (2012) Plant MicroRNA prediction by supervised machine learning using C5.0 decision trees. J Nucleic Acids 2012:652979

    Article  PubMed  PubMed Central  Google Scholar 

  31. Xuan P, Guo M, Huang Y et al (2011) MaturePred: efficient identification of microRNAs within novel plant pre-miRNAs. PLoS One 6:e27422

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cui H, Zhai J, Ma C (2015) miRLocator: machine learning-based prediction of mature MicroRNAs within plant Pre-miRNA sequences. PLoS One 10:e0142753

    Article  PubMed  PubMed Central  Google Scholar 

  33. Hackenberg M, Sturm M, Langenberger D et al (2009) miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res 37:W68–W76

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Mathelier A, Carbone A (2010) MIReNA: finding microRNAs with high accuracy and no learning at genome scale and from deep sequencing data. Bioinformatics 26:2226–2234

    Article  CAS  PubMed  Google Scholar 

  35. 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 

  36. Breakfield NW, Corcoran DL, Petricka JJ et al (2012) High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis. Genome Res 22:163–176

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lee J, Kim D-I, Park JH et al (2013) MiRAuto: an automated user-friendly microRNA prediction tool utilizing plant small RNA sequencing data. Mol Cells 35:342–347

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. An J, Lai J, Sajjanhar A et al (2014) miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data. BMC Bioinformatics 15:275

    Article  PubMed  PubMed Central  Google Scholar 

  39. Lei J, Sun Y (2014) miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data. Bioinformatics 30:2837–2839

    Article  CAS  PubMed  Google Scholar 

  40. Higashi S, Fournier C, Gautier C et al (2015) Mirinho: An efficient and general plant and animal pre-miRNA predictor for genomic and deep sequencing data. BMC Bioinformatics 16:179

    Article  PubMed  PubMed Central  Google Scholar 

  41. Evers M, Huttner M, Dueck A et al (2015) miRA: adaptable novel miRNA identification in plants using small RNA sequencing data. BMC Bioinformatics 16:370

    Article  PubMed  PubMed Central  Google Scholar 

  42. Paicu C, Mohorianu I, Stocks M et al (2017) miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets. Bioinformatics 33:2446–2454

    Article  PubMed  PubMed Central  Google Scholar 

  43. 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 

  44. Muller H, Marzi MJ, Nicassio F (2014) IsomiRage: from functional classification to differential expression of miRNA isoforms. Front Bioeng Biotechnol 2:38

    Article  PubMed  PubMed Central  Google Scholar 

  45. Zhang Y, Zang Q, Zhang H et al (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 

  46. Yang K, Sablok G, Qiao G et al (2017) isomiR2Function: an integrated workflow for identifying MicroRNA variants in plants. Front Plant Sci 8:322

    PubMed  PubMed Central  Google Scholar 

  47. Zhang Y, Zang Q, Xu B et al (2016) IsomiR bank: a research resource for tracking IsomiRs. Bioinformatics 32:2069–2071

    Article  PubMed  Google Scholar 

  48. Lepe-Soltero D, Armenta-Medina A, Xiang D et al (2017) Annotating and quantifying pri-miRNA transcripts using RNA-Seq data of wild type and serrate-1 globular stage embryos of Arabidopsis thaliana. Data Brief 15:642–647

    Article  PubMed  PubMed Central  Google Scholar 

  49. 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 

  50. Xie F, Zhang B (2010) Target-align: a tool for plant microRNA target identification. Bioinformatics 26:3002–3003

    Article  CAS  PubMed  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. Jha A, Shankar R (2011) Employing machine learning for reliable miRNA target identification in plants. BMC Genomics 12:636

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Wu H-J, Ma Y-K, Chen T et al (2012) PsRobot: a web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40:W22–W28

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Addo-Quaye C, Eshoo TW, Bartel DP, Axtell MJ (2008) Endogenous siRNA and miRNA targets identified by sequencing of the Arabidopsis degradome. Curr Biol 18:758–762

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Addo-Quaye C, Miller W, Axtell MJ (2009) CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets. Bioinformatics 25:130–131

    Article  CAS  PubMed  Google Scholar 

  56. Zheng Y, Li Y-F, Sunkar R, Zhang W (2012) SeqTar: an effective method for identifying microRNA guided cleavage sites from degradome of polyadenylated transcripts in plants. Nucleic Acids Res 40:e28–e28

    Article  CAS  PubMed  Google Scholar 

  57. Li F, Orban R, Baker B (2012) SoMART: a web server for plant miRNA, tasiRNA and target gene analysis. Plant J 70:891–901

    Article  CAS  PubMed  Google Scholar 

  58. Hsu S-D, Lin F-M, Wu W-Y et al (2011) miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic Acids Res 39:D163–D169

    Article  CAS  PubMed  Google Scholar 

  59. Chou C-H, Shrestha S, Yang C-D et al (2018) miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res 46(D1):D296–D302

    Article  CAS  PubMed  Google Scholar 

  60. Li J, Millar AA (2013) Expression of a microRNA-resistant target transgene misrepresents the functional significance of the endogenous microRNA: target gene relationship. Mol Plant 6:577–580

    Article  CAS  PubMed  Google Scholar 

  61. Ghosh Dastidar M, Mosiolek M, Bleckmann A et al (2016) Sensitive whole mount in situ localization of small RNAs in plants. Plant J 88:694–702

    Article  CAS  PubMed  Google Scholar 

  62. Bleckmann A, Dresselhaus T (2016) Fluorescent whole-mount RNA in situ hybridization (F-WISH) in plant germ cells and the fertilized ovule. Methods 98:66–73

    Article  CAS  PubMed  Google Scholar 

  63. Franco-Zorrilla JM, Valli A, Todesco M et al (2007) Target mimicry provides a new mechanism for regulation of microRNA activity. Nat Genet 39:1033–1037

    Article  CAS  PubMed  Google Scholar 

  64. Todesco M, Rubio-Somoza I, Paz-Ares J, Weigel D (2010) A collection of target mimics for comprehensive analysis of microRNA function in Arabidopsis thaliana. PLoS Genet 6:e1001031

    Article  PubMed  PubMed Central  Google Scholar 

  65. Yan J, Gu Y, Jia X et al (2012) Effective small RNA destruction by the expression of a short tandem target mimic in Arabidopsis. Plant Cell 24:415–427

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Ramachandran V, Chen X (2008) Degradation of microRNAs by a family of exoribonucleases in Arabidopsis. Science 321:1490–1492

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Ebert MS, Neilson JR, Sharp PA (2007) MicroRNA sponges: competitive inhibitors of small RNAs in mammalian cells. Nat Meth 4:721–726

    Article  CAS  Google Scholar 

  68. Reichel M, Li Y, Li J, Millar AA (2015) Inhibiting plant microRNA activity: molecular SPONGEs, target MIMICs and STTMs all display variable efficacies against target microRNAs. Plant Biotechnol J 13:915–926

    Article  CAS  PubMed  Google Scholar 

  69. Alonso JM, Stepanova AN, Leisse TJ et al (2003) Genome-wide insertional mutagenesis of Arabidopsis thaliana. Science 301:653–657

    Article  PubMed  Google Scholar 

  70. Henikoff S, Till BJ, Comai L (2004) TILLING Traditional mutagenesis meets functional genomics. Plant Physiol 135:630–636

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Silva NVE, Patron NJ (2017) CRISPR-based tools for plant genome engineering. Emerg Topics Life Sci 1:ETLS20170011 149

    Google Scholar 

  72. Demirci Y, Zhang B, Unver T (2018) CRISPR/Cas9: an RNA-guided highly precise synthetic tool for plant genome editing. J Cell Physiol 233:1844–1859

    Article  CAS  PubMed  Google Scholar 

  73. Zhao Y, Zhang C, Liu W et al (2016) An alternative strategy for targeted gene replacement in plants using a dual-sgRNA/Cas9 design. Sci Rep 6:23890

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Zhou J, Deng K, Cheng Y et al (2017) CRISPR-Cas9 based genome editing reveals new insights into MicroRNA function and regulation in rice. Front Plant Sci 8:1598

    Article  PubMed  PubMed Central  Google Scholar 

  75. Wang Z-P, Xing H-L, Dong L et al (2015) Egg cell-specific promoter-controlled CRISPR/Cas9 efficiently generates homozygous mutants for multiple target genes in Arabidopsis in a single generation. Genome Biol 16:144

    Article  PubMed  PubMed Central  Google Scholar 

  76. Jacobs TB, LaFayette PR, Schmitz RJ, Parrott WA (2015) Targeted genome modifications in soybean with CRISPR/Cas9. BMC Biotechnol 15:16

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

Thanks to Cei Abreu-Goodger for comments on this manuscript. Research on miRNAs in the Gillmor laboratory is supported by grant CN-17-64 from the University of California Institute for Mexico and the United States (UC MEXUS) and the Consejo Nacional de Ciencia y Tecnología de México (CONACyT).

Author information

Authors and Affiliations

  1. Laboratorio Nacional de Genómica para la Biodiversidad (Langebio), Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato, Mexico

    Alma Armenta-Medina & C. Stewart Gillmor

Authors
  1. Alma Armenta-Medina
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. Stewart Gillmor
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. Stewart Gillmor .

Editor information

Editors and Affiliations

  1. Unidad de Genómica Avanzada, Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV-IPN), Irapuato, Guanajuato, Mexico

    Stefan de Folter

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

Armenta-Medina, A., Gillmor, C.S. (2019). An Introduction to Methods for Discovery and Functional Analysis of MicroRNAs in Plants. 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_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-9042-9_1

  • 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

Search

Navigation