Abstract
The introduction of Next-Generation Sequencing (NGS) technologies has opened new avenues, including determination of the relationship of genomic and epigenomic variation and phenotypes to disease. These technologies are particularly well suited for discovery of both small RNAs, around 30–75 base pairs long, and long RNAs, longer than 75 base pairs, because the NGS sequencers can produce millions of short reads in a relatively rapid period of time. However, the large amounts (terabases) of data generated require proper computational resources and analytical methods to translate the rich source of genomic data into meaningful information for biomedical applications. In this chapter, we describe various bioinformatics methods for performing integrative analysis for the identification of miRNAs and their target mRNAs from the NGS sequencers. We describe the most commonly used databases and prediction programs that are available on the World Wide Web and demonstrate the use of some of these programs by an example. We provide a list of these programs along with their Web URLs and suggest guidelines for successful application.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Sharp PA. RNAi and double-strand RNA. Genes Dev. 1999;13(2):139–41.
Golden DE, Gerbasi VR, Sontheimer EJ. An inside job for siRNAs. Mol Cell. 2008;31(3):309–12.
Moazed D. Small RNAs in transcriptional gene silencing and genome defence. Nature. 2009;457(7228):413–20.
Chapman EJ, Carrington JC. Specialization and evolution of endogenous small RNA pathways. Nat Rev Genet. 2007;8(11):884–96.
Nilsen TW. Endo-siRNAs: yet another layer of complexity in RNA silencing. Nat Struct Mol Biol. 2008;15(6):546–8.
Ghildiyal M, Zamore PD. Small silencing RNAs: an expanding universe. Nat Rev Genet. 2009;10(2):94–108.
Kim VN, Han J, Siomi MC. Biogenesis of small RNAs in animals. Nat Rev Mol Cell Biol. 2009;10(2):126–39.
Ambros V, Chen X. The regulation of genes and genomes by small RNAs. Development. 2007;134(9):1635–41.
Brodersen P, Voinnet O. Revisiting the principles of microRNA target recognition and mode of action. Nat Rev Mol Cell Biol. 2009;10(2):141–8.
Hussain MU. Micro-RNAs (miRNAs): genomic organisation, biogenesis and mode of action. Cell Tissue Res. 2012;349(2):405–13.
Kusenda B, et al. MicroRNA biogenesis, functionality and cancer relevance. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2006;150(2):205–15.
Faller M, Guo F. MicroRNA biogenesis: there’s more than one way to skin a cat. Biochim Biophys Acta. 2008;1779(11):663–7.
Gregory RI, Chendrimada TP, Shiekhattar R. MicroRNA biogenesis: isolation and characterization of the microprocessor complex. Methods Mol Biol. 2006;342:33–47.
Winter J, et al. Many roads to maturity: microRNA biogenesis pathways and their regulation. Nat Cell Biol. 2009;11(3):228–34.
Lim LP, et al. Vertebrate microRNA genes. Science. 2003;299(5612):1540.
Lynam-Lennon N, Maher SG, Reynolds JV. The roles of microRNA in cancer and apoptosis. Biol Rev Camb Philos Soc. 2009;84(1):55–71.
Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843–54.
Lodish HF, et al. Micromanagement of the immune system by microRNAs. Nat Rev Immunol. 2008;8(2):120–30.
Berardi E, et al. microRNAs in ES cell differentiation. Am J Physiol Heart Circ Physiol. 2012;303(8):H931–9.
Ebert MS, Sharp PA. Roles for microRNAs in conferring robustness to biological processes. Cell. 2012;149(3):515–24.
Osman A. MicroRNAs in health and disease—basic science and clinical applications. Clin Lab. 2012;58(5–6):393–402.
Garzon R, Calin GA, Croce CM. MicroRNAs in cancer. Annu Rev Med. 2009;60:167–79.
Farazi TA, et al. miRNAs in human cancer. J Pathol. 2011;223(2):102–15.
Nygaard S, et al. Identification and analysis of miRNAs in human breast cancer and teratoma samples using deep sequencing. BMC Med Genomics. 2009;2:35.
Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6(11):857–66.
Catto JW, et al. MicroRNA in prostate, bladder, and kidney cancer: a systematic review. Eur Urol. 2011;59(5):671–81.
Bartels CL, Tsongalis GJ. MicroRNAs: novel biomarkers for human cancer. Clin Chem. 2009;55(4):623–31.
Cortez MA, et al. MicroRNAs in body fluids—the mix of hormones and biomarkers. Nat Rev Clin Oncol. 2011;8(8):467–77.
Iorio MV, Croce CM. MicroRNA dysregulation in cancer: diagnostics, monitoring and therapeutics. A comprehensive review. EMBO Mol Med. 2012;4(3):143–59.
Mardis ER. The impact of next-generation sequencing technology on genetics. Trends Genet. 2008;24(3):133–41.
Friedlander MR, et al. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 2012;40(1):37–52.
Pantano L, Estivill X, Marti E. SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells. Nucleic Acids Res. 2010;38(5):e34.
Hackenberg M, et al. miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res. 2009;37(Web Server issue):W68–76.
Zhu E, et al. mirTools: microRNA profiling and discovery based on high-throughput sequencing. Nucleic Acids Res. 2010;38(Web Server issue):W392–7.
Zhang Y, et al. CPSS: a computational platform for the analysis of small RNA deep sequencing data. Bioinformatics. 2012;28(14):1925–7.
Ronen R, et al. miRNAkey: a software for microRNA deep sequencing analysis. Bioinformatics. 2010;26(20):2615–6.
Maragkakis M, et al. DIANA-microT web server: elucidating microRNA functions through target prediction. Nucleic Acids Res. 2009;37(Web Server issue):W273–6.
Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005;120(1):15–20.
Lewis BP, et al. Prediction of mammalian microRNA targets. Cell. 2003;115(7):787–98.
Rehmsmeier M, et al. Fast and effective prediction of microRNA/target duplexes. RNA. 2004;10(10):1507–17.
Kertesz M, et al. The role of site accessibility in microRNA target recognition. Nat Genet. 2007;39(10):1278–84.
Robins H, Li Y, Padgett RW. Incorporating structure to predict microRNA targets. Proc Natl Acad Sci U S A. 2005;102(11):4006–9.
Long D, et al. Potent effect of target structure on microRNA function. Nat Struct Mol Biol. 2007;14(4):287–94.
Muckstein U, et al. Thermodynamics of RNA-RNA binding. Bioinformatics. 2006;22(10):1177–82.
Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33.
Alon S, et al. Systematic identification of edited microRNAs in the human brain. Genome Res. 2012;22(8):1533–40.
Bass BL. RNA editing by adenosine deaminases that act on RNA. Annu Rev Biochem. 2002;71:817–46.
Ekdahl Y, et al. A-to-I editing of microRNAs in the mammalian brain increases during development. Genome Res. 2012;22(8):1477–87.
Reinhart BJ, et al. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature. 2000;403(6772):901–6.
Ambros V, Lee RC. Identification of microRNAs and other tiny noncoding RNAs by cDNA cloning. Methods Mol Biol. 2004;265:131–58.
Xu G, et al. Cloning and identification of microRNAs in bovine alveolar macrophages. Mol Cell Biochem. 2009;332(1–2):9–16.
Long JE, Chen HX. Identification and characteristics of cattle microRNAs by homology searching and small RNA cloning. Biochem Genet. 2009;47(5–6):329–43.
He X, et al. Cloning and identification of novel microRNAs from rat hippocampus. Acta Biochim Biophys Sin (Shanghai). 2007;39(9):708–14.
Pfeffer S, et al. Identification of virus-encoded microRNAs. Science. 2004;304(5671):734–6.
Lagos-Quintana M, et al. Identification of tissue-specific microRNAs from mouse. Curr Biol. 2002;12(9):735–9.
Bentwich I, et al. Identification of hundreds of conserved and nonconserved human microRNAs. Nat Genet. 2005;37(7):766–70.
Morin RD, et al. Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. Genome Res. 2008;18(4):610–21.
Glazov EA, et al. A microRNA catalog of the developing chicken embryo identified by a deep sequencing approach. Genome Res. 2008;18(6):957–64.
Creighton CJ, Reid JG, Gunaratne PH. Expression profiling of microRNAs by deep sequencing. Brief Bioinform. 2009;10(5):490–7.
Babiarz JE, et al. Mouse ES cells express endogenous shRNAs, siRNAs, and other microprocessor-independent, dicer-dependent small RNAs. Genes Dev. 2008;22(20):2773–85.
Lim LP, et al. The microRNAs of Caenorhabditis elegans. Genes Dev. 2003;17(8):991–1008.
Hofacker IL. Vienna RNA secondary structure server. Nucleic Acids Res. 2003;31(13):3429–31.
Lai EC, et al. Computational identification of Drosophila microRNA genes. Genome Biol. 2003;4(7):R42.
Hertel J, Stadler PF. Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data. Bioinformatics. 2006;22(14):e197–202.
Terai G, et al. miRRim: a novel system to find conserved miRNAs with high sensitivity and specificity. RNA. 2007;13(12):2081–90.
Siepel A, et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005;15(8):1034–50.
Berezikov E, et al. Phylogenetic shadowing and computational identification of human microRNA genes. Cell. 2005;120(1):21–4.
Boffelli D, et al. Phylogenetic shadowing of primate sequences to find functional regions of the human genome. Science. 2003;299(5611):1391–4.
Li H, Homer N. A survey of sequence alignment algorithms for next-generation sequencing. Brief Bioinform. 2010;11(5):473–83.
Langmead B, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):R25.
Dohm JC, et al. Substantial biases in ultra-short read data sets from high-throughput DNA sequencing. Nucleic Acids Res. 2008;36(16):e105.
Linsen SE, et al. Limitations and possibilities of small RNA digital gene expression profiling. Nat Methods. 2009;6(7):474–6.
Friedlander MR, et al. Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol. 2008;26(4):407–15.
Cloonan N, et al. MicroRNAs and their isomiRs function cooperatively to target common biological pathways. Genome Biol. 2011;12(12):R126.
Ryan BM, Robles AI, Harris CC. Genetic variation in microRNA networks: the implications for cancer research. Nat Rev Cancer. 2010;10(6):389–402.
Fernandez-Valverde SL, Taft RJ, Mattick JS. Dynamic isomiR regulation in Drosophila development. RNA. 2010;16(10):1881–8.
Zhou H, et al. Deep annotation of mouse iso-miR and iso-moR variation. Nucleic Acids Res. 2012;40(13):5864–75.
Li SC, et al. miRNA arm selection and isomiR distribution in gastric cancer. BMC Genomics. 2012;13 Suppl 1:S13.
Li R, et al. SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics. 2009;25(15):1966–7.
Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011;39(Database issue):D152–7.
Griffiths-Jones S, et al. Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 2005;33(Database issue):D121–4.
Tarailo-Graovac M, Chen N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinformatics. 2009;Chapter 4:Unit 4 10.
Hackenberg M, Matthiesen R. Annotation-Modules: a tool for finding significant combinations of multisource annotations for gene lists. Bioinformatics. 2008;24(11):1386–93.
Pasaniuc B, Zaitlen N, Halperin E. Accurate estimation of expression levels of homologous genes in RNA-seq experiments. J Comput Biol. 2011;18(3):459–68.
Moxon S, et al. A toolkit for analysing large-scale plant small RNA datasets. Bioinformatics. 2008;24(19):2252–3.
Thomson DW, Bracken CP, Goodall GJ. Experimental strategies for microRNA target identification. Nucleic Acids Res. 2011;39(16):6845–53.
Krek A, et al. Combinatorial microRNA target predictions. Nat Genet. 2005;37(5):495–500.
Marin RM, Vanicek J. Efficient use of accessibility in microRNA target prediction. Nucleic Acids Res. 2011;39(1):19–29.
Marin RM, Vanicek J. Optimal use of conservation and accessibility filters in microRNA target prediction. PLoS One. 2012;7(2):e32208.
John B, et al. Human MicroRNA targets. PLoS Biol. 2004;2(11):e363.
Betel D, et al. The microRNA.org resource: targets and expression. Nucleic Acids Res. 2008;36(Database issue):D149–53.
Maragkakis M, et al. Accurate microRNA target prediction correlates with protein repression levels. BMC Bioinformatics. 2009;10:295.
Kruger J, Rehmsmeier M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 2006;34(Web Server issue):W451–4.
Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 2003;31(13):3406–15.
Zuker M, Stiegler P. Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res. 1981;9(1):133–48.
Miranda KC, et al. A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell. 2006;126(6):1203–17.
Wiese KC, Hendriks A. Comparison of P-RnaPredict and mfold—algorithms for RNA secondary structure prediction. Bioinformatics. 2006;22(8):934–42.
Reczko M, et al. Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data. Front Genet. 2011;2:103.
Blow M, et al. A survey of RNA editing in human brain. Genome Res. 2004;14(12):2379–87.
Sommer B, et al. RNA editing in brain controls a determinant of ion flow in glutamate-gated channels. Cell. 1991;67(1):11–9.
Paz-Yaacov N, et al. Adenosine-to-inosine RNA editing shapes transcriptome diversity in primates. Proc Natl Acad Sci U S A. 2010;107(27):12174–9.
Farajollahi S, Maas S. Molecular diversity through RNA editing: a balancing act. Trends Genet. 2010;26(5):221–30.
Nishikura K. Functions and regulation of RNA editing by ADAR deaminases. Annu Rev Biochem. 2010;79:321–49.
Warf MB, et al. Effects of ADARs on small RNA processing pathways in C. elegans. Genome Res. 2012;22(8):1488–98.
Lai EC. microRNAs: runts of the genome assert themselves. Curr Biol. 2003;13(23):R925–36.
Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004;116(2):281–97.
Lee Y, et al. The nuclear RNase III Drosha initiates microRNA processing. Nature. 2003;425(6956):415–9.
Bernstein E, et al. Role for a bidentate ribonuclease in the initiation step of RNA interference. Nature. 2001;409(6818):363–6.
Luciano DJ, et al. RNA editing of a miRNA precursor. RNA. 2004;10(8):1174–7.
Sharma PM, et al. RNA editing in the Wilms’ tumor susceptibility gene, WT1. Genes Dev. 1994;8(6):720–31.
Kawahara Y, et al. Redirection of silencing targets by adenosine-to-inosine editing of miRNAs. Science. 2007;315(5815):1137–40.
Kawahara Y, et al. Frequency and fate of microRNA editing in human brain. Nucleic Acids Res. 2008;36(16):5270–80.
Habig JW, Dale T, Bass BL. miRNA editing—we should have inosine this coming. Mol Cell. 2007;25(6):792–3.
Chiang HR, et al. Mammalian microRNAs: experimental evaluation of novel and previously annotated genes. Genes Dev. 2010;24(10):992–1009.
Vesely C, et al. Adenosine deaminases that act on RNA induce reproducible changes in abundance and sequence of embryonic miRNAs. Genome Res. 2012;22(8):1468–76.
Burroughs AM, et al. A comprehensive survey of 3′ animal miRNA modification events and a possible role for 3′ adenylation in modulating miRNA targeting effectiveness. Genome Res. 2010;20(10):1398–410.
de Hoon MJ, et al. Cross-mapping and the identification of editing sites in mature microRNAs in high-throughput sequencing libraries. Genome Res. 2010;20(2):257–64.
Griffiths-Jones S. The microRNA registry. Nucleic Acids Res. 2004;32(Database issue):D109–11.
Barrett T, et al. NCBI GEO: archive for functional genomics data sets—10 years on. Nucleic Acids Res. 2011;39(Database issue):D1005–10.
Wang X. miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA. 2008;14(6):1012–7.
Wang X, El Naqa IM. Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics. 2008;24(3):325–32.
Piriyapongsa J, et al. microPIR: an integrated database of microRNA target sites within human promoter sequences. PLoS One. 2012;7(3):e33888.
Younger ST, Corey DR. Transcriptional gene silencing in mammalian cells by miRNA mimics that target gene promoters. Nucleic Acids Res. 2011;39(13):5682–91.
Hsu SD, et al. miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic Acids Res. 2011;39(Database issue):D163–9.
Vergoulis T, et al. TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res. 2012;40(Database issue):D222–9.
Xiao F, et al. miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res. 2009;37(Database issue):D105–10.
Jiang Q, et al. miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res. 2009;37(Database issue):D98–104.
Kaya KD, et al. mESAdb: microRNA expression and sequence analysis database. Nucleic Acids Res. 2011;39(Database issue):D170–80.
Kanehisa M, et al. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 2012;40(Database issue):D109–14.
Ashburner M, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25(1):25–9.
Yu W, et al. A navigator for human genome epidemiology. Nat Genet. 2008;40(2):124–5.
Nicoloso MS, et al. Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility. Cancer Res. 2010;70(7):2789–98.
Bruno AE, et al. miRdSNP: a database of disease-associated SNPs and microRNA target sites on 3′UTRs of human genes. BMC Genomics. 2012;13:44.
Lekprasert P, Mayhew M, Ohler U. Assessing the utility of thermodynamic features for microRNA target prediction under relaxed seed and no conservation requirements. PLoS One. 2011;6(6):e20622.
Dweep H, et al. miRWalk—database: prediction of possible miRNA binding sites by “walking” the genes of three genomes. J Biomed Inform. 2011;44(5):839–47.
Yang JH, et al. starBase: a database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data. Nucleic Acids Res. 2011;39(Database issue):D202–9.
Hiard S, et al. Patrocles: a database of polymorphic miRNA-mediated gene regulation in vertebrates. Nucleic Acids Res. 2010;38(Database issue):D640–51.
Olejniczak M, et al. RNAimmuno: a database of the nonspecific immunological effects of RNA interference and microRNA reagents. RNA. 2012;18(5):930–5.
Gennarino VA, et al. HOCTAR database: a unique resource for microRNA target prediction. Gene. 2011;480(1–2):51–8.
Cho S, et al. miRGator v2.0: an integrated system for functional investigation of microRNAs. Nucleic Acids Res. 2011;39(Database issue):D158–62.
Lu TP, et al. miRSystem: an integrated system for characterizing enriched functions and pathways of MicroRNA targets. PLoS One. 2012;7(8):e42390.
Plaisier CL, Bare JC, Baliga NS. miRvestigator: web application to identify miRNAs responsible for co-regulated gene expression patterns discovered through transcriptome profiling. Nucleic Acids Res. 2011;39(Web Server issue):W125–31.
Ruepp A, Kowarsch A, Theis F. PhenomiR: microRNAs in human diseases and biological processes. Methods Mol Biol. 2012;822:249–60.
Ziebarth JD, et al. PolymiRTS database 2.0: linking polymorphisms in microRNA target sites with human diseases and complex traits. Nucleic Acids Res. 2012;40(Database issue):D216–21.
Szczesniak MW, et al. miRNEST database: an integrative approach in microRNA search and annotation. Nucleic Acids Res. 2012;40(Database issue):D198–204.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Gupta, R., Davuluri, R.V. (2014). Bioinformatics Approaches to the Study of MicroRNAs. In: Fabbri, M. (eds) Non-coding RNAs and Cancer. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8444-8_9
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8444-8_9
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8443-1
Online ISBN: 978-1-4614-8444-8
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)