sRNAbench: profiling of small RNAs and its sequence variants in single or multi-species high-throughput experiments

Open access


MicroRNAs and other small RNAs are known to play important functions in gene regulation. Over the last years, it became also apparent that many virus genomes encode microRNAs and that those strongly interact with the host transcriptome. Important functions include the evasion of the immune response and the regulation of the switch to lytic infection. Since the advent of deep sequencing protocols for small RNAs, expression profiles can be routinely determined. However, currently the tools developed for the data analysis of small RNA deep sequencing experiments are limited to the analysis of only one species at a time. In order to facilitate the analysis of experimental setups that include genetic material from several species, we developed sRNAbench. It maintains the main features implemented in its predecessor program, miRanalyzer, and includes new functionalities such as full isomiR support including statistical test on differential frequency, improved prediction of novel microRNAs, extended summary files and data visualization support. Both a standalone program and a webserver are available at:

[1] Morin RD, O’Connor MD, Griffith M, Kuchenbauer F, Delaney A, Prabhu A-L, Zhao Y, McDonald H, Zeng T, Hirst M, Eaves CJ, Marra MA: Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. Genome Res 2008, 18:610–21.

[2] Finnegan EJ, Matzke MA: The small RNA world. J Cell Sci 2003, 116(Pt 23):4689–93.

[3] Grosshans H, Filipowicz W: Molecular biology: the expanding world of small RNAs. Nature 2008, 451:414–6.

[4] Axtell MJ: Classification and comparison of small RNAs from plants. Annu Rev Plant Biol 2013, 64:137–59.

[5] Tuck AC, Tollervey D: RNA in pieces. Trends Genet 2011, 27:422–32.

[6] Hall AE, Turnbull C, Dalmay T: Y RNAs: recent developments. Biomol Concepts 2013, 4:103–110.

[7] Neilsen CT, Goodall GJ, Bracken CP: IsomiRs--the overlooked repertoire in the dynamic microRNAome. Trends Genet 2012, 28:544–9.

[8] 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: MicroRNAs and their isomiRs function cooperatively to target common biological pathways. Genome Biol 2011, 12:R126.

[9] Burroughs AM, Ando Y, de Hoon MJL, Tomaru Y, Nishibu T, Ukekawa R, Funakoshi T, Kurokawa T, Suzuki H, Hayashizaki Y, Daub CO: A comprehensive survey of 3’ animal miRNA modification events and a possible role for 3’ adenylation in modulating miRNA targeting effectiveness. Genome Res 2010, 20:1398–410.

[10] Moxon S, Schwach F, Dalmay T, Maclean D, Studholme DJ, Moulton V: A toolkit for analysing large-scale plant small RNA datasets. Bioinformatics 2008, 24:2252–3.

[11] Friedländer MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N: Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol 2008, 26:407–15.

[12] Hackenberg M, Sturm M, Langenberger D, Falcón-Pérez JM, Aransay AM: miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res 2009, 37(Web Server issue):W68–76.

[13] Pantano L, Estivill X, Martí 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:e34.

[14] MacLean D, Moulton V, Studholme DJ: Finding sRNA generative locales from high-throughput sequencing data with NiBLS. BMC Bioinformatics 2010, 11:93.

[15] Hendrix D, Levine M, Shi W: miRTRAP, a computational method for the systematic identification of miRNAs from high throughput sequencing data. Genome Biol 2010, 11:R39.

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

[17] Hackenberg M, Rodríguez-Ezpeleta N, Aransay AM: miRanalyzer: an update on the detection and analysis of microRNAs in high-throughput sequencing experiments. Nucleic Acids Res 2011, 39(Web Server issue):W132–8.

[18] Fasold M, Langenberger D, Binder H, Stadler PF, Hoffmann S: DARIO: a ncRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res 2011, 39(Web Server issue):W112–7.

[19] Stocks MB, Moxon S, Mapleson D, Woolfenden HC, Mohorianu I, Folkes L, Schwach F, Dalmay T, Moulton V: The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets. Bioinformatics 2012, 28:2059–61.

[20] Hardcastle TJ, Kelly KA, Baulcombe DC: Identifying small interfering RNA loci from high-throughput sequencing data. Bioinformatics 2012, 28:457–63.

[21] Zhang Y, Xu B, Yang Y, Ban R, Zhang H, Jiang X, Cooke HJ, Xue Y, Shi Q: CPSS: a computational platform for the analysis of small RNA deep sequencing data. Bioinformatics 2012, 28:1925–7.

[22] Chen C-J, Servant N, Toedling J, Sarazin A, Marchais A, Duvernois-Berthet E, Cognat V, Colot V, Voinnet O, Heard E, Ciaudo C, Barillot E: ncPRO-seq: a tool for annotation and profiling of ncRNAs in sRNA-seq data. Bioinformatics 2012, 28:3147–9.

[23] Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N: miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 2012, 40:37–52.

[24] Axtell MJ: ShortStack: comprehensive annotation and quantification of small RNA genes. RNA 2013, 19:740–51.

[25] Sablok G, Milev I, Minkov G, Minkov I, Varotto C, Yahubyan G, Baev V: isomiRex: web-based identification of microRNAs, isomiR variations and differential expression using next-generation sequencing datasets. FEBS Lett 2013, 587:2629–34.

[26] An J, Lai J, Lehman ML, Nelson CC: miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data. Nucleic Acids Res 2013, 41:727–37.

[27] Wu J, Liu Q, Wang X, Zheng J, Wang T, You M, Sheng Sun Z, Shi Q: mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing. RNA Biol 2013, 10:1087–92.

[28] Katiyar-Agarwal S, Jin H: Role of small RNAs in host-microbe interactions. Annu Rev Phytopathol 2010, 48:225–46.

[29] Skalsky RL, Cullen BR: Viruses, microRNAs, and host interactions. Annu Rev Microbiol 2010, 64:123–41.

[30] Libri V, Miesen P, van Rij RP, Buck AH: Regulation of microRNA biogenesis and turnover by animals and their viruses. Cell Mol Life Sci 2013, 70:3525–44.

[31] Bernal D, Trelis M, Montaner S, Cantalapiedra F, Galiano A, Hackenberg M, Marcilla A: Surface analysis of Dicrocoelium dendriticum. The molecular characterization of exosomes reveals the presence of miRNAs. J Proteomics 2014.

[32] Hoy AM, Lundie RJ, Ivens A, Quintana JF, Nausch N, Forster T, Jones F, Kabatereine NB, Dunne DW, Mutapi F, Macdonald AS, Buck AH: Parasite-derived microRNAs in host serum as novel biomarkers of helminth infection. PLoS Negl Trop Dis 2014, 8:e2701.

[33] Langmead B, Trapnell C, Pop M, Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009, 10:R25.

[34] Kozomara A, Griffiths-Jones S: miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 2014, 42(Database issue):D68–73.

[35] Lorenz R, Bernhart SH, Höner Zu Siederdissen C, Tafer H, Flamm C, Stadler PF, Hofacker IL: ViennaRNA Package 2.0. Algorithms Mol Biol 2011, 6:26.

[36] Taub M, Lipson D, Speed TP: Methods for Allocating Ambiguous Short-reads. Commun Inf Syst 2010, 10:69–82.

[37] Roberts A, Pachter L: Streaming fragment assignment for real-time analysis of sequencing experiments. Nat Methods 2013, 10:71–3.

[38] D’Ambrogio A, Gu W, Udagawa T, Mello CC, Richter JD: Specific miRNA stabilization by Gld2-catalyzed monoadenylation. Cell Rep 2012, 2:1537–45.

[39] Hackenberg M, Shi B-J, Gustafson P, Langridge P: Characterization of phosphorus-regulated miR399 and miR827 and their isomirs in barley under phosphorus-sufficient and phosphorusdeficient conditions. BMC Plant Biol 2013, 13:214.

[40] Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, Cao X, Carrington JC, Chen X, Green PJ, Griffiths- Jones S, Jacobsen SE, Mallory AC, Martienssen RA, Poethig RS, Qi Y, Vaucheret H, Voinnet O, Watanabe Y, Weigel D, Zhu J-K: Criteria for annotation of plant MicroRNAs. Plant Cell 2008, 20:3186–90.

[41] Meng F, Hackenberg M, Li Z, Yan J, Chen T: Discovery of novel microRNAs in rat kidney using next generation sequencing and microarray validation. PLoS One 2012, 7:e34394.

[42] Kozomara A, Griffiths-Jones S: miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res 2011, 39(Database issue):D152–7.

[43] Robinson MD, McCarthy DJ, Smyth GK: edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26:139–40.

[44] Maza E, Frasse P, Senin P, Bouzayen M, Zouine M: Comparison of normalization methods for differential gene expression analysis in RNA-Seq experiments: A matter of relative size of studied transcriptomes. Commun Integr Biol 2013, 6:e25849.

[45] Dillies M-A, Rau A, Aubert J, Hennequet-Antier C, Jeanmougin M, Servant N, Keime C, Marot G, Castel D, Estelle J, Guernec G, Jagla B, Jouneau L, Laloë D, Le Gall C, Schaëffer B, Le Crom S, Guedj M, Jaffrézic F: A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis. Brief Bioinform 2013, 14:671–83.

[46] Pfeffer S, Zavolan M, Grässer FA, Chien M, Russo JJ, Ju J, John B, Enright AJ, Marks D, Sander C, Tuschl T: Identification of virusencoded microRNAs. Science 2004, 304:734–6.

[47] Cai X, Lu S, Zhang Z, Gonzalez CM, Damania B, Cullen BR: Kaposi’s sarcoma-associated herpesvirus expresses an array of viral microRNAs in latently infected cells. Proc Natl Acad Sci U S A 2005, 102:5570–5.

[48] Mayer KFX, Waugh R, Brown JWS, Schulman A, Langridge P, Platzer M, Fincher GB, Muehlbauer GJ, Sato K, Close TJ, Wise RP, Stein N: A physical, genetic and functional sequence assembly of the barley genome. Nature 2012, 491:711–6.

[49] Hackenberg M, Shi B-J, Gustafson P, Langridge P: A transgenic transcription factor (TaDREB3) in barley affects the expression of microRNAs and other small non-coding RNAs. PLoS One 2012, 7:e42030.

[50] Hackenberg M, Huang P-J, Huang C-Y, Shi B-J, Gustafson P, Langridge P: A comprehensive expression profile of microRNAs and other classes of non-coding small RNAs in barley under phosphorous-deficient and -sufficient conditions. DNA Res 2013, 20:109–25.

[51] Pruitt KD, Tatusova T, Brown GR, Maglott DR: NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy. Nucleic Acids Res 2012, 40(Database issue):D130–5.

[52] Flicek P, Amode MR, Barrell D, Beal K, Billis K, Brent S, Carvalho-Silva D, Clapham P, Coates G, Fitzgerald S, Gil L, Girón

Journal Information


All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 156 156 57
PDF Downloads 36 36 20