miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

详细信息    查看全文

• 作者：Fuliang Xie (1)
  Peng Xiao (2)
  Dongliang Chen (1)
  Lei Xu (1)
  Baohong Zhang (1) zhangb@ecu.edu
• 关键词：microRNA – ; miRDeepFinder – ; Deep sequencing – ; Target – ; Pathway analysis
• 刊名：Plant Molecular Biology
• 出版年：2012
• 出版时间：September 2012
• 年：2012
• 卷：80
• 期：1
• 页码：75-84
• 全文大小：340.8 KB
• 参考文献：1. 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
  2. Ambros V (2004) The functions of animal microRNAs. Nature 431:350–355
  3. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29
  4. 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
  5. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297
  6. Bonnet E, Wuyts J, Rouze P, Van de Peer Y (2004) Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativa identifies important target genes. Proc Natl Acad Sci USA 101:11511–11516
  7. 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
  8. Chen X (2008) MicroRNA metabolism in plants. Curr Top Microbiol Immunol 320:117–136
  9. Chen C, Ridzon DA, Broomer AJ, Zhou Z, Lee DH, Nguyen JT, Barbisin M, Xu NL, Mahuvakar VR, Andersen MR, Lao KQ, Livak KJ, Guegler KJ (2005) Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33:e179
  10. Ender C, Meister G (2010) Argonaute proteins at a glance. J Cell Sci 123:1819–1823
  11. Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM, Cumbie JS, Givan SA, Law TF, Grant SR, Dangl JL, Carrington JC (2007) High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PloS one 2:e219
  12. 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
  13. Fu H, Tie Y, Xu C, Zhang Z, Zhu J, Shi Y, Jiang H, Sun Z, Zheng X (2005) Identification of human fetal liver miRNAs by a novel method. FEBS Lett 579:3849–3854
  14. Fujii H, Chiou TJ, Lin SI, Aung K, Zhu JK (2005) A miRNA involved in phosphate-starvation response in Arabidopsis. Curr Biol 15:2038–2043
  15. Gardner PP, Daub J, Tate JG, Nawrocki EP, Kolbe DL, Lindgreen S, Wilkinson AC, Finn RD, Griffiths-Jones S, Eddy SR, Bateman A (2009) Rfam: updates to the RNA families database. Nucleic Acids Res 37:D136–D140
  16. Grad Y, Aach J, Hayes GD, Reinhart BJ, Church GM, Ruvkun G, Kim J (2003) Computational and experimental identification of C. elegans microRNAs. Mol Cell 11:1253–1263
  17. Griffiths-Jones S (2004) The microRNA registry. Nucleic Acids Res 32:D109–D111
  18. Guo HS, Xie Q, Fei JF, Chua NH (2005) MicroRNA directs mRNA cleavage of the transcription factor NAC1 to downregulate auxin signals for arabidopsis lateral root development. Plant Cell 17:1376–1386
  19. Hackenberg M, Sturm M, Langenberger D, Falcon-Perez JM, Aransay AM (2009) miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res 37:W68–W76
  20. Herr AJ (2005) Pathways through the small RNA world of plants. FEBS Lett 579:5879–5888
  21. Hofacker IL (2003) Vienna RNA secondary structure server. Nucleic Acids Res 31:3429–3431
  22. Hsieh LC, Lin SI, Shih AC, Chen JW, Lin WY, Tseng CY, Li WH, Chiou TJ (2009) Uncovering small RNA-mediated responses to phosphate deficiency in Arabidopsis by deep sequencing. Plant Physiol 151:2120–2132
  23. Huang PJ, Liu YC, Lee CC, Lin WC, Gan RR, Lyu PC, Tang P (2010) DSAP: deep-sequencing small RNA analysis pipeline. Nucleic Acids Res 38(Suppl):W385–W391
  24. Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27–30
  25. Kim VN (2005) MicroRNA biogenesis: coordinated cropping and dicing. Natl Rev Mol Cell Biol 6:376–385
  26. Lee RC, Feinbaum RL, Ambros V (1993) The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell 75:843–854
  27. 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
  28. 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 JK (2008) Criteria for annotation of plant MicroRNAs. Plant Cell 20:3186–3190
  29. Moxon S, Schwach F, Dalmay T, Maclean D, Studholme DJ, Moulton V (2008) A toolkit for analysing large-scale plant small RNA datasets. Bioinformatics 24:2252–2253
  30. Pfeffer S, Lagos-Quintana M, Tuschl T (2005) Cloning of small RNA molecules. Curr Protoc Mol Biol Chapter 26, Unit 26 24
  31. Pillai RS, Bhattacharyya SN, Filipowicz W (2007) Repression of protein synthesis by miRNAs: how many mechanisms? Trends Cell Biol 17:118–126
  32. 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
  33. Schwab R, Palatnik JF, Riester M, Schommer C, Schmid M, Weigel D (2005) Specific effects of microRNAs on the plant transcriptome. Dev Cell 8:517–527
  34. Smith TF, Waterman MS (1981) Identification of common molecular subsequences. J Mol Biol 147:195–197
  35. Sunkar R, Zhou X, Zheng Y, Zhang W, Zhu JK (2008) Identification of novel and candidate miRNAs in rice by high throughput sequencing. BMC Plant Biol 8:25
  36. Wang WC, Lin FM, Chang WC, Lin KY, Huang HD, Lin NS (2009) miRExpress: analyzing high-throughput sequencing data for profiling microRNA expression. BMC Bioinformatics 10:328
  37. Xie F, Zhang B (2010) Target-align: a tool for plant microRNA target identification. Bioinformatics 26:3002–3003
  38. Xie FL, Huang SQ, Guo K, Xiang AL, Zhu YY, Nie L, Yang ZM (2007) Computational identification of novel microRNAs and targets in Brassica napus. FEBS Lett 581:1464–1474
  39. Xie F, Frazier TP, Zhang B (2010) Identification and characterization of microRNAs and their targets in the bioenergy plant switchgrass (Panicum virgatum). Planta 232:417–434
  40. Xu J, Li CX, Li YS, Lv JY, Ma Y, Shao TT, Xu LD, Wang YY, Du L, Zhang YP, Jiang W, Li CQ, Xiao Y, Li X (2011) MiRNA–miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features. Nucleic Acids Res 39:825–836
  41. Zhang Y (2005) miRU: an automated plant miRNA target prediction server. Nucleic Acids Res 33:W701–W704
  42. Zhang B, Pan X, Cannon CH, Cobb GP, Anderson TA (2006) Conservation and divergence of plant microRNA genes. Plant J 46:243–259
  43. Zhang B, Pan X, Stellwag EJ (2008) Identification of soybean microRNAs and their targets. Planta 229:161–182
  44. Zhu E, Zhao F, Xu G, Hou H, Zhou L, Li X, Sun Z, Wu J (2010) mirTools: microRNA profiling and discovery based on high-throughput sequencing. Nucleic Acids Res 38(Suppl):W392–W397
  45. Zuker M, Stiegler P (1981) Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res 9:133–148
• 作者单位：1. Department of Biology, East Carolina University, Greenville, NC 27858, USA2. Department of Mathematics, East Carolina University, Greenville, NC 27858, USA
• ISSN：1573-5028

文摘

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, “miRNA primer designer” to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.