Systematic characterization of small RNAome during zebrafish early developmental stages

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• 作者：Yuangen Yao (4)
  Lili Ma (4)
  Qiong Jia (4)
  Wankun Deng (4)
  Zexian Liu (4)
  Yuanwei Zhang (4)
  Jian Ren (4)
  Yu Xue (4)
  Haibo Jia (4)
  Qing Yang (4)
  
• 关键词：Deep sequencing ; miRNA ; piRNA ; Zebrafish ; Embryonic development
• 刊名：BMC Genomics
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：15
• 期：1
• 全文大小：1,939 KB
• 参考文献：1. Moazed D: Small RNAs in transcriptional gene silencing and genome defence. / Nature 2009,457(7228):413鈥?20. CrossRef
  2. Stefani G, Slack FJ: Small non-coding RNAs in animal development. / Nat Rev Mol Cell Biol 2008,9(3):219鈥?30. CrossRef
  3. Pauli A, Rinn JL, Schier AF: Non-coding RNAs as regulators of embryogenesis. / Nat Rev Genet 2011,12(2):136鈥?49. CrossRef
  4. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. / Cell 2004,116(2):281鈥?97. CrossRef
  5. Houwing S, Kamminga LM, Berezikov E, Cronembold D, Girard A, van den Elst H, Filippov DV, Blaser H, Raz E, Moens CB, / et al.: A role for Piwi and piRNAs in germ cell maintenance and transposon silencing in zebrafish. / Cell 2007,129(1):69鈥?2. CrossRef
  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鈥?0. CrossRef
  7. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, / et al.: MicroRNA expression profiles classify human cancers. / Nature 2005,435(7043):834鈥?38. CrossRef
  8. Malone CD, Brennecke J, Dus M, Stark A, McCombie WR, Sachidanandam R, Hannon GJ: Specialized piRNA pathways act in germline and somatic tissues of the Drosophila ovary. / Cell 2009,137(3):522鈥?35. CrossRef
  9. Brennecke J, Aravin AA, Stark A, Dus M, Kellis M, Sachidanandam R, Hannon GJ: Discrete small RNA-generating loci as master regulators of transposon activity in Drosophila. / Cell 2007,128(6):1089鈥?103. CrossRef
  10. Aravin AA, Hannon GJ, Brennecke J: The Piwi-piRNA pathway provides an adaptive defense in the transposon arms race. / Science 2007,318(5851):761鈥?64. CrossRef
  11. Suh N, Blelloch R: Small RNAs in early mammalian development: from gametes to gastrulation. / Development 2011,138(9):1653鈥?661. CrossRef
  12. Ohnishi Y, Totoki Y, Toyoda A, Watanabe T, Yamamoto Y, Tokunaga K, Sakaki Y, Sasaki H, Hohjoh H: Small RNA class transition from siRNA/piRNA to miRNA during pre-implantation mouse development. / Nucleic Acids Res 2010,38(15):5141鈥?151. CrossRef
  13. Shao P, Liao JY, Guan DG, Yang JH, Zheng LL, Jing Q, Zhou H, Qu LH: Drastic expression change of transposon-derived piRNA-like RNAs and microRNAs in early stages of chicken embryos implies a role in gastrulation. / RNA Biol 2012,9(2):212鈥?27. CrossRef
  14. Song JL, Stoeckius M, Maaskola J, Friedlander M, Stepicheva N, Juliano C, Lebedeva S, Thompson W, Rajewsky N, Wessel GM: Select microRNAs are essential for early development in the sea urchin. / Dev Biol 2012,362(1):104鈥?13. CrossRef
  15. Kimmel CB, Ballard WW, Kimmel SR, Ullmann B, Schilling TF: Stages of embryonic development of the zebrafish. / Dev Dyn 1995,203(3):253鈥?10. CrossRef
  16. Chen PY, Manninga H, Slanchev K, Chien M, Russo JJ, Ju J, Sheridan R, John B, Marks DS, Gaidatzis D, / et al.: The developmental miRNA profiles of zebrafish as determined by small RNA cloning. / Genes Dev 2005,19(11):1288鈥?293. CrossRef
  17. Wienholds E, Kloosterman WP, Miska E, Alvarez-Saavedra E, Berezikov E, de Bruijn E, Horvitz HR, Kauppinen S, Plasterk RH: MicroRNA expression in zebrafish embryonic development. / Science 2005,309(5732):310鈥?11. CrossRef
  18. Giraldez AJ, Mishima Y, Rihel J, Grocock RJ, Van Dongen S, Inoue K, Enright AJ, Schier AF: Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs. / Science 2006,312(5770):75鈥?9. CrossRef
  19. Wei C, Salichos L, Wittgrove CM, Rokas A, Patton JG: Transcriptome-wide analysis of small RNA expression in early zebrafish development. / RNA 2012,18(5):915鈥?29. CrossRef
  20. Wang Z, Gerstein M, Snyder M: RNA-Seq: a revolutionary tool for transcriptomics. / Nat Rev Genet 2009,10(1):57鈥?3. CrossRef
  21. Xue C, Li F, He T, Liu GP, Li Y, Zhang X: Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. / BMC Bioinformatics 2005, 6:310. CrossRef
  22. Jiang P, Wu H, Wang W, Ma W, Sun X, Lu Z: MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. / Nucleic Acids Res 2007,35(Web Server issue):W339-W344. CrossRef
  23. Lertampaiporn S, Thammarongtham C, Nukoolkit C, Kaewkamnerdpong B, Ruengjitchatchawalya M: Heterogeneous ensemble approach with discriminative features and modified-SMOTEbagging for pre-miRNA classification. / Nucleic Acids Res 2013,41(1):e21. CrossRef
  24. Zhang Y, Yang Y, Zhang H, Jiang X, Xu B, Xue Y, Cao Y, Zhai Q, Zhai Y, Xu M, / et al.: Prediction of novel pre-microRNAs with high accuracy through boosting and SVM. / Bioinformatics 2011,27(10):1436鈥?437. CrossRef
  25. Friedlander 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(4):407鈥?15. CrossRef
  26. Hackenberg M, Sturm M, Langenberger D, Falcon-Perez JM, Aransay AM: miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. / Nucleic Acids Res 2009,37(Web Server issue):W68-W76. CrossRef
  27. 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(14):1925鈥?927. CrossRef
  28. Hofacker IL: Vienna RNA secondary structure server. / Nucleic Acids Res 2003,31(13):3429鈥?431. CrossRef
  29. Ding J, Zhou S, Guan J: MiRenSVM: towards better prediction of microRNA precursors using an ensemble SVM classifier with multi-loop features. / BMC Bioinformatics 2010,11(Suppl 11):S11. CrossRef
  30. Morin RD, O鈥機onnor MD, Griffith M, Kuchenbauer F, Delaney A, Prabhu AL, Zhao Y, McDonald H, Zeng T, Hirst M, / et al.: Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. / Genome Res 2008,18(4):610鈥?21. CrossRef
  31. 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(3):R25. CrossRef
  32. Friedlander 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(1):37鈥?2. CrossRef
  33. Zhang B, Stellwag EJ, Pan X: Large-scale genome analysis reveals unique features of microRNAs. / Gene 2009,443(1鈥?):100鈥?09. CrossRef
  34. Schier AF: The maternal-zygotic transition: death and birth of RNAs. / Science 2007,316(5823):406鈥?07. CrossRef
  35. Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. / Proc Natl Acad Sci U S A 1998,95(25):14863鈥?4868. CrossRef
  36. Lee SI, Lee BR, Hwang YS, Lee HC, Rengaraj D, Song G, Park TS, Han JY: MicroRNA-mediated posttranscriptional regulation is required for maintaining undifferentiated properties of blastoderm and primordial germ cells in chickens. / Proc Natl Acad Sci U S A 2011,108(26):10426鈥?0431. CrossRef
  37. Berenguer J, Herrera A, Vuolo L, Torroba B, Llorens F, Sumoy L, Pons S: MicroRNA 22 regulates cell cycle length in cerebellar granular neuron precursors. / Mol Cell Biol 2013,33(14):2706鈥?717. CrossRef
  38. Stahlhut C, Suarez Y, Lu J, Mishima Y, Giraldez AJ: miR-1 and miR-206 regulate angiogenesis by modulating VegfA expression in zebrafish. / Development 2012,139(23):4356鈥?364. CrossRef
  39. Wu TH, Pan CY, Lin MC, Hsieh JC, Hui CF, Chen JY: In vivo screening of zebrafish microRNA responses to bacterial infection and their possible roles in regulating immune response genes after lipopolysaccharide stimulation. / Fish Physiol Biochem 2012,38(5):1299鈥?310. CrossRef
  40. Chen X, Li Q, Wang J, Guo X, Jiang X, Ren Z, Weng C, Sun G, Wang X, Liu Y, / et al.: Identification and characterization of novel amphioxus microRNAs by Solexa sequencing. / Genome Biol 2009,10(7):R78. CrossRef
  41. Sai Lakshmi S, Agrawal S: piRNABank: a web resource on classified and clustered Piwi-interacting RNAs. / Nucleic Acids Res 2008,36(Database issue):D173-D177.
  42. Crooks GE, Hon G, Chandonia JM, Brenner SE: WebLogo: a sequence logo generator. / Genome Res 2004,14(6):1188鈥?190. CrossRef
  43. Fujita PA, Rhead B, Zweig AS, Hinrichs AS, Karolchik D, Cline MS, Goldman M, Barber GP, Clawson H, Coelho A, / et al.: The UCSC genome browser database: update 2011. / Nucleic Acids Res 2011,39(Database issue):D876-D882. CrossRef
  44. Kozomara A, Griffiths-Jones S: miRBase: integrating microRNA annotation and deep-sequencing data. / Nucleic Acids Res 2011,39(Database issue):D152-D157. CrossRef
  45. Burge SW, Daub J, Eberhardt R, Tate J, Barquist L, Nawrocki EP, Eddy SR, Gardner PP, Bateman A: Rfam 11.0: 10 years of RNA families. / Nucleic Acids Res 2013,41(Database issue):D226-D232. CrossRef
  46. Batuwita R, Palade V: microPred: effective classification of pre-miRNAs for human miRNA gene prediction. / Bioinformatics 2009,25(8):989鈥?95. CrossRef
  47. Xue Y, Liu Z, Gao X, Jin C, Wen L, Yao X, Ren J: GPS-SNO: computational prediction of protein S-nitrosylation sites with a modified GPS algorithm. / PloS one 2010,5(6):e11290. CrossRef
  48. Arata N, Nakayasu H: A periaxonal net in the zebrafish central nervous system. / Brain Res 2003,961(2):179鈥?89. CrossRef
  
• 作者单位：Yuangen Yao (4)
  Lili Ma (4)
  Qiong Jia (4)
  Wankun Deng (4)
  Zexian Liu (4)
  Yuanwei Zhang (4)
  Jian Ren (4)
  Yu Xue (4)
  Haibo Jia (4)
  Qing Yang (4)
  
  4. State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, 510275, China
  
• ISSN：1471-2164

文摘

Background During early vertebrate development, various small non-coding RNAs (sRNAs) such as MicroRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs) are dynamically expressed for orchestrating the maternal-to-zygotic transition (MZT). Systematic analysis of expression profiles of zebrafish small RNAome will be greatly helpful for understanding the sRNA regulation during embryonic development. Results We first determined the expression profiles of sRNAs during eight distinct stages of early zebrafish development by sRNA-seq technology. Integrative analyses with a new computational platform of CSZ (characterization of small RNAome for zebrafish) demonstrated an sRNA class transition from piRNAs to miRNAs as development proceeds. We observed that both the abundance and diversity of miRNAs are gradually increased, while the abundance is enhanced more dramatically than the diversity during development. However, although both the abundance and diversity of piRNAs are gradually decreased, the diversity was firstly increased then rapidly decreased. To evaluate the computational accuracy, the expression levels of four known miRNAs were experimentally validated. We also predicted 25 potentially novel miRNAs, whereas two candidates were verified by Northern blots. Conclusions Taken together, our analyses revealed the piRNA to miRNA transition as a conserved mechanism in zebrafish, although two different types of sRNAs exhibit distinct expression dynamics in abundance and diversity, respectively. Our study not only generated a better understanding for sRNA regulations in early zebrafish development, but also provided a useful platform for analyzing sRNA-seq data. The CSZ was implemented in Perl and freely downloadable at: http://csz.biocuckoo.org.