Applied Biochemistry and Biotechnology

, Volume 172, Issue 8, pp 3875–3887 | Cite as

Identification of MicroRNA Genes and their mRNA Targets in Festuca arundinacea

  • Xi Hong Sun
  • Ling Ping Zhao
  • Quan Zou
  • Zhan Bin WangEmail author


MicroRNAs (miRNAs) have emerged as a novel class of endogenous, small, non-coding RNAs of 22 nucleotides (nts) in length, which plays important roles in post-transcriptional degradation of target mRNA or inhibition of protein synthesis through binding the specific sites of target mRNA. Growing evidences have shown that miRNAs play an important role in various biological processes, including growth and development, signal transduction, apoptosis, proliferation, stress responses, maintenance of genome stability, and so on. In our study, we used bioinformatic tools to predict miRNA and the corresponding target genes of Festuca arundinacea. We used known miRNAs of other plants from miRBase to search against expressed sequence tags (EST) databases and genome survey sequences (GSS) of F. arundinacea. A total of 8 potential miRNAs were predicted. Phylogenetic analysis of the predicted miRNAs revealed that miRNA398c of F. arundinacea species was evolutionary highly conserved with Populus trichocarpa. The 8 potential miRNAs corresponding to 20 target genes were found. Most of the miRNA target genes were predicted to encode transcription factors that regulate cell growth and development, signaling, metabolism, and other biology processes. By bioinformatics methods, we can effectively predict novel miRNAs and its target genes and add information to F. arundinacea miRNA database. Moreover, it shows a path for the prediction and analysis of miRNAs to those species whose genomes are not available through bioinformatics tools.


miRNA Computational prediction Festuca arundinacea Target genes 



This research was supported by the National Natural Science Foundation of China (31302013, 61370010).

Supplementary material

12010_2014_805_MOESM1_ESM.doc (39 kb)
ESM 1 (DOC 39 kb)


  1. 1.
    Huang, Y., Shen, X. J., Zou, Q., Wang, S. P., Tang, S. M., & Zhang, G. Z. (2011). Biological functions of microRNAs: a review. Journal of Physiology and Biochemistry, 67(1), 129–139.CrossRefGoogle Scholar
  2. 2.
    Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 116(2), 281–297.CrossRefGoogle Scholar
  3. 3.
    Wu, G. (2013). Plant microRNAs and development. Journal of Genetics and Genomics, 40(5), 217–230.CrossRefGoogle Scholar
  4. 4.
    Tang, G., Yan, J., Gu, Y., Qiao, M., Fan, R., Mao, Y., et al. (2012). Construction of short tandem target mimic (STTM) to block the functions of plant and animal microRNAs. Methods, 58(2), 118–125.CrossRefGoogle Scholar
  5. 5.
    Merchan, F., Boualem, A., Crespi, M., & Frugier, F. (2009). Plant polycistronic precursors containing non-homologous microRNAs target transcripts encoding functionally related proteins. Genome Biology, 10, R136.CrossRefGoogle Scholar
  6. 6.
    Ren, G., Xie, M., Dou, Y., Zhang, S., Zhang, C., & Yu, B. (2012). Regulation of miRNA abundance by RNA binding protein TOUGH in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America, 109(31), 12817–12821.CrossRefGoogle Scholar
  7. 7.
    Szarzynska, B., Sobkowiak, L., Pant, B. D., Balazadeh, S., Scheible, W. R., Mueller-Roeber, B., et al. (2009). Gene structures and processing of Arabidopsis thaliana HYL1-dependent pri-miRNAs. Nucleic Acids Research, 37(9), 3083–3093.CrossRefGoogle Scholar
  8. 8.
    Meyers, B. C., Green, P. J., & Lu, C. (2008). miRNAs in the plant genome: all things great and small. Genome Dynamics, 4, 108–118.CrossRefGoogle Scholar
  9. 9.
    Sunkar, R., & Zhu, J. K. (2004). Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell, 16(8), 2001–2019.CrossRefGoogle Scholar
  10. 10.
    Martin, R. C., Liu, P. P., Goloviznina, N. A., & Nonogaki, H. (2010). microRNA, seeds, and Darwin?: diverse function of miRNA in seed biology and plant responses to stress. Journal of Experimental Botany, 61(9), 2229–2234.CrossRefGoogle Scholar
  11. 11.
    Sunkar, R., Li, Y. F., & Jagadeeswaran, G. (2012). Functions of microRNAs in plant stress responses. Trends in Plant Science, 17(4), 196–203.CrossRefGoogle Scholar
  12. 12.
    Zhang, H., & Li, L. (2013). SQUAMOSA promoter binding protein-like7 regulated microRNA408 is required for vegetative development in Arabidopsis. Plant Journal, 74(1), 98–109.CrossRefGoogle Scholar
  13. 13.
    Chen, X., Zhang, Z., Liu, D., Zhang, K., Li, A., & Mao, L. (2010). SQUAMOSA promoter-binding protein-like transcription factors: star players for plant growth and development. Journal of Integrative Plant Biology, 52(11), 946–951.CrossRefGoogle Scholar
  14. 14.
    Llave, C., Kasschau, K. D., Rector, M. A., & Carrington, J. C. (2002). Endogenous and silencing-associated small RNAs in plants. Plant Cell, 14(7), 1605–1619.CrossRefGoogle Scholar
  15. 15.
    Jones-Rhoades, M. W., & Bartel, D. P. (2004). Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Molecular Cell, 14(6), 787–799.CrossRefGoogle Scholar
  16. 16.
    Berezikov, E., Cuppen, E., & Plasterk, R. H. (2006). Approaches to microRNA discovery. Nature Genetics, 38(Suppl), S2–S7.CrossRefGoogle Scholar
  17. 17.
    Liu, Y. X., Chang, W., Han, Y. P., Zou, Q., Guo, M. Z., & Li, W. B. (2011). In silico detection of novel microRNAs genes in soybean genome. Agricultural Sciences in China, 10(9), 1336–1345.CrossRefGoogle Scholar
  18. 18.
    Zuo, J., Wang, Y., Liu, H., Ma, Y., Ju, Z., Zhai, B., et al. (2011). MicroRNAs in tomato plants. Science China Life Sciences, 54(7), 599–605.CrossRefGoogle Scholar
  19. 19.
    Qiu, D., Pan, X., Wilson, I. W., Li, F., Liu, M., Teng, W., et al. (2009). High throughput sequencing technology reveals that the taxoid elicitor methyl jasmonate regulates microRNA expression in Chinese yew (Taxus chinensis). Gene, 436(1–2), 37–44.CrossRefGoogle Scholar
  20. 20.
    Wu, Y., Du, J., Wang, X., Fang, X., Shan, W., & Liang, Z. (2012). Computational prediction and experimental verification of miRNAs in Panicum miliaceum L. Science China Life Sciences, 55(9), 807–817.CrossRefGoogle Scholar
  21. 21.
    Zhang, Y., Yu, M., Yu, H., Han, J., Song, C., Ma, R., et al. (2012). Computational identification of microRNAs in peach expressed sequence tags and validation of their precise sequences by miR-RACE. Molecular Biology Reports, 39(2), 1975–1987.CrossRefGoogle Scholar
  22. 22.
    Gebelin, V., Argout, X., Engchuan, W., Pitollat, B., Duan, C., Montoro, P., et al. (2012). Identification of novel microRNAs in Hevea brasiliensis and computational prediction of their targets. BMC Plant Biology, 12, 18.CrossRefGoogle Scholar
  23. 23.
    Xie, F. L., Huang, S. Q., Guo, K., Xiang, A. L., Zhu, Y. Y., Nie, L., et al. (2007). Computational identification of novel microRNAs and targets in Brassica napus. FEBS Letters, 581(7), 1464–1474.CrossRefGoogle Scholar
  24. 24.
    Dong, Q. H., Han, J., Yu, H. P., Wang, C., Zhao, M. Z., Liu, H., et al. (2012). Computational identification of MicroRNAs in strawberry expressed sequence tags and validation of their precise sequences by miR-RACE. Journal of Heredity, 103(2), 268–277.CrossRefGoogle Scholar
  25. 25.
    Han, Y., Luan, F., Zhu, H., Shao, Y., Chen, A., Lu, C., et al. (2009). Computational identification of microRNAs and their targets in wheat (Triticum aestivum L.). Science in China Series C, Life Sciences, 52(11), 1091–1100.CrossRefGoogle Scholar
  26. 26.
    Unver, T., Namuth-Covert, D. M., & Budak, H. (2009). Review of current methodological approaches for characterizing microRNAs in plants. International Journal of Plant Genomics, 2009(2009), 262463.Google Scholar
  27. 27.
    Wang, Z. Y., Scott, M., Bell, J., Hopkins, A., & Lehmann, D. (2003). Field performance of transgenic tall fescue (Festuca arundinacea Schreb.) plants and their progenies. Theoretical and Applied Genetics, 107(3), 406–412.CrossRefGoogle Scholar
  28. 28.
    Tennant, T., & Wu, L. (2000). Effects of water stress on selenium accumulation in tall fescue (Festuca arundinacea Schreb) from a selenium-contaminated soil. Archives of Environmental Contamination and Toxicology, 38(1), 32–39.CrossRefGoogle Scholar
  29. 29.
    Ge, Y., & Wang, Z. Y. (2006). Tall Fescue (Festuca arundinacea Schreb.). Methods in Molecular Biology, 344, 75–81.Google Scholar
  30. 30.
    Unver, T., Bakar, M., Shearman, R. C., & Budak, H. (2010). Genome-wide profiling and analysis of Festuca arundinacea miRNAs and transcriptomes in response to foliar glyphosate application. Molecular Genetics and Genomics, 283(4), 397–413.CrossRefGoogle Scholar
  31. 31.
    Altschul, S., Madden, T. L., Schaffer, A. A., Zhang, J., Zhang, Z., Miller, W., et al. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25, 3389–3402.CrossRefGoogle Scholar
  32. 32.
    Chen, C., Ridzon, D. A., Broomer, A. J., Zhou, Z., Lee, D. H., Nguyen, J. T., et al. (2005). Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Research, 33, e179.CrossRefGoogle Scholar
  33. 33.
    Tamura, K., Dudley, J., Nei, M., & Kumar, S. (2007). MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Molecular Biology and Evolution, 24(8), 1596–1599.CrossRefGoogle Scholar
  34. 34.
    Tamura, K., Nei, M., & Kumar, S. (2004). Prospects for inferring very large phylogenies by using the neighbor-joining method. Proceedings of the National Academy of Sciences of the United States of America, 101(30), 11030–11035.CrossRefGoogle Scholar
  35. 35.
    Thompson, J. D., Higgins, D. G., & Gibson, T. J. (1994). CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties, and weight matrix choice. Nucleic Acids Research, 22(22), 4673–4680.CrossRefGoogle Scholar
  36. 36.
    Zhang, B., Pan, X., Cannon, C. H., Cobb, G. P., & Anderson, T. A. (2006). Conservation and divergence of plant microRNA genes. Plant Journal, 46(2), 243–259.CrossRefGoogle Scholar
  37. 37.
    Zhang, B. H., Pan, X. P., Cox, S. B., Cobb, G. P., & Anderson, T. A. (2006). Evidence that miRNAs are different from other RNAs. Cellular and Molecular Life Sciences, 63(2), 246–254.CrossRefGoogle Scholar
  38. 38.
    Zhang, B., Pan, X., Cobb, G. P., & Anderson, T. A. (2006). Plant microRNA: a small regulatory molecule with big impact. Developmental Biology, 289(1), 3–16.CrossRefGoogle Scholar
  39. 39.
    Munoz-Merida, A., Perkins, J. R., Viguera, E., Thode, G., Bejarano, E. R., & Perez-Pulido, A. J. (2012). Semirna: searching for plant miRNAs using target sequences. OMICS, 16(4), 168–177.CrossRefGoogle Scholar
  40. 40.
    Lai, X., Schmitz, U., Gupta, S. K., Bhattacharya, A., Kunz, M., Wolkenhauer, O., et al. (2012). Computational analysis of target hub gene repression regulated by multiple and cooperative miRNAs. Nucleic Acids Research, 40(18), 8818–8834.CrossRefGoogle Scholar
  41. 41.
    Fujita, S., & Iba, H. (2008). Putative promoter regions of miRNA genes involved in evolutionarily conserved regulatory systems among vertebrates. Bioinformatics, 24(3), 303–308.CrossRefGoogle Scholar
  42. 42.
    Searle, I., & Coupland, G. (2004). Induction of flowering by seasonal changes in photoperiod. EMBO Journal, 23(6), 1217–1222.CrossRefGoogle Scholar
  43. 43.
    Ben-Naim, O., Eshed, R., Parnis, A., Teper-Bamnolker, P., Shalit, A., Coupland, G., et al. (2006). The CCAAT binding factor can mediate interactions between CONSTANS-like proteins and DNA. Plant Journal, 46(3), 462–476.CrossRefGoogle Scholar
  44. 44.
    Voinnet, O. (2005). Induction and suppression of RNA silencing: insights from viral infections. Nature Reviews Genetics, 6(3), 206–220.CrossRefGoogle Scholar
  45. 45.
    Yang, T. W., Xue, L. G., & An, L. Z. (2007). Functional diversity of miRNA in plants. Plant Science, 172(3), 423–432.CrossRefGoogle Scholar
  46. 46.
    Bazzini, A. A., Hopp, H. E., Beachy, R. N., & Asurmendi, S. (2007). Infection and coaccumulation of tobacco mosaic virus proteins alter microRNA levels, correlating with symptom and plant development. Proceedings of the National Academy of Sciences of the United States of America, 104(29), 12157–12162.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Xi Hong Sun
    • 1
  • Ling Ping Zhao
    • 1
  • Quan Zou
    • 2
  • Zhan Bin Wang
    • 1
    Email author
  1. 1.Animal Science and Technology CollegeHenan University of Science and TechnologyLuoyang CityPeople’s Republic of China
  2. 2.School of Information Science and Technology of Xiamen UniversityXiamen CityPeople’s Republic of China

Personalised recommendations