Scientia Agricultura Sinica ›› 2013, Vol. 46 ›› Issue (6): 1263-1271.doi: 10.3864/j.issn.0578-1752.2013.06.021

• ANIMAL SCIENCE·RESOURCE INSECT • Previous Articles     Next Articles

Upregulation and Expression of Bombyx mori bmo-miR-14 and Prediction of Its Target Genes

 LIU  Yue, YANG  Lan-Cui, NIE  Zuo-Ming, LU  Xuan, LU Zheng-Bing , CHEN  Jian, YU  Wei, WU  Xiang-Fu, ZHANG  Yao-Zhou   

  1. 1.Departmen of Applied Engineering, Zhejiang Economic & Trade Polytechnic, Hangzhou 310018;
    2.Institute of Biochemistry,  School of Life Science, Zhejiang Sci-Tech University, Hangzhou 310018
  • Received:2012-08-30 Online:2013-03-15 Published:2012-10-21

Abstract: 【Objective】The objective of this study is to offer a method for upregulating miRNA and predicting its targets in BmN cells, and to provide a methodological reference for studying the function of miRNAs in BmN cells. 【Method】An eukaryotic expression vector pSK-hr3-ie1-EGFP-pri-mir-14 for expressing Bombyx mori bmo-miR-14 was constructed and the miRNA gene was expressed in BmN cells. Additionally, the level of bmo-miR-14 in BmN cells was also up-regulated by transfecting chemically synthesized miRNA mimics. Firstly, the fragment containing pri-mir-14 was amplified by PCR and inserted into the downstream of EGFP of eukaryotic expression vector pSK-hr3-ie1-EGFP. The recombinant plasmid pSK-hr3-ie1-EGFP-pri-mir-14, control plasmid pSK-hr3-ie1-EGFP, bmo-miR-14 mimics and negative control mimics were transfected into BmN cells, respectively. The fluorescent light was observed and used to identify the efficiency of transfection. The miRNA levels in transfected BmN cells were identified by qRT-PCR. The RNAhybrid and miRanda were used to predict the targets of bmo-miR-14, respectively. 【Result】The miR-14 level was improved in BmN cells by transfecting with pSK-hr3-ie1-EGFP-pri-mir-14 and bmo-miR-14 mimics, and the level was improved as 2.1 and 984 times as the control, respectively. Further, the targeted genes of bmo-miR-14 were identified by bioinformatics tools and a total of 153 and 171 potential targeted genes were identified by RNAhybrid and miRanda software, respectively. In the predicted target genes, a total of 49 genes were predicted by RNAhybrid and miRanda together. The 49 targeted genes were assigned to GO terms of molecular function ontology, and binding and catalytic were overrepresented. In the biological process ontology, cellular process and metabolic process overrepresented among the 49 genes.【Conclusion】The approach to upregulate the level of bmo-miR-14 by transfecting with recombinant expression vector or miRNA mimics has laid a good foundation for the further studies on bmo-miR-14 in BmN cells.

Key words: Bombyx mori , bmo-miR-14 , upregulation , targeted genes , prediction

[1]陈青云, 王青青. microRNA对免疫系统发育和应答的调节作用. 浙江大学学报: 医学版, 2010, 39(3): 326-332.

Chen Q Y, Wang Q Q. Function of microRNAs in development of immune system and in regulation of immune response. Journal of Zhejiang University: Medical Sciences, 2010, 39(3): 326-332. (in Chinese)

[2]Ambros V. MicroRNAs与疾病和发育. 生命科学, 2010, 22(3): 229-231.

Ambros V. MicroRNA regulatory pathways in development and disease. Chinese Bulletin of Life Sciences, 2010, 22(3): 229-231. (in Chinese)

[3]吴家昌, 马琼, 邹贤飞, 杨彤涛, 单乐群, 马保安. miRNA与细胞分化的研究进展. 现代生物医学进展, 2010, 10(3): 567-572.

Wu J C, Ma Q, Zou X F, Yang T T, Shan L Q, Ma B A. Advance on microRNA and cell differentiation. Progress in Modern Biomedicine, 2010, 10(3): 567-572. (in Chinese)

[4]He P A, Nie Z M, Chen J Q, Chen J, Lü Z B, Sheng Q, Zhou S P, Gao X L, Kong L Y, Wu X F, Jin Y F, Zhang Y Z. Identification and characteristics of microRNAs from Bombyx mori. BMC Genomics, 2008, 9: 248.

[5]Cao J, Tong C Z, Wu X J, Lü J N, Yang Z L, Jin Y F. Identification of conserved microRNAs in Bombyx mori (silkworm) and regulation of fibroin L chain production by microRNAs in heterologous system. Insect Biochemistry and Molecular Biology, 2008, 38(12): 1066-1071.

[6]Yu X, Zhou Q, Li S C, Luo Q, Cai Y, Lin W, Chen H, Yang Y, Hu S, Yu J. The silkworm (Bombyx mori) microRNAs and their expressions in multiple developmental stages. PLoS ONE, 2008, 3(8): e2997.

[7]Liu S P, Xia Q Y, Zhao P, Cheng T C, Hong K L, Xiang Z H. Characterization and expression patterns of let-7 microRNA in the silkworm (Bombyx mori). BMC Developmental Biology, 2007, 7: 88.

[8]Zhang Y, Zhou X, Ge X, Jiang J H, Li M W, Jia S H, Yang X N, Kan Y C, Mian X X, Zhao G P, Li F, Huang Y P. Insect-specific microRNA involved in the development of the silkworm Bombyx mori. PLoS ONE, 2009, 4(3): e4677.

[9]Jagadeeswaran G, Zheng Y, Sumathipala N, Jiang H B, Arrese E L, Soulages J L, Zhang W X, Sunkar R. Deep sequencing of small RNA libraries reveals dynamic regulation of conserved and novel microRNAs and microRNA-stars during silkworm development. BMC Genomics, 2010, 11: 52.

[10]Xu P Z, Vernooy S Y, Guo M, Hay B A. The Drosophila microRNA mir-14 suppresses cell death and is required for normal fat metabolism. Current Biology, 2003, 13(9): 790-795.

[11]Varghese J, Cohen S M. microRNA miR-14 acts to modulate a positive autoregulatory loop controlling steroid hormone signaling in Drosophila. Genes & Development, 2007, 21(18): 2277-2282.

[12]Kumarswamy R, Chandna S. Inhibition of microRNA-14 contributes to actinomycin-D-induced apoptosis in the Sf9 insect cell line. Cell Biology International, 2010, 34(8): 851-857.

[13]Varghese J, Lim S F, Cohen S M. Drosophila miR-14 regulates insulin production and metabolism through its target, sugarbabe. Genes & Development, 2010, 24(24): 2748-2753.

[14]Friedman R C, Farh K K H, Burge C B, Bartel D P. Most mammalian mRNAs are conserved targets of microRNAs. Genome Resarch, 2009, 19(1): 92-105.

[15]Hong X, Hammell M, Ambros V, Cohen S M. Immunopurification of Ago1 miRNPs selects for a distinct class of microRNA targets. PNAS, 2009, 106(35): 15085-15090.

[16]Hu T, Chen P, Fu Q, Liu Y, Ishaq M, Li J W, Ma L, Guo D Y. Comparative studies of various artificial microRNA expression vectors for RNAi in mammalian cells. Molecular Biotechnology, 2010, 46(1): 34-40.

[17]Schmollinger S, Strenkert D, Schroda M. An inducible artificial microRNA system for Chlamydomonas reinhardtii confirms a key role for heat shock factor 1 in regulating thermotolerance. Current Genetics, 2010, 56(4): 383-389.

[18]Huang Y, Zou Q, Wang S P, Tang S M, Zhang G Z, Shen X J. Construction and detection of expression vectors of microRNA-9a in BmN cells. Journal of Zhejiang University-Science B: Biomedicine & Biotechnology, 2011, 12(7): 527-533.

[19]Chen C Z, Li L, Lodish H F, Bartel D P. MicroRNAs modulate hematopoietic lineage differentiation. Science, 2004, 303(5654): 83-86.

[20]Zhou H X, Xia X G, Xu Z S. An RNA polymerase II construct synthesizes short-hairpin RNA with a quantitative indicator and mediates highly efficient RNAi. Nucleic Acids Research, 2005, 33(6): e62.

[21]Chang K, Elledge S J, Hannon G J. Lessons from Nature: microRNA-based shRNA libraries. Nature Methods, 2006, 3(9): 707-714.

[22]Fukuda Y, Kawasaki H, Taira K. Construction of microRNA- containing vectors for expression in mammalian cells. Methods in Molecular Biology, 2006, 338: 167-173.
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