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基于生物信息学的hsa-miR-32靶基因预测与功能分析

彭璨璨 马文丽 夏巍 黄正亮 郑文岭

彭璨璨, 马文丽, 夏巍, 黄正亮, 郑文岭. 基于生物信息学的hsa-miR-32靶基因预测与功能分析[J]. 中华疾病控制杂志, 2016, 20(6): 609-613. doi: 10.16462/j.cnki.zhjbkz.2016.06.017
引用本文: 彭璨璨, 马文丽, 夏巍, 黄正亮, 郑文岭. 基于生物信息学的hsa-miR-32靶基因预测与功能分析[J]. 中华疾病控制杂志, 2016, 20(6): 609-613. doi: 10.16462/j.cnki.zhjbkz.2016.06.017
PENG Can-can, MA Wen-li, XIA Wei, HUANG Zheng-liang, ZHENG Wen-ling. Bioinformatics analysis and prediction of hsa-miR-32 target genes[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2016, 20(6): 609-613. doi: 10.16462/j.cnki.zhjbkz.2016.06.017
Citation: PENG Can-can, MA Wen-li, XIA Wei, HUANG Zheng-liang, ZHENG Wen-ling. Bioinformatics analysis and prediction of hsa-miR-32 target genes[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2016, 20(6): 609-613. doi: 10.16462/j.cnki.zhjbkz.2016.06.017

基于生物信息学的hsa-miR-32靶基因预测与功能分析

doi: 10.16462/j.cnki.zhjbkz.2016.06.017
基金项目: 

国家自然科学基金(39880032);广东省领军人才基金(C1030925)

详细信息
    作者简介:

    彭璨璨(1991-),女,广东清远人,在读硕士研究生。主要研究方向:基因芯片与生物信息学。

  • 中图分类号: R349.6;R349.64

Bioinformatics analysis and prediction of hsa-miR-32 target genes

  • 摘要: 目的 利用生物信息学方法,预测hsa-miR-32的靶基因并分析其功能,为深入研究其生物学功能提供指导和思路。方法 利用miRBase数据库获取并分析不同物种的miR-32序列特征;从公共GEO(gene expression omnibus,GEO)数据库中下载不同疾病相关的microRNA表达谱芯片数据,通过miRGator v3.0在线工具和Qlucore Omics Explorer 3.0软件分析hsa-miR-32在不同疾病组织中表达情况;并用PicTar、DIANA-microT-CDS 7.0、PITA及miRanda等方法预测hsa-miR-32靶基因,对获得的靶基因集合分别进行功能富集分析(gene ontology analysis)和生物通路富集分析(pathway enrichment analysis)。结果 miR-32在不同物种间高度保守。与癌旁正常组织相比,hsa-miR-32在子宫癌、结直肠癌、胰腺癌、前列腺癌、乳腺癌等多种癌组织中表达异常(均有P<0.05)。包括已被证实的靶基因,共得到168个候选基因,这些靶基因主要参与调控基因表达、细胞增殖、信号转导、细胞死亡等生物学过程(均有P<0.05),涉及小细胞肺癌、前列腺癌、胶质瘤、黑素瘤等疾病相关通路,以及p53等肿瘤相关信号通路和细胞周期等信号转导通路(均有P<0.05)。结论 hsa-miR-32功能广泛,与癌症的发生、发展密切相关。
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出版历程
  • 收稿日期:  2015-12-24
  • 修回日期:  2016-03-27

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