Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions.
Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions.
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miRNA-mRNA 和 miRNA-miRNA 相互作用的综合分析
DOI：
10.1155/2014/907420
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发表时间：
2014
影响因子：
--
通讯作者：
Chen F
中科院分区：
文献类型：
--
作者：
Guo L;Zhao Y;Yang S;Zhang H;Chen F
微小RNA（miRNAs）是小型的非编码调控分子。它们参与许多重要的生物学过程，并通过抑制基因表达发挥作用。本研究利用高通量miRNA和mRNA数据集，对miRNA - mRNA以及miRNA - miRNA相互作用及其调控模式进行了综合分析。基于倍数变化分析获得了异常表达的miRNA和mRNA图谱，并使用实时定量聚合酶链反应（qRT - PCR）对失调的miRNAs进行进一步验证。发现miRNAs和靶mRNA呈现出多种表达模式。还发现miRNA - miRNA相互作用以及成簇的/同源的miRNAs对灵活且具有选择性的调控网络有贡献。相互作用的miRNAs（例如，miRNA - 103a和miR - 103b）在表达上表现出更显著的差异，这表明在miRNA世界中可能存在“受限的相互作用”。来自相同基因簇（例如，miR - 23b基因簇）或基因家族（例如，miR - 10基因家族）的miRNAs总是表现出相同类型的失调模式，尽管它们在表达水平上有时存在差异。这些成簇的和同源的miRNAs可能具有密切的功能关系，这可能表明miRNAs之间存在协同相互作用。基于miRNA生物学特性对miRNA - mRNA进行综合分析将进一步丰富miRNA的研究。
MicroRNAs (miRNAs) are small, noncoding regulatory molecules. They are involved in many essential biological processes and act by suppressing gene expression. The present work reports an integrative analysis of miRNA-mRNA and miRNA-miRNA interactions and their regulatory patterns using high-throughput miRNA and mRNA datasets. Aberrantly expressed miRNA and mRNA profiles were obtained based on fold change analysis, and qRT-PCR was used for further validation of deregulated miRNAs. miRNAs and target mRNAs were found to show various expression patterns. miRNA-miRNA interactions and clustered/homologous miRNAs were also found to contribute to the flexible and selective regulatory network. Interacting miRNAs (e.g., miRNA-103a and miR-103b) showed more pronounced differences in expression, which suggests the potential “restricted interaction” in the miRNA world. miRNAs from the same gene clusters (e.g., miR-23b gene cluster) or gene families (e.g., miR-10 gene family) always showed the same types of deregulation patterns, although they sometimes differed in expression levels. These clustered and homologous miRNAs may have close functional relationships, which may indicate collaborative interactions between miRNAs. The integrative analysis of miRNA-mRNA based on biological characteristics of miRNA will further enrich miRNA study.
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影响因子：
14.9
作者：
Kozomara A;Griffiths-Jones S
通讯作者：
Griffiths-Jones S
影响因子：
3.7
作者：
Guo L;Yang Q;Lu J;Li H;Ge Q;Gu W;Bai Y;Lu Z
通讯作者：
Lu Z
基于深度测序数据 isomiR 的 miRNA 基因簇和家族的全局表达分析
影响因子：
3.1
作者：
Guo, Li;Lu, Zuhong
通讯作者：
Lu, Zuhong
影响因子：
7
作者：
Morin, Ryan D.;O'Connor, Michael D.;Marra, Marco A.
通讯作者：
Marra, Marco A.
DOI：
10.1093/bioinformatics/btq675
发表时间：
2011-02-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Smoot ME;Ono K;Ruscheinski J;Wang PL;Ideker T
通讯作者：
Ideker T