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人类基因组中组蛋白修饰与微小RNA调控的协同作用。

Coordinated action of histone modification and microRNA regulations in human genome.

作者信息

Wang Xuan, Zheng Guantao, Dong Dong

机构信息

Institute of Molecular Ecology and Evolution, SKLEC & IECR, East China Normal University, Shanghai, China.

Institute of Molecular Ecology and Evolution, SKLEC & IECR, East China Normal University, Shanghai, China.

出版信息

Gene. 2015 Oct 10;570(2):277-81. doi: 10.1016/j.gene.2015.06.046. Epub 2015 Jun 19.

Abstract

Both histone modifications and microRNAs (miRNAs) play pivotal role in gene expression regulation. Although numerous studies have been devoted to explore the gene regulation by miRNA and epigenetic regulations, their coordinated actions have not been comprehensively examined. In this work, we systematically investigated the combinatorial relationship between miRNA and epigenetic regulation by taking advantage of recently published whole genome-wide histone modification data and high quality miRNA targeting data. The results showed that miRNA targets have distinct histone modification patterns compared with non-targets in their promoter regions. Based on this finding, we proposed a machine learning approach to fit predictive models on the task to discern whether a gene is targeted by a specific miRNA. We found a considerable advantage in both sensitivity and specificity in diverse human cell lines. Finally, we found that our predicted miRNA targets are consistently annotated with Gene Ontology terms. Our work is the first genome-wide investigation of the coordinated action of miRNA and histone modification regulations, which provide a guide to deeply understand the complexity of transcriptional regulation.

摘要

组蛋白修饰和微小RNA(miRNA)在基因表达调控中都起着关键作用。尽管已有大量研究致力于探索miRNA介导的基因调控和表观遗传调控,但它们的协同作用尚未得到全面研究。在这项工作中,我们利用最近发表的全基因组范围的组蛋白修饰数据和高质量的miRNA靶向数据,系统地研究了miRNA与表观遗传调控之间的组合关系。结果表明,与非靶基因相比,miRNA靶基因在其启动子区域具有独特的组蛋白修饰模式。基于这一发现,我们提出了一种机器学习方法来拟合预测模型,以辨别一个基因是否被特定的miRNA靶向。我们发现在多种人类细胞系中,该方法在敏感性和特异性方面都具有显著优势。最后,我们发现我们预测的miRNA靶基因能够始终如一地用基因本体论术语进行注释。我们的工作是首次对miRNA和组蛋白修饰调控的协同作用进行全基因组范围的研究,为深入理解转录调控的复杂性提供了指导。

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