Dissection of human MiRNA regulatory influence to subpathway

Briefings in Bioinformatics, Mar 2012

The global insight into the relationships between miRNAs and their regulatory influences remains poorly understood. And most of complex diseases may be attributed to certain local areas of pathway (subpathway) instead of the entire pathway. Here, we reviewed the studies on miRNA regulations to pathways and constructed a bipartite miRNAs and subpathways network for systematic analyzing the miRNA regulatory influences to subpathways. We found that a small fraction of miRNAs were global regulators, environmental information processing pathways were preferentially regulated by miRNAs, and miRNAs had synergistic effect on regulating group of subpathways with similar function. Integrating the disease states of miRNAs, we also found that disease miRNAs regulated more subpathways than nondisease miRNAs, and for all miRNAs, the number of regulated subpathways was not in proportion to the number of the related diseases. Therefore, the study not only provided a global view on the relationships among disease, miRNA and subpathway, but also uncovered the function aspects of miRNA regulations and potential pathogenesis of complex diseases. A web server to query, visualize and download for all the data can be freely accessed at http://bioinfo.hrbmu.edu.cn/miR2Subpath.

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Dissection of human MiRNA regulatory influence to subpathway

Xia Li Wei Jiang Wei Li Baofeng Lian Shuyuan Wang Mingzhi Liao Xiaowen Chen Yanqiu Wang Yingli Lv Shiyuan Wang Lei Yang The global insight into the relationships between miRNAs and their regulatory influences remains poorly understood. And most of complex diseases may be attributed to certain local areas of pathway (subpathway) instead of the entire pathway. Here, we reviewed the studies on miRNA regulations to pathways and constructed a bipartite miRNAs and subpathways network for systematic analyzing the miRNA regulatory influences to subpathways. We found that a small fraction of miRNAs were global regulators, environmental information processing pathways were preferentially regulated by miRNAs, and miRNAs had synergistic effect on regulating group of subpathways with similar function. Integrating the disease states of miRNAs, we also found that disease miRNAs regulated more subpathways than nondisease miRNAs, and for all miRNAs, the number of regulated subpathways was not in proportion to the number of the related diseases. Therefore, the study not only provided a global view on the relationships among disease, miRNA and subpathway, but also uncovered the function aspects of miRNA regulations and potential pathogenesis of complex diseases. A web server to query, visualize and download for all the data can be freely accessed at http://bioinfo.hrbmu.edu.cn/miR2Subpath. - INTRODUCTION The mechanism of post-transcriptional regulation of coding genes is rising as one of the new challenges in systems biology. miRNAs are single-stranded RNAs, which regulate gene expression by translation inhibition or degradation of mRNAs in posttranscriptional level [1]. Some investigations have been reported that miRNAs take part in a lot of important biological functions and a broad spectrum of human diseases, such as cell proliferation, differentiation, apoptosis [24], immune response [5], tumor development [6], cardiac diseases [7] and so on. More and more studies have demonstrated that one miRNA can regulate several hundred genes on average [8]. Currently, the functional interpretation of miRNAs mainly relies on the functions of their target genes. Several studies predicted the functions of miRNAs based on the enrichment analysis of their target genes from a number of functional categories. For example, miRGator [9] and DIANA-mirPath [10] provided the statistically enriched Gene Ontology functions, KEGG/GenMAPP/BioCarta pathways, or diseases from Ingenuity Pathway Analysis [11]. Another comprehensive analysis established a dictionary on miRNAs and their putative target pathways and found that differentially expressed genes in cancer were statistically significant enriched with targets of certain miRNAs [12]. They are effective tools for study on miRNAs and pathways, but they do not pay more attention to local areas of pathway and the properties of miRNA regulations to pathways, especially in human diseases. Recently, we have demonstrated that subpathway (local area of the entire biological pathway)-based analysis may give us much more detailed explanations of type-specific functions for pathology of complex diseases, because the focused genes may not be significantly enriched in the entire pathway but the subpathways [13]. In this study, we constructed the bipartite graph of miRNAsubpathway interactions to explore the rules of miRNA regulatory influence on subpathway. The results indicated that miRNAs have synergistic effect to regulate a group of subpathways with similar function. Through integrating the disease information of miRNAs, the characteristics of disease miRNAs regulation were also uncovered. All the findings can help us to understand the detail mechanisms of miRNAs regulations and identify novel disordered miRNAs or subpathways in human diseases. MATERIALS AND METHODS Data Source MiRNA target genes We acquired human miRNA target genes from seven miRNA target predicting tools, which were PicTar [14], RNAhybrid [15], DIANA-microT [16], RNA22 [17], miRBase Targets [18], miRanda [19], TargetScan [20]. In order to improve the reliability of the predicted miRNA regulations, we only extracted the regulations that were predicted by at least two tools. In the final, we obtained 776 miRNAs, 15 185 miRNA target genes and 289 469 miRNA regulations. Disease information of miRNAs We downloaded the miR2Disease database (August 2009) [21], which contained the disease-miRNA relationships extracted from literatures. Disease miRNAs are defined by miRNAs themselves deregulation in various human diseases. In total, there are 123 diseases, 414 miRNAs and 2047 miRNA-disease pairs in the whole data file. We classified diseases according to the rules in the online book of Genes and Disease (http://www.ncbi.nlm .nih.gov/books/NBK22183/). In the final, the 123 diseases were grouped into 15 disease categories. The concrete classes were Hematological (Hem), Cancer, Chromosomal (Chr), Ophthamological (Oph), Immunological (Imm), (...truncated)


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Xia Li, Wei Jiang, Wei Li, Baofeng Lian, Shuyuan Wang, Mingzhi Liao, Xiaowen Chen, Yanqiu Wang, Yingli Lv, Shiyuan Wang, Lei Yang. Dissection of human MiRNA regulatory influence to subpathway, Briefings in Bioinformatics, 2012, pp. 175-186, 13/2, DOI: 10.1093/bib/bbr043