基于共调控功能模块的方法来识别miRNA-miRNA协同调控网络

   来自哈尔滨医科大学生物信息科学与技术学院李霞教授课题组在《Nucleic Acids Research》杂志在线发表题为“MiRNA–miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features”的文章，该文章提出了基于共调控功能模块的方法来识别miRNA-miRNA协同调控网络的新方法，从一个全新的角度阐述了microRNA的调控机制，并为复杂疾病的机理探究、预防、诊断和治疗的发展起到积极的推动作用。
   人类基因组可以编码多于1100 miRNAs，这些miRNA能调控大部分人类基因。有限的miRNA能调控大部分编码蛋白的基因被认为是通过协同作用完成的，也就是多个miRNA可以一起协同控制单个基因。因此，miRNA间的协同调控对于理解复杂的转录后调控是重要的。鉴于此，该研究借助miRNA对共调控的功能模块构建了miRNA-miRNA功能协同网络（MFSN）。功能模块有三个特征：被miRNA对共调控，富集在同一个GO功能类中， 在蛋白质互作网络中距离近。和其他的生物网络性质类似，MFSN呈现无尺度，小世界和模块化结构。这些网络特性允许多个miRNA同时发挥调控作用，从而对干扰快速地做出响应。在该工作中，研究者发现疾病miRNA在MFSN中的拓扑测度是不同于非疾病miRNA的。疾病miRNA间有更多的协同作用，表明它们有更高的功能复杂性。他们还倾向定位在包含miRNA比较多的模块中，特别是这些模块的交叠处，表明疾病miRNA倾向是MFSN的全局中心，对不同或相似生物过程起到衔接作用。另外，和同一疾病相关的miRNA在网络中距离近，暗示着同一疾病的miRNA调控相同或者相似的功能。该方法不仅能有效的识别协同调控的miRNA对，而且也从系统的水平对疾病miRNA的作用机制进行了阐述。
   该工作主要由已毕业博士生徐娟完成。这篇论文是李霞课题组在计算系统生物学中取得的又一重要研究成果。课题组致力于利用计算系统生物学的方法阐明复杂疾病的致病机理，在计算系统生物学的领域已经走在了国际前沿。李霞教授领导的课题组在癌症等重大疾病功能基因识别方法的研究取得重要研究成果，科学研究论文已经陆续发表在《Briefings in Bioinformatics》， 《Nucleic Acids Research》，《Molecular Cancer Therapeutics》，《Bioinformatics》等国外著名生命科学杂志上。
原文摘要：
MiRNA–miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features
Juan Xu, Chuan-Xing Li, Yong-Sheng Li, Jun-Ying Lv, Ye Ma, Ting-Ting Shao, Liang-De Xu, Ying-Ying Wang, Lei Du, Yun-Peng Zhang, Wei Jiang, Chun-Quan Li, Yun Xiao and Xia Li*
Abstract
Synergistic regulations among multiple microRNAs (miRNAs) are important to understand the mechanisms of complex post-transcriptional regulations in humans. Complex diseases are affected by several miRNAs rather than a single miRNA. So, it is a challenge to identify miRNA synergism and thereby further determine miRNA functions at a system-wide level and investigate disease miRNA features in the miRNA–miRNA synergistic network from a new view. Here, we constructed a miRNA–miRNA functional synergistic network (MFSN) via co-regulating functional modules that have three features: common targets of corresponding miRNA pairs, enriched in the same gene ontology category and close proximity in the protein interaction network. Predicted miRNA synergism is validated by significantly high co-expression of functional modules and significantly negative regulation to functional modules. We found that the MFSN exhibits a scale free, small world and modular architecture. Furthermore, the topological features of disease miRNAs in the MFSN are distinct from non-disease miRNAs. They have more synergism, indicating their higher complexity of functions and are the global central cores of the MFSN. In addition, miRNAs associated with the same disease are close to each other. The structure of the MFSN and the features of disease miRNAs are validated to be robust using different miRNA target data sets.