title: Systematic exploration of autonomous modules in noisy microRNA-target networks for testing the generality of the ceRNA hypothesis.
abstract: BACKGROUND
  In the competing endogenous RNA (ceRNA) hypothesis, different transcripts communicate through a competition for their common targeting microRNAs (miRNAs). Individual examples have clearly shown the functional importance of ceRNA in gene regulation and cancer biology. It remains unclear to what extent gene expression levels are regulated by ceRNA in general. One major hurdle to studying this problem is the intertwined connections in miRNA-target networks, which makes it difficult to isolate the effects of individual miRNAs.
  
  
  RESULTS
  Here we propose computational methods for decomposing a complex miRNA-target network into largely autonomous modules called microRNA-target biclusters (MTBs). Each MTB contains a relatively small number of densely connected miRNAs and mRNAs with few connections to other miRNAs and mRNAs. Each MTB can thus be individually analyzed with minimal crosstalk with other MTBs. Our approach differs from previous methods for finding modules in miRNA-target networks by not making any pre-assumptions about expression patterns, thereby providing objective information for testing the ceRNA hypothesis. We show that the expression levels of miRNAs and mRNAs in an MTB are significantly more anti-correlated than random miRNA-mRNA pairs and other validated and predicted miRNA-target pairs, demonstrating the biological relevance of MTBs. We further show that there is widespread correlation of expression between mRNAs in same MTBs under a wide variety of parameter settings, and the correlation remains even when co-regulatory effects are controlled for, which suggests potential widespread expression buffering between these mRNAs, which is consistent with the ceRNA hypothesis. Lastly, we also propose a potential use of MTBs in functional annotation of miRNAs.
  
  
  CONCLUSIONS
  MTBs can be used to help identify autonomous miRNA-target modules for testing the generality of the ceRNA hypothesis experimentally. The identified modules can also be used to test other properties of miRNA-target networks in general.
authors.forename: Danny Kit-Sang
authors.initials: DK
authors.lastname: Yip
authors.forename: Iris K
authors.initials: IK
authors.lastname: Pang
authors.affiliation: Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong. kevinyip@cse.cuhk.edu.hk.
authors.forename: Kevin Y
authors.initials: KY
authors.lastname: Yip
mesh_terms: D045744:Cell Line, Tumor; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger