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A novel group of small non-coding RNA, known as microRNA (miRNA) is predictedto regulate as high as 90% of the coding genes in human. The diversity andabundance of miRNA targets offer an enormous level of combinatorialpossibilities and suggest that miRNAs and their targets form a complexregulatory network. In the present study, we analyzed 711 miRNAs and their 34,525 predicted targets in the miRBase database which generate a complexbipartite network having numerous numbers of genes forming the hub. Genes atthe hub (total 9877) are significantly over represented in genes with specificmolecular functions, biological processes and biological pathways as revealedfrom the analysis using PANTHER. We further construct a miRNA co-target networkby linking every pair of miRNAs which co-target at least one gene. The weightof the link, which is taken to be the number of co-targets of the pair ofmiRNAs vary widely, and we could erase several links while keeping the relevantfeatures of the network intact. The largest connected sub-graph, thus obtained,contains 479 miRNAs. More than 75% of the miRNAs deregulated in 15 differentdiseases collected from published data are found to be in this largest subgraph. We further analyze this sub-graph to obtain 70 small clusters containingtotal 330 miRNAs of 479. We identified the biological pathways where theco-targeted genes in the clusters are significantly over- represented incomparison to that obtained with that are not co-targeted by the miRNAs in thecluster. Using published data, we identified that specific clusters of miRNAsare associated with specific diseases by altering particular pathways. Wepropose that instead of single miRNA, clusters of miRNA that co-targets thegenes are important for the regulation of miRNA in diseases.

MicroRNA Interaction network in human: implications of clustered microRNA in biological pathways and genetic diseases