NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs

PLoS One. 2011 Feb 25;6(2):e17429. doi: 10.1371/journal.pone.0017429.


Background: MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (

Results: mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs.

Conclusions: Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Cluster Analysis
  • Computational Biology / methods*
  • Databases, Nucleic Acid*
  • Forecasting / methods
  • Genome, Human
  • Humans
  • Metabolic Networks and Pathways / genetics
  • Metabolic Networks and Pathways / physiology
  • MicroRNAs / genetics*
  • MicroRNAs / metabolism
  • Models, Biological
  • Protein Interaction Mapping
  • Sequence Analysis, RNA / methods*
  • Signal Transduction / genetics*
  • Software
  • Validation Studies as Topic


  • MicroRNAs