Why Network analysis for mRNA-miRNA-circRNA data integration?

Network analysis provides a global picture of interrealted changes in gene expression. It will allow you to get a better overview of how upstream changes effect downstream targets. 

In this example, RNA-seq data from cancer vs. normal tissue was analysed in-depth to provide expression levels of miRNAs, circRNAs plus their respective host and target-genes.


This information was integrated with regulatory relationships to form a complex network. From this global picture we extracted subnetworks of pathways consistent with known regulatory mechanisms: circRNAs are 'sponging up' miRNAs which would normally down-regulate their respective targets, - hence the downregulation of a circRNA negatively affects expression of the downstream target genes.


The figure below shows the network emerging by selecting significantly downregulated circRNAs with their downstream paths. Genes are shown in brown, circRNAs in pink and miRNAs in red, with the log2(FoldChange) value inside each node to show the extent and direction of regulation.


The central node in this example is downregulated by eight different miRNAs. The gene identified here is a known suppressor of tumor progression in a variety of cancers, but had not previous been implicated in this specific type of cancer.



Visulization of the emerging network generated by selecting significantly downregulated circRNAs with their downstream paths


Excel file containing the selected central nodes and their related pathways.