Network correlation of noncoding RNAs: a new gene regulatory network in virus infection

A wealth of evidence indicates that non-coding RNAs, particularly long non-coding RNAs and circular RNAs are key players in highly complex gene regulatory networks. Accumulating experimental evidence suggests that circRNAs and lncRNAs can act as miRNA sponges, thus they possibly represent an additional mechanism/layer in which cells are able to regulate gene expression, in a hierarchical manner. The culmination of such evidence has resulted in the to the proposal of the competing endogenous RNA hypothesis. In this, non-coding RNAs (ie lncRNAs, circRNAs) are purported to sit at the top of these hierarchies, influencing the activity of 10s of miRNA, which themselves can each influence the expression of 10s-100s target mRNA. CircRNAs, in particular, represent prime candidates for the coordinators of the ceRNA hypothesis.

Recent observations that the gamma-herpesvirus Kaposi's Sarcoma herpesvirus (KSHV) affects expression of distinct circRNAs that operate as miRNA sponges indicates that KSHV has evolved the capacity to subvert the activity of putative ceRNA networks to exert broad influence on gene expression. However, due to the high complexity and scope of the gene networks of interest, a computational approach is required to analyse the huge transcriptomic and proteomic datasets generated by studies aiming to investigate such phenomenon. Primarily, machine-learning techniques will be utilised to disentangle any complex regulatory networks that are being influenced by KSHV, with the goal of using such perturbations to normal cellular functioning to infer the native operations of such cellular systems.