Sensitivity of Gene Sets to miRNA Regulation: A Cell-Based Probabilistic Approach

Abstract

Mature microRNAs (miRNAs) are small, non-coding RNA molecules that function by base-pairing with mRNAs. In multicellular organisms, miRNAs lead to mRNA destabilization and translation arrest. Importantly, the quantities and stichometry of miRNAs/mRNAs determine the miRNA regulation characteristics of specific cells. In this study, we used COMICS (Competition of miRNA Interactions in Cell Systems), a stochastic computational iterative framework to characterize genes by their sensitivity and robustness to miRNA regulation. We monitor the cell state by quantifying the retention level for all mRNAs, at the end of 100,000 simulation iterations. In HeLa cells, we partitioned all genes to five classes according to their decay rates. We show that the largest class (69% of genes) is apparently resistant to miRNA regulation. We created in silico perturbations using overexpressing of all major miRNAs (248 types) at various levels relative to the basal level (x1 to x1000). We further classified genes according to the differential behaviour for any pair of conditions of miRNA expression profile. Based on such measure (OvereXpression Ratio, OXR), we identified a small number of gene sets that are especially sensitive to OXR. Our results expose an overlooked quantitative dimension for set of genes and miRNA regulation in living cells.