Abstract
Mature microRNAs (miRNAs) are non-coding RNA that regulate most human genes through base-pairing with their targets. Under a condition of transcriptional arrest, cells were manipulated by overexpressing miRNAs. We observed global time-dependent changes in mRNA retention which are not restricted to the overexpressed miRNA targets. We developed COMICS (Competition of MiRNA Interactions in Cell Systems), a stochastic computational iterative framework for identifying general principles in miRNA regulation. We show that altering the composition of miRNAs governs cell identity. We identified gene sets that exhibit a coordinated behavior with respect to an exhaustive overexpression of all miRNAs. Among the stable genes that exhibit high mRNA retention levels, many participate in translation and belong to the translation machinery. The stable genes are shared among all tested cells, in contrast to the sensitive, low retention genes that are cell-type specific. We conclude that the stochastic nature of miRNA action imparts an unexpected robustness to living cells. The use of a systematic probabilistic approach exposes design principles of miRNAs regulation toward cell states, cell identity, and the translational machinery.
Synopsis This study models the miRNA regulatory network in different cell-lines under a transcriptional arrest paradigm. The probabilistic model is implemented using a stochastic computational framework called COMICS. The molecular outcome under miRNA regulation scheme is revealed from thousands of simulations under exhaustive miRNA manipulations.
Transcription arrest emphasizes the impact of miRNA manipulations on gene expression. The composition of miRNA, and primarily the most abundant ones dominate mRNA attenuation in living cells.
Cell identity can be shifted by the cell-specific composition of the miRNAs but not the mRNAs.
An exceptional immunity of genes vis-a-vis any manipulations of miRNAs is a property of the translational machinery. It suggests a common signature with respect to the nature of the miRNA binding sites.
Changing the parameters of the miRNAs probabilistic model affects the dynamics of gene expression but not its steady state or the cell identity.
