Model-guided quantitative analysis of microRNA-mediated regulation on competing endogenous RNAs using a synthetic gene circuit

Competing endogenous RNAs (ceRNAs) cross-regulate each other at the posttranscriptional level by titrating shared microRNAs (miRNAs). Here, we established a computational model to quantitatively describe a minimum ceRNA network and experimentally validated our model predictions in cultured human cells by using synthetic gene circuits. We demonstrated that the range and strength of ceRNA regulation are largely determined by the relative abundance and the binding strength of miRNA and ceRNAs. We found that a nonreciprocal competing effect between partially and perfectly complementary targets is mainly due to different miRNA loss rates in these two types of regulations. Furthermore, we showed that miRNA-like off targets with high expression levels and strong binding sites significantly diminish the RNA interference efficiency, but the effect caused by high expression levels could be compensated by introducing more small interference RNAs (siRNAs). Thus, our results provided a quantitative understanding of ceRNA cross-regulation via shared miRNA and implied an siRNA design strategy to reduce the siRNA off-target effect in mammalian cells.