We used an experimental design based on two bidirectional plasmids and flow cytometry measurements of cotransfected mammalian cells. We validated a stochastic gene interaction model that describes how mRNAs can influence each other’s fluctuations in a miRNA-dependent manner in single cells. We show that miRNA–target correlations eventually lead to either bimodal cell population distributions with high and low target expression states, or correlated fluctuations across targets when the pool of unbound targets and miRNAs are in near-equimolar concentration. We found that there is an optimal range of conditions for the onset of cross-regulation, which is compatible with 10–1000 copies of targets per cell.

RNAs competing for microRNAs mutually influence their fluctuations in a highly non-linear microRNA-dependent manner in single cells

BALDASSI, CARLO;ZECCHINA, RICCARDO
2017-01-01

Abstract

We used an experimental design based on two bidirectional plasmids and flow cytometry measurements of cotransfected mammalian cells. We validated a stochastic gene interaction model that describes how mRNAs can influence each other’s fluctuations in a miRNA-dependent manner in single cells. We show that miRNA–target correlations eventually lead to either bimodal cell population distributions with high and low target expression states, or correlated fluctuations across targets when the pool of unbound targets and miRNAs are in near-equimolar concentration. We found that there is an optimal range of conditions for the onset of cross-regulation, which is compatible with 10–1000 copies of targets per cell.
2017
Bosia, Carla; Conti, Francesco; Sgrò, Laura; Baldassi, Carlo; Brusa, Davide; Cavallo, Federica; Di Cunto, Ferdinando; Turco, Emilia; Pagnani, Andrea; Zecchina, Riccardo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/3996680
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