Related Experiment Video
Updated: Jul 14, 2026

A Reporter Assay to Analyze Intronic microRNA Maturation in Mammalian Cells
Published on: June 16, 2022
Impact of competition between precursor and mature microRNAs on stochastic gene expression
Raunak Adhikary1, Dipjyoti Das1
1Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Nadia, Mohanpur, West Bengal 741246, India.
Abstract:
MicroRNAs (miRNAs) are key post-transcriptional regulators, processed from precursor miRNAs (pre-miRNAs) into mature miRNAs through nuclear and cytoplasmic proteins. Recent evidence shows that pre-miRNAs and mature miRNAs can compete for the same target mRNAs, yet the impact of this miRNA maturation-driven competition on gene expression noise remains unknown. We address this in widespread feedback motifs where both pre-miRNAs and mature miRNAs degrade a protein's transcripts, and the protein itself either activates or represses miRNA transcription. Using a mathematical model, we show that miRNA maturation tunes the behavior of positive or negative feedback loops, which function as bistable switches or oscillators at the mean-field level, respectively. The relative degradation of mature versus pre-miRNAs and the mRNA-miRNA co-degradation rates can jointly modulate the parameter regions of bistability or oscillations. Moreover, for positive feedback, stochastic simulations reveal that bimodal mRNA distributions emerge near the saddle-node bifurcation boundaries, but not always within the bistable regions. Bimodal mRNA distributions also appear for negative feedback, but outside the region of limit cycles. Importantly, in both feedback types, such noise-induced bimodality emerges in regions where mean-field analysis predicts no bistability or limit cycles. These results demonstrate that noise-induced phenotypic variability cannot necessarily be linked to underlying deterministic bifurcations and elucidate how miRNA maturation shapes stochastic gene expression in regulatory motifs relevant to development and disease.
Insights
MicroRNA (miRNA) maturation impacts gene expression noise. Competition between precursor and mature miRNAs can create bimodal mRNA distributions, revealing noise-induced variability beyond traditional models.
Area of Science:
- Molecular Biology
- Systems Biology
- Gene Regulation
Background:
- MicroRNAs (miRNAs) are crucial post-transcriptional regulators.
- miRNA maturation involves processing precursor miRNAs (pre-miRNAs) into mature miRNAs.
- Pre- and mature miRNAs can compete for the same target mRNAs, but their impact on gene expression noise is unclear.
Purpose of the Study:
- Investigate how miRNA maturation influences gene expression noise in feedback loops.
- Determine the role of pre-miRNA and mature miRNA competition in gene expression variability.
- Analyze the relationship between noise-induced bimodality and deterministic bifurcations.
Main Methods:
- Developed a mathematical model for feedback motifs involving miRNA regulation.
- Analyzed mean-field behavior of positive and negative feedback loops.
- Performed stochastic simulations to assess gene expression noise and mRNA distributions.
Main Results:
- miRNA maturation tunes feedback loops into bistable switches or oscillators.
- Relative degradation rates and co-degradation influence bistability and oscillation regions.
- Stochastic simulations revealed noise-induced bimodal mRNA distributions outside predicted mean-field regions for both positive and negative feedback.
Conclusions:
- Noise-induced phenotypic variability is not always tied to deterministic bifurcations.
- miRNA maturation significantly shapes stochastic gene expression in regulatory networks.
- Findings are relevant for understanding gene expression in development and disease.
Related Concept Videos
MicroRNAs
MicroRNAs
MicroRNAs
mRNA Stability and Gene Expression
Cis-acting Elements involved in mRNA stability
mRNA Stability and Gene Expression
Cis-acting Elements involved in mRNA stability
Regulation of Expression at Multiple Steps

