miRNAs provide robustness in gene expression for a specific network motif
Gene regulatory networks controlling cell fate decisions consist of several feedback loops and redundant components to ensure robust cellular functioning even if one or few components fail18,45,64 to perform accordingly. In a mammalian cell, miRNAs are part of many Transcriptional Regulatory Networks (TRNs), and they function along with the transcription factors to regulate target gene expression via feedback or feedforward loops.17,43,44,65 It is well-known in the literature that gene transcription happens in a bursting manner66–69 and is a highly noisy process.66,69,70 The translation and degradation processes of proteins also involve fluctuations from the different origins within a cell. These perturbations can propagate through a regulatory network to generate high fluctuations in the mRNA and protein numbers.46 Interestingly, for a feedforward loop motif (Fig. 4a, right panel ), where an upstream protein activates miRNA and its target, any fluctuation in the upstream protein would drive miRNA and target expression in the same direction.71 In such networks, miRNAs act as noise buffers and fine-tune the steady-state protein levels to achieve uniform protein expression in the cell population.71
The noise in gene expression can arise from various intrinsic (inherent molecular fluctuations) or extrinsic (due to the cell-to-cell variabilities) sources.72 The stochasticity in gene expression is contributed from both the intrinsic as well as extrinsic sources.67,68,72,73 Using single-cell reporter assays and mathematical modeling, Schmiedel et al13 have revealed that in embryonic stem cells, miRNAs reduced the variability in protein expression for low expressing genes, while increasing the same for the highly expressed genes.13 They found that the combined regulation of genes by multiple miRNAs further reduced the protein expression noise.13 Studies along the same direction have indicated that miRNA in feedforward loops can contribute to a similar reduction in protein expression noise.71Osella et al74 created a stochastic model for a gene’s expression, which is activated by a specific transcription factor (Fig. 4a, left panel ).74