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