  MicroRNAs are endogenous non-coding RNAs which negatively regulate the
expression of protein-coding genes in plants and animals. They are known to
play an important role in several biological processes and, together with
transcription factors, form a complex and highly interconnected regulatory
network. Looking at the structure of this network it is possible to recognize a
few overrepresented motifs which are expected to perform important elementary
regulatory functions. Among them a special role is played by the
microRNA-mediated feedforward loop in which a master transcription factor
regulates a microRNA and, together with it, a set of target genes. In this
paper we show analytically and through simulations that the incoherent version
of this motif can couple the fine-tuning of a target protein level with an
efficient noise control, thus conferring precision and stability to the overall
gene expression program, especially in the presence of fluctuations in upstream
regulators. Among the other results, a nontrivial prediction of our model is
that the optimal attenuation of fluctuations coincides with a modest repression
of the target expression. This feature is coherent with the expected
fine-tuning function and in agreement with experimental observations of the
actual impact of a wide class of microRNAs on the protein output of their
targets. Finally we describe the impact on noise-buffering efficiency of the
cross-talk between microRNA targets that can naturally arise if the
microRNA-mediated circuit is not considered as isolated, but embedded in a
larger network of regulations.
