title: A combination of transcriptional and microRNA regulation improves the stability of the relative concentrations of target genes.
abstract: It is well known that, under suitable conditions, microRNAs are able to fine tune the relative concentration of their targets to any desired value. We show that this function is particularly effective when one of the targets is a Transcription Factor (TF) which regulates the other targets. This combination defines a new class of feed-forward loops (FFLs) in which the microRNA plays the role of master regulator. Using both deterministic and stochastic equations, we show that these FFLs are indeed able not only to fine-tune the TF/target ratio to any desired value as a function of the miRNA concentration but also, thanks to the peculiar topology of the circuit, to ensure the stability of this ratio against stochastic fluctuations. These two effects are due to the interplay between the direct transcriptional regulation and the indirect TF/Target interaction due to competition of TF and target for miRNA binding (the so called "sponge effect"). We then perform a genome wide search of these FFLs in the human regulatory network and show that they are characterized by a very peculiar enrichment pattern. In particular, they are strongly enriched in all the situations in which the TF and its target have to be precisely kept at the same concentration notwithstanding the environmental noise. As an example we discuss the FFL involving E2F1 as Transcription Factor, RB1 as target and miR-17 family as master regulator. These FFLs ensure a tight control of the E2F/RB ratio which in turns ensures the stability of the transition from the G0/G1 to the S phase in quiescent cells.
authors.affiliation: Department of Physics and INFN, University of Torino, Torino, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Riba
authors.affiliation: Department of Physics and INFN, University of Torino, Torino, Italy.
authors.forename: Carla
authors.initials: C
authors.lastname: Bosia
authors.affiliation: National Research Council (CNR), Institute of Informatics and Telematics (IIT) and Institute of Clinical Physiology (IFC), Laboratory for Integrative System Medicine (LISM), Pisa, Italy.
authors.forename: Mariama
authors.initials: M
authors.lastname: El Baroudi
authors.affiliation: Department of Physics and INFN, University of Torino, Torino, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Ollino
authors.affiliation: Department of Physics and INFN, University of Torino, Torino, Italy.
authors.forename: Michele
authors.initials: M
authors.lastname: Caselle
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D050687:E2F1 Transcription Factor / Q000378:metabolism; D053263:Gene Regulatory Networks; D016161:Genes, Retinoblastoma; D042822:Genomic Instability; D006801:Humans; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D008957:Models, Genetic; D012323:RNA Processing, Post-Transcriptional; D013269:Stochastic Processes; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D050687:E2F1 Transcription Factor; C493753:E2F1 protein, human; C524941:MIRN17 microRNA, human; D035683:MicroRNAs; D014157:Transcription Factors