Dynamical gene regulatory networks are tuned by transcriptional autoregulation with microRNA feedback

Abstract

the autoregulatory loops (M1) are present more often than expected by chance, this could lead to all motifs appearing to be enriched. We therefore used two remaining 24% were detected in four or more tissues (Figure.5A).Where TFs have binding site data in more than one tissue, we asked whether their connections were conserved between those tissues. To this end, we investigated the conservation of M1 and M2 type motifs between tissues. M1 autoregulatory motifs are well conserved between different tissue types: the autoregulatory ability of over half of all TFs was conserved in 100% of tissues where data exist ( Figure.5B).This suggests that their biological function may be linked to their ability to autoregulate. The presence of M2 motifs was only slightly less well conserved between tissues (Figure.5C). When M2 motifs are not conserved between tissues, the most significant factor is loss of autoregulation -19% of all M2 motifs lose their autoregulatory signal between tissues, whereas only 1.3% of motifs are not conserved because they are missing TF regulation of the microRNA. However, even when the presence of the M2 motif is conserved, the identity of the components of Affiliations ContributionsSGJ and NP supervised this study. TGM, SGJ and NP conceived and designed this study. All computational and bioinformatics experiments and subsequent analysis were conducted by TGM. Ethics approval and consent to participateNot applicable. Consent for publicationNot applicable.

Dynamic properties of noise and Her6 levels are optimized by miR‐9, allowing the decoding of the Her6 oscillator

“…This strongly suggests that, at single cell level, the onset of elavl3 expression preceded the switching off of her6 thus providing support for the computational model where a downstream gene X is activated independently or before a change in the level of gene Y (Her6; Fig ). Elavl3 is a good candidate for fulfilling the role of downstream target X because ChiP‐seq experiments have revealed Hes1 binding sites on elavl3 's regulatory region (Consortium, , GEO reference numbers: GSM2825430 and GSM2422987 and preprint: Minchington et al , ), and reciprocally, evidence has been reported indicating indirect negative feedback (Coolen et al , ), which is consistent with the opposing functions of Her6/Elavl3. Future experiments will be needed to characterize the interactions of Her6 with downstream targets.…”

Cooperative RNA degradation stabilizes intermediate epithelial-mesenchymal states and supports a phenotypic continuum

“…Mechanistically, the emergence of this intermediate cell state was due to the emergent feedback loop between the microRNA and mRNA, consisting of both transcriptional and post-transcriptional regulations (Figure 3C). It was previously shown that this type of hybrid feedback system is common in biology (29). Importantly, the well-known Zeb1-miR200 feedback loop contains this network topology (30).…”

Evolution of miRNA binding sites and regulatory networks in cichlids

“…In a wider context, as the individual regulatory hallmarks of TFs and miRNAs start to become characterised in disease e.g. forms of cancer (Plaisier et al 2016; Mullany et al 2018; Nersisyan et al 2021), congenital heart disease (You et al 2020), neuromuscular disorders (Bo et al 2021), as well as related to gene expression in human tissues (Minchington et al 2020) and plant stress response (Sharma et al 2020; Sharma et al 2021), the computational framework we applied here could be used to study the evolution of characterised regulatory edges and GRNs in the aforementioned, and other systems and phylogenies. However, the combined framework could be extended further by 1) analysing the impact of either more, or all of the 104 three-node motif models (Ahnert and Fink 2016) through the integration of epigenetic and co-immunoprecipitation assay data to gain regulatory directionality; and 2) including relevant datasets to study the regulatory effect of other mechanisms e.g.…”