Computational Analysis of Transcriptional and Post-transcriptional Feedback Loops in Development and Cell Differentiation

Regulation of gene expression is critical to organism development and health. Positive and negative feedback in networks of gene regulatory interactions are associated with the maintenance of distinct cell states/types or oscillations, respectively. Recent computational studies identified two structures of positive feedback relevant to establishment of cell type: interconnected transcriptional “high-feedback” loops and a purely post-transcriptional feedback loop arising from multiple microRNA molecules cooperatively regulating one mRNA. The goals of this work were to develop methods for analyzing often-unintuitive high-feedback loops in large networks, generalize the two new regulatory structures to consider oscillation, and further explore the ability of post-transcriptional interactions to generate several stable gene expression states. Instances of the studied subnetwork structures were identified via a graph-theoretical approach, representing regulatory networks as signed directed graphs of genes. Subnetworks’ behaviors were predicted by numerical integration of ordinary differential equation systems representing the amounts of each RNA, complex, or protein. The network structure analysis approaches developed herein can be applied to realistic networks on consumer hardware. Regulated RNA degradation directed by the binding of two microRNAs is predicted to permit oscillations with a period uniquely sensitive to the target mRNA’s transcription rate, robustly producing bimodal gene expression in a population. Expansion to four microRNA binding sites supports up to four stable states without transcriptional feedback. The combination of multiple microRNAs and transcriptional feedback is predicted to permit, under some parameters, a range of intermediate cell states like the cancer-associated epithelial-mesenchymal continuum. Overall, this work explores the behaviors of regulatory network structures with previously underappreciated possible roles in development and cancer.