Dynamics of transcription-translation networks

TL;DR

This paper develops a qualitative modeling framework for gene regulatory networks that explicitly includes both transcription and translation processes, extending existing protein-only models to better capture biological dynamics.

Contribution

It introduces a class of models incorporating mRNA and protein concentrations with steep sigmoid regulation functions, extending protein-only theories to include translation.

Findings

Non-uniqueness of solutions can occur in the step-function limit.

Singular behavior in switching domains is largely avoided.

Properties of fixed points and periodic orbits are extended to this new context.

Abstract

A theory for qualitative models of gene regulatory networks has been developed over several decades, generally considering transcription factors to regulate directly the expression of other transcription factors, without any intermediate variables. Here we explore a class of models that explicitly includes both transcription and translation, keeping track of both mRNA and protein concentrations. We mainly deal with transcription regulation functions that are steep sigmoids or step functions, as is often done in protein-only models, though translation is governed by a linear term. We extend many aspects of the protein-only theory to this new context, including properties of fixed points, description of trajectories by mappings between switching points, qualitative analysis via a state-transition diagram, and a result on periodic orbits for negative feedback loops. We find that while singular behaviour in switching domains is largely avoided, non-uniqueness of solutions can still occur in the step-function limit.