Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published January 15, 2009 | Accepted Version
Journal Article Open

Modeling the dynamics of transcriptional gene regulatory networks for animal development

Abstract

The dynamic process of cell fate specification is regulated by networks of regulatory genes. The architecture of the network defines the temporal order of specification events. To understand the dynamic control of the developmental process, the kinetics of mRNA and protein synthesis and the response of the cis-regulatory modules to transcription factor concentration must be considered. Here we review mathematical models for mRNA and protein synthesis kinetics which are based on experimental measurements of the rates of the relevant processes. The model comprises the response functions of cis-regulatory modules to their transcription factor inputs, by incorporating binding site occupancy and its dependence on biologically measurable quantities. We use this model to simulate gene expression, to distinguish between cis-regulatory execution of "AND" and "OR" logic functions, rationalize the oscillatory behavior of certain transcriptional auto-repressors and to show how linked subcircuits can be dealt with. Model simulations display the effects of mutation of binding sites, or perturbation of upstream gene expression. The model is a generally useful tool for understanding gene regulation and the dynamics of cell fate specification.

Additional Information

© 2008 Elsevier Inc. Received 7 June 2008; revised 14 October 2008; accepted 21 October 2008. Available online 12 November 2008. The authors thank Jongmin Nam and Joel Smith for critical review of the manuscript and very insightful comments. Research was supported by NIH grant GM61005. Smadar Ben-Tabou de-Leon was supported by the Human Frontiers Science Program Organization.

Attached Files

Accepted Version - nihms590519.pdf

Files

nihms590519.pdf
Files (1.5 MB)
Name Size Download all
md5:da2f797ad7765c5eb39cb99193cf30ea
1.5 MB Preview Download

Additional details

Created:
August 22, 2023
Modified:
October 18, 2023