University of Massachusetts Medical School Faculty Publications

UMMS Affiliation

Program in Systems Biology; Department of Microbiology and Physiological Systems

Publication Date

2021-04-10

Document Type

Article Preprint

Disciplines

Genetic Phenomena | Genetics and Genomics | Systems Biology

Abstract

Gene networks typically involve the regulatory control of multiple genes with related function. This connectivity enables correlated control of the levels and timing of gene expression. Here we study how the timing of gene expression in networks can be encoded in the regulatory DNA of a gene. Using stochastic simulations, we examine the role of binding affinity, TF regulatory function and network size in controlling the mean first-passage time to reach a fixed fraction of steady-state expression for both an auto-regulated TF gene and a target gene. We also examine how the variability in first-passage time depends on these factors. We find that both network size and binding affinity can dramatically speed up or slow down the response time of network genes, in some cases predicting more than a 100-fold change compared to constitutive expression. Furthermore, these factors can also significantly impact the fidelity of this response. Importantly, these effects do not occur at “extremes” of network size or binding affinity, but rather in an intermediate window of either quantity.

Keywords

transcriptional regulation, resource competition, network motifs, auto-regulation, gene expression

Rights and Permissions

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.

DOI of Published Version

10.1101/2021.04.09.439163

Source

bioRxiv 2021.04.09.439163; doi: https://doi.org/10.1101/2021.04.09.439163. Link to preprint on bioRxiv.

Comments

This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.

Journal/Book/Conference Title

bioRxiv

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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