Predictive modeling reveals that higher-order cooperativity drives transcriptional repression in a synthetic developmental enhancer
Abstract
A challenge in quantitative biology is to predict output patterns of gene expression from knowledge of input transcription factor patterns and from the arrangement of binding sites for these transcription factors on regulatory DNA. We tested whether widespread thermodynamic models could be used to infer parameters describing simple regulatory architectures that inform parameter-free predictions of more complex enhancers in the context of transcriptional repression by Runt in the early fruit fly embryo. By modulating the number and placement of Runt binding sites within an enhancer, and quantifying the resulting transcriptional activity using live imaging, we discovered that thermodynamic models call for higher-order cooperativity between multiple molecular players. This higher-order cooperativity capture the combinatorial complexity underlying eukaryotic transcriptional regulation and cannot be determined from simpler regulatory architectures, highlighting the challenges in reaching a predictive understanding of transcriptional regulation in eukaryotes and calling for approaches that quantitatively dissect their molecular nature.
Data availability
All data (both input transcription factor concentration and output transcription from all synthetic enhancers, both pre- and post-processed data) have been deposited in Dryad under the doi (https://doi.org/10.5061/dryad.7sqv9s4sv).
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Predictive modeling reveals that higher-order cooperativity drives transcriptional repression in a synthetic developmental enhancerDryad Digital Repository, doi:10.5061/dryad.7sqv9s4sv.
Article and author information
Author details
Funding
Burroughs Wellcome Fund (Career Award)
- Hernan G Garcia
Sloan Research Foundation
- Hernan G Garcia
Human Frontier Science Program
- Hernan G Garcia
Searle Scholars Program
- Hernan G Garcia
Shurl and Kay Curci Foundation
- Hernan G Garcia
Hellman Foundation
- Hernan G Garcia
National Institute of Health (DP2 OD024541-01)
- Hernan G Garcia
National Science Foundation (1652236)
- Hernan G Garcia
Korea Foundation for Advanced Studies (Graduate Student Fellowship)
- Yang Joon Kim
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Kim et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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