Shadow enhancers can suppress input transcription factor noise through distinct regulatory logic
Abstract
Shadow enhancers, groups of seemingly redundant enhancers, are found in a wide range of organisms and are critical for robust developmental patterning. However, their mechanism of action is unknown. We hypothesized that shadow enhancers drive consistent expression levels by buffering upstream noise through a separation of transcription factor (TF) inputs at the individual enhancers. By measuring transcriptional dynamics of several Kruppel shadow enhancer configurations in live Drosophila embryos, we showed individual member enhancers act largely independently. We found that TF fluctuations are an appreciable source of noise that the shadow enhancer pair can better buffer than duplicated enhancers. The shadow enhancer pair is uniquely able to maintain low levels of expression noise across a wide range of temperatures. A stochastic model demonstrated the separation of TF inputs is sufficient to explain these findings. Our results suggest the widespread use of shadow enhancers is partially due to their noise suppressing ability.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files. Code for analyzing the transcriptional traces and for creating the computational models is available on Git Hub: https://github.com/WunderlichLab/KrShadowEnhancerCode.
Article and author information
Author details
Funding
Eunice Kennedy Shriver National Institute of Child Health and Human Development (R00-HD073191)
- Zeba Wunderlich
Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01-HD095246)
- Zeba Wunderlich
Hellman Foundation
- Zeba Wunderlich
National Institute of Biomedical Imaging and Bioengineering (T32-EB009418)
- Alvaro Fletcher
ARCS Foundation
- Rachel Waymack
National Science Foundation (DMS1763272)
- German Enciso
Simons Foundation (594598)
- German Enciso
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Waymack 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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