Shadow enhancers can suppress input transcription factor noise through distinct regulatory logic

  1. Rachel Waymack
  2. Alvaro Fletcher
  3. German Enciso
  4. Zeba Wunderlich  Is a corresponding author
  1. University of California, Irvine, United States

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

  1. Rachel Waymack

    Developmental and Cell Biology, University of California, Irvine, Irvine, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Alvaro Fletcher

    Mathematical, Computational, and System Biology Graduate Program, University of California, Irvine, Irvine, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. German Enciso

    Mathematics, University of California, Irvine, Irvine, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Zeba Wunderlich

    Developmental and Cell Biology, University of California, Irvine, Irvine, United States
    For correspondence
    zeba@uci.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4491-5715

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.

Metrics

  • 3,843
    views
  • 477
    downloads
  • 39
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Rachel Waymack
  2. Alvaro Fletcher
  3. German Enciso
  4. Zeba Wunderlich
(2020)
Shadow enhancers can suppress input transcription factor noise through distinct regulatory logic
eLife 9:e59351.
https://doi.org/10.7554/eLife.59351

Share this article

https://doi.org/10.7554/eLife.59351

Further reading

    1. Chromosomes and Gene Expression
    Shihui Chen, Carolyn Marie Phillips
    Research Article

    RNA interference (RNAi) is a conserved pathway that utilizes Argonaute proteins and their associated small RNAs to exert gene regulatory function on complementary transcripts. While the majority of germline-expressed RNAi proteins reside in perinuclear germ granules, it is unknown whether and how RNAi pathways are spatially organized in other cell types. Here, we find that the small RNA biogenesis machinery is spatially and temporally organized during Caenorhabditis elegans embryogenesis. Specifically, the RNAi factor, SIMR-1, forms visible concentrates during mid-embryogenesis that contain an RNA-dependent RNA polymerase, a poly-UG polymerase, and the unloaded nuclear Argonaute protein, NRDE-3. Curiously, coincident with the appearance of the SIMR granules, the small RNAs bound to NRDE-3 switch from predominantly CSR-class 22G-RNAs to ERGO-dependent 22G-RNAs. NRDE-3 binds ERGO-dependent 22G-RNAs in the somatic cells of larvae and adults to silence ERGO-target genes; here we further demonstrate that NRDE-3-bound, CSR-class 22G-RNAs repress transcription in oocytes. Thus, our study defines two separable roles for NRDE-3, targeting germline-expressed genes during oogenesis to promote global transcriptional repression, and switching during embryogenesis to repress recently duplicated genes and retrotransposons in somatic cells, highlighting the plasticity of Argonaute proteins and the need for more precise temporal characterization of Argonaute-small RNA interactions.

    1. Chromosomes and Gene Expression
    2. Genetics and Genomics
    Steven Henikoff, David L Levens
    Insight

    A new method for mapping torsion provides insights into the ways that the genome responds to the torsion generated by RNA polymerase II.