1. Chromosomes and Gene Expression
Download icon

Msn2/4 regulate expression of glycolytic enzymes and control transition from quiescence to growth

  1. Zheng Kuang
  2. Sudarshan Pinglay
  3. Hongkai Ji  Is a corresponding author
  4. Jef D Boeke  Is a corresponding author
  1. NYU Langone Medical Center, United States
  2. Johns Hopkins University School of Public Health, United States
Research Article
  • Cited 28
  • Views 2,174
  • Annotations
Cite this article as: eLife 2017;6:e29938 doi: 10.7554/eLife.29938

Abstract

Nutrient availability and stresses impact a cell's decision to enter a growth state or a quiescent state. Acetyl-CoA stimulates cell growth under nutrient-limiting conditions, but how cells generate acetyl-CoA under starvation stress is less understood. Here, we show that general stress response factors, Msn2 and Msn4, function as master transcriptional regulators of yeast glycolysis via directly binding and activating genes encoding glycolytic enzymes. Yeast cells lacking Msn2 and Msn4 exhibit prevalent repression of glycolysis genes and a significant delay of acetyl-CoA accumulation and reentry into growth from quiescence. Thus Msn2/4 exhibit a dual role in activating carbohydrate metabolism genes and stress response genes. These results suggest a possible mechanism by which starvation-induced stress response factors may prime quiescent cells to reenter growth through glycolysis when nutrients are limited.

Data availability

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Zheng Kuang

    Institute for Systems Genetics, NYU Langone Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5855-8371
  2. Sudarshan Pinglay

    Institute for Systems Genetics, NYU Langone Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8781-1476
  3. Hongkai Ji

    Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, United States
    For correspondence
    hji@jhu.edu
    Competing interests
    The authors declare that no competing interests exist.
  4. Jef D Boeke

    Institute for Systems Genetics, NYU Langone Medical Center, New York, United States
    For correspondence
    jef.boeke@nyumc.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5322-4946

Funding

National Institutes of Health (U54GM103520)

  • Zheng Kuang
  • Jef D Boeke

National Institutes of Health (R01HG006841)

  • Zheng Kuang
  • Hongkai Ji

National Institutes of Health (R01HG006282)

  • Zheng Kuang
  • Hongkai Ji

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Naama Barkai, Weizmann Institute of Science, Israel

Publication history

  1. Received: June 26, 2017
  2. Accepted: September 25, 2017
  3. Accepted Manuscript published: September 26, 2017 (version 1)
  4. Version of Record published: October 10, 2017 (version 2)

Copyright

© 2017, Kuang 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

  • 2,174
    Page views
  • 356
    Downloads
  • 28
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

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)

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

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

Further reading

    1. Chromosomes and Gene Expression
    2. Evolutionary Biology
    Mathias Scharmann et al.
    Research Article Updated

    Differences between males and females are usually more subtle in dioecious plants than animals, but strong sexual dimorphism has evolved convergently in the South African Cape plant genus Leucadendron. Such sexual dimorphism in leaf size is expected largely to be due to differential gene expression between the sexes. We compared patterns of gene expression in leaves among 10 Leucadendron species across the genus. Surprisingly, we found no positive association between sexual dimorphism in morphology and the number or the percentage of sex-biased genes (SBGs). Sex bias in most SBGs evolved recently and was species specific. We compared rates of evolutionary change in expression for genes that were sex biased in one species but unbiased in others and found that SBGs evolved faster in expression than unbiased genes. This greater rate of expression evolution of SBGs, also documented in animals, might suggest the possible role of sexual selection in the evolution of gene expression. However, our comparative analysis clearly indicates that the more rapid rate of expression evolution of SBGs predated the origin of bias, and shifts towards bias were depleted in signatures of adaptation. Our results are thus more consistent with the view that sex bias is simply freer to evolve in genes less subject to constraints in expression level.

    1. Chromosomes and Gene Expression
    2. Plant Biology
    Jaemyung Choi et al.
    Research Article

    Flowering plants utilize small RNA molecules to guide DNA methyltransferases to genomic sequences. This RNA-directed DNA methylation (RdDM) pathway preferentially targets euchromatic transposable elements. However, RdDM is thought to be recruited by methylation of histone H3 at lysine 9 (H3K9me), a hallmark of heterochromatin. How RdDM is targeted to euchromatin despite an affinity for H3K9me is unclear. Here we show that loss of histone H1 enhances heterochromatic RdDM, preferentially at nucleosome linker DNA. Surprisingly, this does not require SHH1, the RdDM component that binds H3K9me. Furthermore, H3K9me is dispensable for RdDM, as is CG DNA methylation. Instead, we find that non-CG methylation is specifically associated with small RNA biogenesis, and without H1 small RNA production quantitatively expands to non-CG methylated loci. Our results demonstrate that H1 enforces the separation of euchromatic and heterochromatic DNA methylation pathways by excluding the small RNA-generating branch of RdDM from non-CG methylated heterochromatin.