1. Chromosomes and Gene Expression
Download icon

RNA Polymerase II cluster dynamics predict mRNA output in living cells

  1. Won-Ki Cho
  2. Namrata Jayanth
  3. Brian P English
  4. Takuma Inoue
  5. J Owen Andrews
  6. William Conway
  7. Jonathan B Grimm
  8. Jan-Hendrik Spille
  9. Luke D Lavis
  10. Timothée Lionnet
  11. Ibrahim I Cisse  Is a corresponding author
  1. Massachusetts Institute of Technology, United States
Research Article
  • Cited 80
  • Views 7,630
  • Annotations
Cite this article as: eLife 2016;5:e13617 doi: 10.7554/eLife.13617

Abstract

Protein clustering is a hallmark of genome regulation in mammalian cells. However, the dynamic molecular processes involved make it difficult to correlate clustering with functional consequences in vivo. We developed a live-cell super-resolution approach to uncover the correlation between mRNA synthesis and the dynamics of RNA Polymerase II (Pol II) clusters at a gene locus. For endogenous β-actin genes in mouse embryonic fibroblasts, we observe that short-lived (~8 s) Pol II clusters correlate with basal mRNA output. During serum stimulation, a stereotyped increase in Pol II cluster lifetime correlates with a proportionate increase in the number of mRNAs synthesized. Our findings suggest that transient clustering of Pol II may constitute a pre-transcriptional regulatory event that predictably modulates nascent mRNA output.

Article and author information

Author details

  1. Won-Ki Cho

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Namrata Jayanth

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Brian P English

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Takuma Inoue

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. J Owen Andrews

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. William Conway

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Jonathan B Grimm

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Jan-Hendrik Spille

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Luke D Lavis

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  10. Timothée Lionnet

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.

  11. Ibrahim I Cisse

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    For correspondence
    icisse@mit.edu
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Xiaowei Zhuang, Howard Hughes Medical Institute, Harvard University, United States

Publication history

  1. Received: December 8, 2015
  2. Accepted: May 2, 2016
  3. Accepted Manuscript published: May 3, 2016 (version 1)
  4. Version of Record published: June 30, 2016 (version 2)

Copyright

© 2016, Cho 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

  • 7,630
    Page views
  • 2,444
    Downloads
  • 80
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, 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)

Categories and tags

Research organism

Further reading

    1. Chromosomes and Gene Expression

    Differentiating Drosophila female germ cells initiate Polycomb silencing by regulating PRC2-interacting proteins

    Steven Z Deluca et al.
    Research Article

    Polycomb silencing represses gene expression and provides a molecular memory of chromatin state that is essential for animal development. We show that Drosophila female germline stem cells (GSCs) provide a powerful system for studying Polycomb silencing. GSCs have a non-canonical distribution of PRC2 activity and lack silenced chromatin, like embryonic progenitors. As GSC daughters differentiate into nurse cells and oocytes, nurse cells silence genes in traditional Polycomb domains and in generally inactive chromatin like embryonic somatic cells. Developmentally controlled expression of two Polycomb repressive complex 2 (PRC2)-interacting proteins, Pcl and Scm, initiate silencing during differentiation. In GSCs, abundant Pcl inhibits PRC2-dependent silencing globally, while in nurse cells Pcl declines and newly-induced Scm concentrates PRC2 activity on traditional Polycomb domains. Our results suggest that PRC2-dependent silencing is developmentally regulated by accessory proteins that either increase the concentration of PRC2 at target sites or inhibit the rate that PRC2 samples chromatin.

    1. Chromosomes and Gene Expression
    2. Evolutionary Biology

    Genomic architecture and evolutionary antagonism drive allelic expression bias in the social supergene of red fire ants

    Carlos Martinez-Ruiz et al.
    Research Article

    Supergene regions maintain alleles of multiple genes in tight linkage through suppressed recombination. Despite their importance in determining complex phenotypes, our empirical understanding of early supergene evolution is limited. Here we focus on the young "social" supergene of fire ants, a powerful system for disentangling the effects of evolutionary antagonism and suppressed recombination. We hypothesize that gene degeneration and social antagonism shaped the evolution of the fire ant supergene, resulting in distinct patterns of gene expression. We test these ideas by identifying allelic differences between supergene variants, characterizing allelic expression across populations, castes and body parts, and contrasting allelic expression biases with differences in expression between social forms. We find strong signatures of gene degeneration and gene-specific dosage compensation. On this background, a small portion of the genes has the signature of adaptive responses to evolutionary antagonism between social forms.

    1. Chromosomes and Gene Expression

    Mechanisms underlying genome instability mediated by formation of foldback inversions in Saccharomyces cerevisiae

    Bin-zhong Li et al.
    Research Article

    Foldback inversions, also called inverted duplications, have been observed in human genetic diseases and cancers. Here we used a Saccharomyces cerevisiae genetic system that generates gross chromosomal rearrangements (GCRs) mediated by foldback inversions combined with whole-genome sequencing to study their formation. Foldback inversions were mediated by formation of single-stranded DNA hairpins. Two types of hairpins were identified: small-loop hairpins that were suppressed by MRE11, SAE2, SLX1, and YKU80 and large-loop hairpins that were suppressed by YEN1, TEL1, SWR1, and MRC1. Analysis of CRISPR/Cas9-induced double strand breaks (DSBs) revealed that long-stem hairpin-forming sequences could form foldback inversions when proximal or distal to the DSB, whereas short-stem hairpin-forming sequences formed foldback inversions when proximal to the DSB. Finally, we found that foldback inversion GCRs were stabilized by secondary rearrangements, mostly mediated by different homologous recombination mechanisms including single-strand annealing; however, POL32-dependent break-induced replication did not appear to be involved forming secondary rearrangements.