Abstract

Transcription is a highly stochastic process. To infer transcription kinetics for a gene-of-interest, researchers commonly compare the distribution of mRNA copy-number to the prediction of a theoretical model. However, the reliability of this procedure is limited because the measured mRNA numbers represent integration over the mRNA lifetime, contribution from multiple gene copies, and mixing of cells from different cell-cycle phases. We address these limitations by simultaneously quantifying nascent and mature mRNA in individual cells, and incorporating cell-cycle effects in the analysis of mRNA statistics. We demonstrate our approach on Oct4 and Nanog in mouse embryonic stem cells. Both genes follow similar two-state kinetics. However, Nanog exhibits slower ON/OFF switching, resulting in increased cell-to-cell variability in mRNA levels. Early in the cell cycle, the two copies of each gene exhibit independent activity. After gene replication, the probability of each gene copy to be active diminishes, resulting in dosage compensation.

Article and author information

Author details

  1. Samuel O Skinner

    Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Heng Xu

    Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Sonal Nagarkar-Jaiswal

    Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Pablo R Freire

    Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Thomas P Zwaka

    Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Ido Golding

    Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, United States
    For correspondence
    golding@bcm.edu
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Robert H Singer, Albert Einstein College of Medicine, United States

Version history

  1. Received: October 9, 2015
  2. Accepted: January 28, 2016
  3. Accepted Manuscript published: January 29, 2016 (version 1)
  4. Version of Record published: March 7, 2016 (version 2)

Copyright

© 2016, Skinner 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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  1. Samuel O Skinner
  2. Heng Xu
  3. Sonal Nagarkar-Jaiswal
  4. Pablo R Freire
  5. Thomas P Zwaka
  6. Ido Golding
(2016)
Single-cell analysis of transcription kinetics across the cell cycle
eLife 5:e12175.
https://doi.org/10.7554/eLife.12175

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https://doi.org/10.7554/eLife.12175

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