Quantitative proteomics reveals key roles for post-transcriptional gene regulation in the molecular pathology of FSHD

  1. Sujatha Jagannathan  Is a corresponding author
  2. Yuko Ogata
  3. Philip R Gafken
  4. Stephen J Tapscott  Is a corresponding author
  5. Robert K Bradley  Is a corresponding author
  1. Fred Hutchinson Cancer Research Center, United States

Abstract

DUX4 is a transcription factor whose misexpression in skeletal muscle causes facioscapulohumeral muscular dystrophy (FSHD). While DUX4's transcriptional activity has been extensively characterized, the DUX4-induced proteome remains undescribed. Here, we report concurrent measurement of RNA and protein levels in DUX4-expressing cells via RNA-seq and quantitative mass spectrometry. DUX4 transcriptional targets were robustly translated, confirming the likely clinical relevance of proposed FSHD biomarkers. However, a multitude of mRNAs and proteins exhibited discordant expression changes upon DUX4 expression. Our dataset revealed unexpected proteomic, but not transcriptomic, dysregulation of diverse molecular pathways, including Golgi apparatus fragmentation, as well as extensive post-transcriptional buffering of stress response genes. Key components of RNA degradation machineries, including UPF1, UPF3B, and XRN1, exhibited suppressed protein, but not mRNA, levels, explaining the build-up of aberrant RNAs that characterizes DUX4-expressing cells. Our results provide a resource for the FSHD community and illustrate the importance of post-transcriptional processes to DUX4-induced pathology.

Data availability

Mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (Vizcaino et al., 2013) with the dataset identifier PXD010221. To enable easy access to processed peptide-spectrum match data, we have also deposited peptide-level data to Dryad (doi:10.5061/dryad.ck06k75). The previously published RNA-seq data are available through the NCBI SRA database under accession number GSE85461

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

Article and author information

Author details

  1. Sujatha Jagannathan

    Computational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    sujatha.jagannathan@ucdenver.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9039-2631
  2. Yuko Ogata

    Proteomics Facility, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Philip R Gafken

    Proteomics Facility, Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Stephen J Tapscott

    Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    stapscot@fredhutch.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0319-0968
  5. Robert K Bradley

    Computational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, United States
    For correspondence
    rbradley@fredhutch.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8046-1063

Funding

National Institute of Neurological Disorders and Stroke (P01NS069539)

  • Stephen J Tapscott
  • Robert K Bradley

FSH Society (FSHS-22014-01)

  • Sujatha Jagannathan

Leukemia and Lymphoma Society

  • Robert K Bradley

National Institutes of Health (P30 CA015704)

  • Yuko Ogata
  • Philip R Gafken

M.J. Murdock Charitable Trust

  • Yuko Ogata
  • Philip R Gafken

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

Copyright

© 2019, Jagannathan 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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https://doi.org/10.7554/eLife.41740

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