Application of ATAC-Seq for genome-wide analysis of the chromatin state at single myofiber resolution

  1. Korin Sahinyan
  2. Darren M Blackburn
  3. Marie-Michelle Simon
  4. Felicia Lazure
  5. Tony Kwan
  6. Guillaume Bourque
  7. Vahab D Soleimani  Is a corresponding author
  1. McGill University, Canada
  2. McGill University and Genome Quebec Innovation Centre, Canada
  3. McGill University and Génome Québec Innovation Centre, Canada

Abstract

Myofibers are the main components of skeletal muscle, which is the largest tissue in the body. Myofibers are highly adaptive and can be altered under different biological and disease conditions. Therefore, transcriptional and epigenetic studies on myofibers are crucial to discover how chromatin alterations occur in the skeletal muscle under different conditions. However, due to the heterogenous nature of skeletal muscle, studying myofibers in isolation proves to be a challenging task. Single cell sequencing has permitted the study of the epigenome of isolated myonuclei. While this provides sequencing with high dimensionality, the sequencing depth is lacking, which makes comparisons between different biological conditions difficult. Here we report the first implementation of single myofiber ATAC-Seq, which allows for the sequencing of an individual myofiber at a depth sufficient for peak calling and for comparative analysis of chromatin accessibility under various physiological and disease conditions. Application of this technique revealed significant differences in chromatin accessibility between resting and regenerating myofibers, as well as between myofibers from a mouse model of Duchenne Muscular Dystrophy (mdx) and wild type (WT) counterparts. This technique can lead to a wide application in the identification of chromatin regulatory elements and epigenetic mechanisms in muscle fibers during development and in muscle-wasting diseases.

Data availability

The data discussed in this study have been deposited in NCBI's Gene Expression Omnibus and are accessible through GEO Series accession numbers GSE173676 and GSE171534

The following data sets were generated

Article and author information

Author details

  1. Korin Sahinyan

    Department of Human Genetics, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  2. Darren M Blackburn

    Department of Human Genetics, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Marie-Michelle Simon

    McGill University and Genome Quebec Innovation Centre, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Felicia Lazure

    Department of Human Genetics, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. Tony Kwan

    McGill University and Génome Québec Innovation Centre, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  6. Guillaume Bourque

    Department of Human Genetics, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3933-9656
  7. Vahab D Soleimani

    Department of Human Genetics, McGill University, Montreal, Canada
    For correspondence
    vahab.soleimani@mcgill.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2154-4894

Funding

Natural Sciences and Engineering Research Council of Canada

  • Vahab D Soleimani

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

Ethics

Animal experimentation: All procedures that were performed on animals were approved by the McGill University Animal Care Committee (UACC), protocol #7512

Copyright

© 2022, Sahinyan 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. Korin Sahinyan
  2. Darren M Blackburn
  3. Marie-Michelle Simon
  4. Felicia Lazure
  5. Tony Kwan
  6. Guillaume Bourque
  7. Vahab D Soleimani
(2022)
Application of ATAC-Seq for genome-wide analysis of the chromatin state at single myofiber resolution
eLife 11:e72792.
https://doi.org/10.7554/eLife.72792

Share this article

https://doi.org/10.7554/eLife.72792

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