Massively multiplex single-molecule oligonucleosome footprinting

  1. Nour J Abdulhay
  2. Colin P McNally
  3. Laura J Hsieh
  4. Sivakanthan Kasinathan
  5. Aidan Keith
  6. Laurel S Estes
  7. Mehran Karimzadeh
  8. Jason G Underwood
  9. Hani Goodarzi
  10. Geeta J Narlikar
  11. Vijay Ramani  Is a corresponding author
  1. University of California San Francisco, United States
  2. Stanford University, United States
  3. Vector Institute, Canada
  4. Pacific Biosciences of California, Inc, United States
  5. University of California, San Francisco, United States

Abstract

Our understanding of the beads-on-a-string arrangement of nucleosomes has been built largely on high-resolution sequence-agnostic imaging methods and sequence-resolved bulk biochemical techniques. To bridge the divide between these approaches, we present the single-molecule adenine methylated oligonucleosome sequencing assay (SAMOSA). SAMOSA is a high-throughput single-molecule sequencing method that combines adenine methyltransferase footprinting and single-molecule real-time DNA sequencing to natively and nondestructively measure nucleosome positions on individual chromatin fibres. SAMOSA data allows unbiased classification of single-molecular 'states' of nucleosome occupancy on individual chromatin fibres. We leverage this to estimate nucleosome regularity and spacing on single chromatin fibres genome-wide, at predicted transcription factor binding motifs, and across both active and silent human epigenomic domains. Our analyses suggest that chromatin is comprised of a diverse array of both regular and irregular single-molecular oligonucleosome patterns that differ subtly in their relative abundance across epigenomic domains. This irregularity is particularly striking in constitutive heterochromatin, which has typically been viewed as a conformationally static entity. Our proof-of-concept study provides a powerful new methodology for studying nucleosome organization at a previously intractable resolution, and offers up new avenues for modeling and visualizing higher-order chromatin structure.

Data availability

All raw data will be made available at GEO Accession GSE162410; processed data is available at Zenodo (https://doi.org/10.5281/zenodo.3834705). All scripts and notebooks for reproducing analyses in the paper are available at https://github.com/RamaniLab/SAMOSA.

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

Article and author information

Author details

  1. Nour J Abdulhay

    Biochemistry & Biophysics, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  2. Colin P McNally

    Biochemistry & Biophysics, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  3. Laura J Hsieh

    Biochemistry & Biophysics, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  4. Sivakanthan Kasinathan

    Pediatrics, Stanford University, Palo Alto, United States
    Competing interests
    No competing interests declared.
  5. Aidan Keith

    Biochemistry & Biophysics, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  6. Laurel S Estes

    Biochemistry & Biophysics, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  7. Mehran Karimzadeh

    Vector Institute, Toronto, Canada
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7324-6074
  8. Jason G Underwood

    Pacific Biosciences of California, Inc, Menlo Park, United States
    Competing interests
    Jason G Underwood, J.G.U. is an employee of Pacific Biosciences, Inc. and holds stock in this company..
  9. Hani Goodarzi

    Biochemistry & Biophysics, University of California San Francisco, San Francisco, United States
    Competing interests
    No competing interests declared.
  10. Geeta J Narlikar

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Competing interests
    Geeta J Narlikar, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1920-0147
  11. Vijay Ramani

    Biochemistry & Biophysics, University of California, San Francisco, San Francisco, United States
    For correspondence
    vijay.ramani@ucsf.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3345-5960

Funding

Sandler Foundation

  • Vijay Ramani

American Cancer Society

  • Laura J Hsieh

National Institutes of Health (R01GM123977)

  • Hani Goodarzi

National Institutes of Health (R35GM127020)

  • Geeta J Narlikar

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

Copyright

© 2020, Abdulhay 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. Nour J Abdulhay
  2. Colin P McNally
  3. Laura J Hsieh
  4. Sivakanthan Kasinathan
  5. Aidan Keith
  6. Laurel S Estes
  7. Mehran Karimzadeh
  8. Jason G Underwood
  9. Hani Goodarzi
  10. Geeta J Narlikar
  11. Vijay Ramani
(2020)
Massively multiplex single-molecule oligonucleosome footprinting
eLife 9:e59404.
https://doi.org/10.7554/eLife.59404

Share this article

https://doi.org/10.7554/eLife.59404

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