Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Genome-wide profiling of nucleosome position and chromatin accessibility in single cells using scMNase-seq

Nature Protocols volume 15, pages 68–85 (2020)Cite this article

Subjects

Abstract

Nucleosome organization is important for chromatin compaction and accessibility. Profiling nucleosome positioning genome-wide in single cells provides critical information to understand the cell-to-cell heterogeneity of chromatin states within a cell population. This protocol describes single-cell micrococcal nuclease sequencing (scMNase-seq), a method for detecting genome-wide nucleosome positioning and chromatin accessibility simultaneously from a small number of cells or single cells. To generate scMNase-seq libraries, single cells are isolated by FACS sorting, lysed and digested by MNase. DNA is purified, end-repaired and ligated to Y-shaped adaptors. Following PCR amplification with indexing primers, the subnucleosome-sized (fragments with a length of ≤80 bp) and mononucleosome-sized (fragments with a length between 140 and 180 bp) DNA fragments are recovered and sequenced on Illumina HiSeq platforms. On average, 0.5–1 million unique mapped reads are obtained for each single cell. The mononucleosome-sized DNA fragments precisely define genome-wide nucleosome positions in single cells, while the subnucleosome-sized DNA fragments provide information on chromatin accessibility. Library preparation of scMNase-seq takes only 2 d, requires only standard molecular biology techniques and does not require sophisticated laboratory equipment. Processing of high-throughput sequencing data requires basic bioinformatics skills and uses publicly available bioinformatics software.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Workflow illustration of the scMNase-seq protocol.
Fig. 2: Dead or apoptotic cells exhibit chromatin fragmentation without MNase digestion.
Fig. 3: MNase titration using bulk cells.
Fig. 4: Gel image showing the size range of scMNase-seq library DNA after PCR amplification.
Fig. 5: Average profiling of nucleosomes and subnucleosomes from pooled single cells.

Similar content being viewed by others

Data availability

Data used in this protocol have been deposited in the Gene Expression Omnibus database with accession number GSE96688. Figure 5 is associated with the raw data. There are no restrictions on data availability.

Code availability

Codes used in this protocol have been deposited in GitHub (https://github.com/binbinlai2012/scMNase). There are no restrictions on code availability.

References

  1. Kornberg, R. D. & Lorch, Y. Twenty-five years of the nucleosome, fundamental particle of the eukaryote chromosome. Cell 98, 285–294 (1999).

    Article  CAS  Google Scholar 

  2. Li, B., Carey, M. & Workman, J. L. The role of chromatin during transcription. Cell 128, 707–719 (2007).

    Article  CAS  Google Scholar 

  3. Lai, W. K. M. & Pugh, B. F. Understanding nucleosome dynamics and their links to gene expression and DNA replication. Nat. Rev. Mol. Cell Biol. 18, 548–562 (2017).

    Article  CAS  Google Scholar 

  4. Hodges, C. et al. Nucleosomal fluctuations govern the transcription dynamics of RNA polymerase II. Science 325, 626–628 (2009).

    Article  CAS  Google Scholar 

  5. Zhang, Z. et al. A packing mechanism for nucleosome organization reconstituted across a eukaryotic genome. Science 332, 977–980 (2011).

    Article  CAS  Google Scholar 

  6. Kaplan, N. et al. The DNA-encoded nucleosome organization of a eukaryotic genome. Nature 458, 362–366 (2009).

    Article  CAS  Google Scholar 

  7. Jiang, C. & Pugh, B. F. Nucleosome positioning and gene regulation: advances through genomics. Nat. Rev. Genet. 10, 161–172 (2009).

    Article  CAS  Google Scholar 

  8. Luger, K. Structure and dynamic behavior of nucleosomes. Curr. Opin. Genet. Dev. 13, 127–135 (2003).

    Article  CAS  Google Scholar 

  9. Lai, B. B. et al. Principles of nucleosome organization revealed by single-cell micrococcal nuclease sequencing. Nature 562, 281–285 (2018).

    Article  CAS  Google Scholar 

  10. Schones, D. E. et al. Dynamic regulation of nucleosome positioning in the human genome. Cell 132, 887–898 (2008).

    Article  CAS  Google Scholar 

  11. Pott, S. & Lieb, J. D. Single-cell ATAC-seq: strength in numbers. Genome Biol. 16, 172 (2015).

    Article  Google Scholar 

  12. Cooper, J. et al. Genome-wide mapping of DNase I hypersensitive sites in rare cell populations using single-cell DNase sequencing. Nat. Protoc. 12, 2342–2354 (2017).

    Article  CAS  Google Scholar 

  13. Jin, W. F. et al. Genome-wide detection of DNase I hypersensitive sites in single cells and FFPE tissue samples. Nature 528, 142–146 (2015).

    Article  CAS  Google Scholar 

  14. Baldi, S. Nucleosome positioning and spacing: from genome-wide maps to single arrays. Essays Biochem 63, 5–14 (2019).

    Article  Google Scholar 

  15. Liang, J., Cai, W. & Sun, Z. S. Single-cell sequencing technologies: current and future. J. Genet. Genomics 41, 513–528 (2014).

    Article  Google Scholar 

  16. Hoeijmakers, W. A. M. & Bartfai, R. Characterization of the nucleosome landscape by micrococcal nuclease-sequencing (MNase-seq). Methods Mol. Biol. 1689, 83–101 (2018).

    Article  CAS  Google Scholar 

  17. Kelsey, G., Stegle, O. & Reik, W. Single-cell epigenomics: recording the past and predicting the future. Science 358, 69–75 (2017).

    Article  CAS  Google Scholar 

  18. Shema, E., Bernstein, B. E. & Buenrostro, J. D. Single-cell and single-molecule epigenomics to uncover genome regulation at unprecedented resolution. Nat. Genet. 51, 19–25 (2019).

    Article  CAS  Google Scholar 

  19. Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015).

    Article  CAS  Google Scholar 

  20. Pott, S. Simultaneous measurement of chromatin accessibility, DNA methylation, and nucleosome phasing in single cells. eLife 6, 061739 (2017).

    Article  Google Scholar 

  21. Clark, S. J. et al. scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat. Commun. 9, 781 (2018).

    Article  Google Scholar 

  22. Li, L. et al. Single-cell multi-omics sequencing of human early embryos. Nat. Cell Biol. 20, 847–858 (2018).

    Article  CAS  Google Scholar 

  23. Buenrostro, J. D. et al. Transposition of native chromatin for fast and sensitive mulitmodal analysis of chromatin architecture. Biophys. J. 106, 77a (2014).

    Article  Google Scholar 

  24. Buenrostro, J. D. et al. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

    Article  CAS  Google Scholar 

  25. Cusanovich, D. A. et al. Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910–914 (2015).

    Article  CAS  Google Scholar 

  26. Klein, A. M. & Macosko, E. InDrops and Drop-seq technologies for single-cell sequencing. Lab Chip 17, 2540–2541 (2017).

    Article  CAS  Google Scholar 

  27. Perfetto, S. P. et al. Amine-reactive dyes for dead cell discrimination in fixed samples. Curr. Protoc. Cytom. 53, 9.34.1–9.34.14 (2010).

    Article  Google Scholar 

  28. Cui, K. & Zhao, K. Genome-wide approaches to determining nucleosome occupancy in metazoans using MNase-Seq. Methods Mol. Biol. 833, 413–419 (2012).

    Article  CAS  Google Scholar 

  29. Gross, A. et al. Technologies for single-cell isolation. Int. J. Mol. Sci. 16, 16897–16919 (2015).

    Article  CAS  Google Scholar 

  30. Kircher, M., Sawyer, S. & Meyer, M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 40, e3 (2011).

    Article  Google Scholar 

  31. Langmead, B. & Salzberg, S. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  Google Scholar 

  32. Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  33. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank the National Heart, Lung, and Blood Institute DNA Sequencing Core Facility for sequencing the libraries and the National Heart, Lung, and Blood Institute Flow Cytometry Core facility for sorting the cells. The work was supported by the Division of Intramural Research, National Heart, Lung and Blood Institute (K.Z.), the National Key Research and Development Project (no. 2016YFA0502203) (B.N.), the General Program of National Natural Science Foundation of China (no. 81670534) (B.N.), and the Medical Scientific and Technological Innovation Funds of Southwest Hospital (no. SWH2016LHYS-04) (B.N.).

Author information

Authors and Affiliations

  1. Department of Pathophysiology, College of High Altitude Military Medicine, Third Military Medical University, Chongqing, People’s Republic of China

    Weiwu Gao & Bing Ni

  2. Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute, NIH, Bethesda, MD, USA

    Weiwu Gao, Binbin Lai & Keji Zhao

  3. Institute of Immunology of PLA, Third Military Medical University, Chongqing, People’s Republic of China

    Weiwu Gao

  4. Key Laboratory of Extreme Environmental Medicine, Ministry of Education of China, Chongqing, People’s Republic of China

    Weiwu Gao & Bing Ni

Authors
  1. Weiwu Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Binbin Lai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bing Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Keji Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.Z. and B.N. directed the project. W.G. performed the experiments. B.L. analyzed the data. W.G., B.L. and K.Z. wrote the manuscript.

Corresponding authors

Correspondence to Bing Ni or Keji Zhao.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Protocols thanks Gonçalo Castelo-Branco, Emily Hodges and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related link

Key references using this protocol

Lai, B. et al. Nature 562, 281–285 (2018): https://doi.org/10.1038/s41586-018-0567-3

Integrated supplementary information

Supplementary Fig. 1 FACS sorting of single cells by FSC versus SSC gating.

Formaldehyde-fixed mouse naïve T cells (100,000) were submitted for FACS sorting based on size and granularity (FSC vs SSC, P1 gate), and cell doublets were excluded firstly by SSC-H vs SSC-W (P2 gate) and further by FSC-H vs FSC-W (P3 gate).

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Supplementary Table 1.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, W., Lai, B., Ni, B. et al. Genome-wide profiling of nucleosome position and chromatin accessibility in single cells using scMNase-seq. Nat Protoc 15, 68–85 (2020). https://doi.org/10.1038/s41596-019-0243-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-019-0243-6

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing