Single-cell chromatin accessibility reveals principles of regulatory variation

  • Nature volume 523, pages 486490 (23 July 2015)
  • doi:10.1038/nature14590
  • Download Citation


Cell-to-cell variation is a universal feature of life that affects a wide range of biological phenomena, from developmental plasticity1,2 to tumour heterogeneity3. Although recent advances have improved our ability to document cellular phenotypic variation4,5,6,7,8, the fundamental mechanisms that generate variability from identical DNA sequences remain elusive. Here we reveal the landscape and principles of mammalian DNA regulatory variation by developing a robust method for mapping the accessible genome of individual cells by assay for transposase-accessible chromatin using sequencing (ATAC-seq)9 integrated into a programmable microfluidics platform. Single-cell ATAC-seq (scATAC-seq) maps from hundreds of single cells in aggregate closely resemble accessibility profiles from tens of millions of cells and provide insights into cell-to-cell variation. Accessibility variance is systematically associated with specific trans-factors and cis-elements, and we discover combinations of trans-factors associated with either induction or suppression of cell-to-cell variability. We further identify sets of trans-factors associated with cell-type-specific accessibility variance across eight cell types. Targeted perturbations of cell cycle or transcription factor signalling evoke stimulus-specific changes in this observed variability. The pattern of accessibility variation in cis across the genome recapitulates chromosome compartments10 de novo, linking single-cell accessibility variation to three-dimensional genome organization. Single-cell analysis of DNA accessibility provides new insight into cellular variation of the ‘regulome’.

  • Subscribe to Nature for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


Primary accessions

Gene Expression Omnibus

Data deposits

All data has been deposited in GEO under the accession number GSE65360. Fluidigm C1 scripts for performing scATAC-seq are available at https://www.fluidigm.com/c1openapp/scripthub/script/2015-06/single-cell-chromatin-accessib-1433443631246-1.


  1. 1.

    , , , & Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 453, 544–547 (2008)

  2. 2.

    et al. Oscillatory control of factors determining multipotency and fate in mouse neural progenitors. Science 342, 1203–1208 (2013)

  3. 3.

    et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396–1401 (2014)

  4. 4.

    et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687–696 (2011)

  5. 5.

    , , & Variability in gene expression underlies incomplete penetrance. Nature 463, 913–918 (2010)

  6. 6.

    et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343, 776–779 (2014)

  7. 7.

    et al. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nature Methods 11, 817–820 (2014)

  8. 8.

    , , & Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338, 1622–1626 (2012)

  9. 9.

    , , , & Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nature Methods 10, 1213–1218 (2013)

  10. 10.

    et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009)

  11. 11.

    et al. Dynamics of chronic myeloid leukaemia. Nature 435, 1267–1270 (2005)

  12. 12.

    ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012)

  13. 13.

    et al. The accessible chromatin landscape of the human genome. Nature 489, 75–82 (2012)

  14. 14.

    & Tn5 in vitro transposition. J. Biol. Chem. 273, 7367–7374 (1998)

  15. 15.

    et al. Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. Genome Biol. 11, R119 (2010)

  16. 16.

    ENCODE Project Consortium. User’s guide to the Encyclopedia of DNA Elements (ENCODE). PLoS Biol. 9, e1001046 (2011)

  17. 17.

    et al. Architecture of the human regulatory network derived from ENCODE data. Nature 489, 91–100 (2012)

  18. 18.

    et al. Dynamic trans-acting factor colocalization in human cells. Cell 155, 713–724 (2013)

  19. 19.

    et al. Sequencing newly replicated DNA reveals widespread plasticity in human replication timing. Proc. Natl Acad. Sci. USA 107, 139–144 (2010)

  20. 20.

    et al. Cohesins functionally associate with CTCF on mammalian chromosome arms. Cell 132, 422–433 (2008)

  21. 21.

    et al. Single-cell NF-κB dynamics reveal digital activation and analogue information processing. Nature 466, 267–271 (2010)

  22. 22.

    , & Validation of noise models for single-cell transcriptomics. Nature Methods 11, 637–640 (2014)

  23. 23.

    et al. Dynamic heterogeneity and DNA methylation in embryonic stem cells. Mol. Cell 55, 319–331 (2014)

  24. 24.

    , & Frequency-modulated nuclear localization bursts coordinate gene regulation. Nature 455, 485–490 (2008)

  25. 25.

    , & Functional roles of pulsing in genetic circuits. Science 342, 1193–1200 (2013)

  26. 26.

    et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011)

  27. 27.

    , , , & Genome architectures revealed by tethered chromosome conformation capture and population-based modeling. Nature Biotechnol. 30, 90–98 (2012)

  28. 28.

    et al. Predictive polymer modeling reveals coupled fluctuations in chromosome conformation and transcription. Cell 157, 950–963 (2014)

Download references


This work was supported by National Institutes of Health (NIH) P50HG007735 (to H.Y.C. and W.J.G.), UH2 AR067676 and Lifespan Extension Foundation (H.Y.C.), U19AI057266 (to W.J.G.) and the Rita Allen Foundation (to W.J.G.) and the Baxter Foundation Faculty Scholar Grant (to W.J.G); H.Y.C. is an Early Career Scientist of the Howard Hughes Medical Institute. J.D.B. acknowledges support from the National Science Foundation Graduate Research Fellowships and NIH training grant T32HG000044 for support. M.P.S. acknowledges the NIH and the National Human Genome Research Institute (NHGRI) for funding through 5U54HG00455805. We thank members of Greenleaf and Chang laboratories, as well as the Fluidigm team, including L. Xi for discussions. We acknowledge the S. Kim laboratory for assistance with FACS sorting and the C. Bustamante laboratory for help with sequencing. We also thank R. Nichols, C. Mazumdar, V. Sebastiano and V. Risca for cells.

Author information

Author notes

    • Beijing Wu
    •  & Ulrike M. Litzenburger

    These authors contributed equally to this work.


  1. Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA

    • Jason D. Buenrostro
    • , Beijing Wu
    • , Michael P. Snyder
    •  & William J. Greenleaf
  2. Program in Epithelial Biology and the Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California 94305, USA

    • Jason D. Buenrostro
    • , Ulrike M. Litzenburger
    •  & Howard Y. Chang
  3. Fluidigm Corporation, South San Francisco, California 94080, USA

    • Dave Ruff
    •  & Michael L. Gonzales
  4. Department of Applied Physics, Stanford University, Stanford, California 94025, USA

    • William J. Greenleaf


  1. Search for Jason D. Buenrostro in:

  2. Search for Beijing Wu in:

  3. Search for Ulrike M. Litzenburger in:

  4. Search for Dave Ruff in:

  5. Search for Michael L. Gonzales in:

  6. Search for Michael P. Snyder in:

  7. Search for Howard Y. Chang in:

  8. Search for William J. Greenleaf in:


J.D.B., H.Y.C. and W.J.G. conceived of the method. J.D.B., B.W., M.G. and D.R. developed the Fluidigm C1 microfluidic protocols. B.W. performed all scATAC-seq experiments with supervision from J.D.B. U.M.L. conducted the flow analysis, immunostains and drug treatments. J.D.B. developed and implemented the analysis infrastructure with input from W.J.G. All authors interpreted the data and wrote the manuscript. W.J.G. and H.Y.C. supervised all aspects of this work.

Competing interests

Stanford University has filed a provisional patent application on the methods described, and J.D.B., H.Y.C. and W.J.G. are named as inventors. D.R. and M.L.G. declare competing financial interests as employees of Fluidigm Corp.

Corresponding authors

Correspondence to Howard Y. Chang or William J. Greenleaf.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Methods Text and Data, a Supplementary Discussion and additional references (see Contents list for details).

Excel files

  1. 1.

    Supplementary Tables

    This file contains Supplementary Table 1.

  2. 2.

    Supplementary Tables

    This file contains Supplementary Table 2.

Zip files

  1. 1.

    Supplementary Data

    This file contains Supplementary Data.


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.