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Characterizing cellular heterogeneity in chromatin state with scCUT&Tag-pro

Nature Biotechnology volume 40, pages 1220–1230 (2022)Cite this article

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Abstract

Technologies that profile chromatin modifications at single-cell resolution offer enormous promise for functional genomic characterization, but the sparsity of the measurements and integrating multiple binding maps represent substantial challenges. Here we introduce single-cell (sc)CUT&Tag-pro, a multimodal assay for profiling protein–DNA interactions coupled with the abundance of surface proteins in single cells. In addition, we introduce single-cell ChromHMM, which integrates data from multiple experiments to infer and annotate chromatin states based on combinatorial histone modification patterns. We apply these tools to perform an integrated analysis across nine different molecular modalities in circulating human immune cells. We demonstrate how these two approaches can characterize dynamic changes in the function of individual genomic elements across both discrete cell states and continuous developmental trajectories, nominate associated motifs and regulators that establish chromatin states and identify extensive and cell-type-specific regulatory priming. Finally, we demonstrate how our integrated reference can serve as a scaffold to map and improve the interpretation of additional scCUT&Tag datasets.

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Fig. 1: scCUT&Tag-pro enables simultaneous profiling of CUT&Tag and protein levels.
Fig. 2: Protein measurements facilitate integrated analysis across modalities.
Fig. 3: scChromHMM annotates chromatin states at single-cell resolution.
Fig. 4: Extensive heterogeneity in repressive chromatin encodes cellular identity.
Fig. 5: Supervised mapping of scCUT&Tag datasets.

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Data availability

Data generated for this manuscript have been deposited in the Gene Expression Omnibus with accession code GSE195725. The processed datasets are available as open-access downloads at https://zenodo.org/record/5504061. The following public datasets were used in this study: GSM4732109 and GSE164378 (Figs. 2,4 and Supplementary Fig. 3); GSM4732123 (Fig. 1d); GSM1220567, GSM1220569, GSM1027296 and GSM1102793 (Fig. 1g); and GSM5034342 and GSM5034344 (Supplementary Figs. 1c and Fig. 5). Datasets used in differential expression analysis with the bulk total RNA-seq were http://r2platform.com/rna_atlas and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138734.

Code availability

Seurat, Signac and scChromHMM are freely available as open-source software packages at https://github.com/satijalab/seurat, https://github.com/timoast/signac and https://github.com/satijalab/scchromhmm, respectively.

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Acknowledgements

We thank all the members of the Satija Lab for thoughtful discussions related to this work. B.Z. is a postdoctoral fellow of the Jane Coffin Childs Memorial Fund for Medical Research. This investigation has been aided by a grant from the Jane Coffin Childs Memorial Fund for Medical Research. This work was supported by the Chan Zuckerberg Initiative (grants EOSS-0000000082 and HCA-A-1704-01895 to R.S.) and the National Institutes of Health (grant K99CA267677-01 to A.S.; grant K99HG011489-01 to T.S.; and grants RM1HG011014-02, 1OT2OD026673-01 and DP2HG009623-01 to R.S.).

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  1. These authors contributed equally: Bingjie Zhang, Avi Srivastava.

Authors and Affiliations

  1. New York Genome Center, New York, NY, USA

    Bingjie Zhang, Avi Srivastava, Tim Stuart, Yuhan Hao & Rahul Satija

  2. Center for Genomics and Systems Biology, New York University, New York, NY, USA

    Bingjie Zhang, Avi Srivastava, Tim Stuart, Yuhan Hao & Rahul Satija

  3. Technology Innovation Lab, New York Genome Center, New York, NY, USA

    Eleni Mimitou, Ivan Raimondi & Peter Smibert

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Contributions

B.Z., A.S. and R.S. conceived the study. A.S., B.Z., T.S. and Y.H. performed computational work supervised by R.S.; B.Z., E.M. and I.R. performed experimental work supervised by R.S. All authors participated in interpretation and writing the manuscript.

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Correspondence to Rahul Satija.

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Competing interests

In the past three years, R.S. has worked as a consultant for Bristol Myers Squibb, Regeneron and Kallyope and served as scientific advisory board member for ImmunAI, Resolve Biosciences, NanoString and the NYC Pandemic Response Lab. P.S. is co-inventor of a patent related to this work. The other authors declare no competing interests.

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Nature Biotechnology thanks Barbara Treutlein, Goncalo Castelo-Branco, Anoop Patel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Zhang, B., Srivastava, A., Mimitou, E. et al. Characterizing cellular heterogeneity in chromatin state with scCUT&Tag-pro. Nat Biotechnol 40, 1220–1230 (2022). https://doi.org/10.1038/s41587-022-01250-0

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