Cited by 1,000Single-cell and spatial transcriptomicsGenomics and Chromatin DynamicsChromatin Remodeling and Cancer

Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion

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Satpathy, Ansuman T., Granja, Jeffrey M., Yost, Kathryn E., Qi, Yanyan, Meschi, Francesca, McDermott, Geoffrey P., Olsen, Brett N., Mumbach, Maxwell R. +14 more·2019·Nature Biotechnology

Published version of a preprint

Abstract

Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here, we assess the performance of a massively parallel droplet-based method for mapping transposase-accessible chromatin in single cells using sequencing (scATAC-seq). We apply scATAC-seq to obtain chromatin profiles of more than 200,000 single cells in human blood and basal cell carcinoma. In blood, application of scATAC-seq enables marker-free identification of cell type-specific cis- and trans-regulatory elements, mapping of disease-associated enhancer activity and reconstruction of trajectories of cellular differentiation. In basal cell carcinoma, application of scATAC-seq reveals regulatory networks in malignant, stromal and immune cells in the tumor microenvironment. Analysis of scATAC-seq profiles from serial tumor biopsies before and after programmed cell death protein 1 blockade identifies chromatin regulators of therapy-responsive T cell subsets and reveals a shared regulatory program that governs intratumoral CD8+ T cell exhaustion and CD4+ T follicular helper cell development. We anticipate that scATAC-seq will enable the unbiased discovery of gene regulatory factors across diverse biological systems.

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  • The scATAC-seq features used here were originally developed for non-perturbed cells, for purposes such as identifying cell types, discovering cell-type-specific regulatory elements, and reconstructing differentiation trajectories.

    “Note that these features were originally developed for scATAC-seq data on non-perturbed cells, with goals such as the identification of cell type, discovery of cell type-specific regulatory elements, or reconstruction of cellular differentiation trajectories43,61.”

    From scPerturb: harmonized single-cell perturbation data (2024) · cites this paper as [61]

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Authors
Satpathy, A. T., Granja, J. M., Yost, K. E., Qi, Y., Meschi, F., McDermott, G. P., Olsen, B. N., Mumbach, M. R., Pierce, S. E., Corces, M. R., Shah, P., Bell, J. C., Jhutty, D., Nemec, C. M., Wang, J., Wang, L., Yin, Y., Giresi, P. G., Chang, A. L. S., Zheng, G. X. Y., Greenleaf, W. J., & Chang, H. Y.
Affiliations
  • Stanford Medicine (US)
  • 10X Genomics (United States) (US)
  • Chan Zuckerberg Biohub San Francisco (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Zheng, Grace X. Y.
  • Greenleaf, William J.
  • Chang, Howard Y.
Venue
Nature Biotechnology
Published
2019-08
Volume
37
Issue
8
Pages
925-936
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W2965985232
Cited by
980
References
86
Citations by year
2026: 121 · 2025: 170 · 2024: 145 · 2023: 162 · 2022: 137 · 2021: 157 · 2020: 75 · 2019: 12
FWCI
33.66
Type
journal article
Language
en
Open access
Locations
  • Nature Biotechnology (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (K08CA23188-01, P50HG007735)
  • Parker Foundation
  • Howard Hughes Medical Institute
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
single-cell ATAC-seq, immune cell development, basal cell carcinoma, tumor microenvironment, T cell exhaustion, CD8+ T cells, enhancer activity, anti-PD-1 therapy, gene regulatory networks, next-generation sequencing
MeSH terms
Bone Marrow Cells, Cell Line, Chromatin, Computer Simulation, Gene Expression Regulation, Hematopoiesis, Humans, Leukocytes, Mononuclear, T-Lymphocytes, Transcription Factors, Single-Cell Analysis, High-Throughput Nucleotide Sequencing

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