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Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion
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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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“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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“Cells were filtered, keeping those with a TSS enrichment of at least five and more than 1,000 unique fragments.”
From Heme induces innate immune memory (2019) · cites this paper as [58]
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Metadata
- 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.
- ORCID
- Venue
- Nature Biotechnology
- Published
- 2019-08
- Volume
- 37
- Issue
- 8
- Pages
- 925-936
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC7299161
- 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
- green
- doi.org
- 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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