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Article
License: CC BY
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Nature Biotechnology
Article . 2019 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
https://doi.org/10.1101/610550...
Article . 2019 . Peer-reviewed
Data sources: Crossref
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Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion

Authors: Ansuman T. Satpathy; Jeffrey M. Granja; Kathryn E. Yost; Yanyan Qi; Francesca Meschi; Geoffrey P. McDermott; Brett N. Olsen; +15 Authors

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

Abstract

AbstractUnderstanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here we present a massively parallel droplet-based platform for mapping transposase-accessible chromatin in tens of thousands of single cells per sample (scATAC-seq). We obtain and analyze chromatin profiles of over 200,000 single cells in two primary human systems. In blood, scATAC-seq allows marker-free identification of cell type-specificcis- andtrans-regulatory elements, mapping of disease-associated enhancer activity, and reconstruction of trajectories of differentiation from progenitors to diverse and rare immune cell types. In basal cell carcinoma, scATAC-seq reveals regulatory landscapes of malignant, stromal, and immune cell types in the tumor microenvironment. Moreover, scATAC-seq of serial tumor biopsies before and after PD-1 blockade allows identification of chromatin regulators and differentiation trajectories of therapy-responsive intratumoral T cell subsets, revealing a shared regulatory program driving CD8+T cell exhaustion and CD4+T follicular helper cell development. We anticipate that droplet-based single-cell chromatin accessibility will provide a broadly applicable means of identifying regulatory factors and elements that underlie cell type and function.

Keywords

T-Lymphocytes, High-Throughput Nucleotide Sequencing, Bone Marrow Cells, Chromatin, Cell Line, Hematopoiesis, Gene Expression Regulation, Leukocytes, Mononuclear, Humans, Computer Simulation, Single-Cell Analysis, Transcription Factors

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    857
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.01%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.01%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
857
Top 0.01%
Top 1%
Top 0.01%
Green
bronze