A single-cell atlas of chromatin accessibility in the human genome
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Abstract
Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of gene regulatory elements in diverse cell types and tissues in the human body, we applied single-cell chromatin accessibility assays to 30 adult human tissue types from multiple donors. We integrated these datasets with previous single-cell chromatin accessibility data from 15 fetal tissue types to reveal the status of open chromatin for ∼1.2 million candidate cis-regulatory elements (cCREs) in 222 distinct cell types comprised of >1.3 million nuclei. We used these chromatin accessibility maps to delineate cell-type-specificity of fetal and adult human cCREs and to systematically interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems.
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DNase-seq and ChIP-seq from ENCODE and the Epigenomics Roadmap and pseudo-bulk single-cell ATAC-seq from CATlas focus the model towards distal regulatory elements.
“as well as DNase-seq and ChIP–seq from ENCODE and the Epigenomics Roadmap31,99 and pseudo-bulk single-cell ATAC–seq data from CATlas100,101, which focuses the model towards distal regulatory elements.”
From Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation (2025) · cites this paper as [100]
Public human liver scATAC-seq data reveal that predicted Tbx3 and Tcf7l1 repressive sites are conserved between species, with similar accessibility patterns along the porto-central axis.
“As a third validation experiment, we analyzed a public human liver scATAC-seq data set62, revealing that the predicted Tbx3 and Tcf7l1 repressive sites are conserved between species, with similar accessibility patterns along the porto-central axis (Fig 5j).”
From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [62]
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- Authors
- Zhang, K., Hocker, J. D., Miller, M., Hou, X., Chiou, J., Poirion, O. B., Qiu, Y., Li, Y. E., Gaulton, K. J., Wang, A., Preissl, S., & Ren, B.
- Affiliations
- University of California San Diego (US)
- Ludwig Cancer Research (US)
- Corresponding author
- Ren, Bing
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 184
- Issue
- 24
- Pages
- 5985-6001.e19
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC8664161
- OpenAlex
- W3214158901
- Cited by
- 502
- References
- 28
- Citations by year
- 2026: 94 · 2025: 123 · 2024: 125 · 2023: 91 · 2022: 65 · 2021: 4
- FWCI
- 23.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- School of Medicine, University of California, San Diego
- Genentech
- National Human Genome Research Institute (3U54HG006997-04S2)
- National Institutes of Health (T32 GM008666, AMP T2D RFP 14)
- Ludwig Institute for Cancer Research
- FNIH
- Broad Institute
- National Institute of General Medical Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- chromatin accessibility, single-cell chromatin accessibility, cis-regulatory elements, gene regulatory elements, cell type specificity, fetal tissue, non-coding variants, human qualities, human disease
- MeSH terms
- Adult, Chromatin, Fetus, Humans, Organ Specificity, Phylogeny, Regulatory Sequences, Nucleic Acid, Risk Factors, Genetic Variation, Genome, Human, Cluster Analysis, Genome-Wide Association Study, Single-Cell Analysis
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