High Resolution Single-Cell Epigenetic Atlas of Immune Cell Types Reveals Gene Regulatory Circuits in Healthy Humans 2308992

Abstract Introduction Single-cell chromatin accessibility (scATAC-seq) profiles genome-wide regulatory elements that shape immune cell identity and function, but its interpretation is currently limited by low cell type resolution and small reference datasets. Existing datasets annotate fewer than 20 immune cell types and are too coarse to resolve heterogeneity and characterize cell type-specific gene regulatory programs and functions. Here, we present a large-scale scATAC-seq resource that substantially improves immune cell annotation and regulatory inference. Methods By integrating matched-donor scRNA-seq and scATAC-seq data from human peripheral blood mononuclear cells (PBMCs) with trimodal TEA-seq (single-cell ATAC, RNA, and surface protein), we classified 36 immune cell types, including 4 myeloid, 6 B cell, 5 NK cell, 6 CD4 T cell, and 15 CD8 T cell subtypes. Cell frequencies from published scRNA-seq and new scATAC-seq labels were highly correlated (median ρ = 0.84). Labels were applied to our longitudinal multi-modal dataset of 206 samples spanning over 3 million PBMCs from 78 healthy human donors. Results We used these annotations to define baseline epigenetic states, age-associated differences, and epigenetic changes following influenza vaccination. Our analysis revealed extensive sets of differentially accessible tiles and enriched transcription factor motifs that define cell type-specific regulatory identities. Linking these chromatin regions and transcription factors to differentially expressed target genes enabled the construction of gene regulatory circuits associated with cell type, aging, and vaccination. Additionally, we trained a classification model for high resolution cell type labeling and doublet detection in new scATAC-seq datasets. Conclusion Together, this multi-modal atlas and associated cell type-labeling model provide an unprecedented reference for immune cell gene regulatory circuits and a valuable resource for exploring the epigenome of human immune cells. Funding Source n/a Topic Categories Computational and Systems Immunology (COMP)

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Publication Details

Journal
The Journal of Immunology
Published
2026-07-28
DOI
https://doi.org/10.1093/jimmun/vkag141.1486
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

High Resolution Single-Cell Epigenetic Atlas of Immune Cell Types Reveals Gene Regulatory Circuits in Healthy Humans 2308992

Tom Bumol, Alan DenAdel, Ziyuan He, Upaasana Krishnan et al.
The Journal of Immunology
Single-cell and spatial transcriptomics
article

High Resolution Single-Cell Epigenetic Atlas of Immune Cell Types Reveals Gene Regulatory Circuits in Healthy Humans 2308992

Tom Bumol, Alan DenAdel, Ziyuan He, Upaasana Krishnan, Peter Skene, Andreas Tjaernberg, Troy Torgerson, Sydney Kuhl, Mark-Phillip Pebworth, Cate Speake, Claire Gustafson, Mariano Gabitto, Morgan Weiss, Xiao-jun Li, Jane Bucker, Emma Kuan, Marla Glass
article en

Abstract

Abstract Introduction Single-cell chromatin accessibility (scATAC-seq) profiles genome-wide regulatory elements that shape immune cell identity and function, but its interpretation is currently limited by low cell type resolution and small reference datasets. Existing datasets annotate fewer than 20 immune cell types and are too coarse to resolve heterogeneity and characterize cell type-specific gene regulatory programs and functions. Here, we present a large-scale scATAC-seq resource that substantially improves immune cell annotation and regulatory inference. Methods By integrating matched-donor scRNA-seq and scATAC-seq data from human peripheral blood mononuclear cells (PBMCs) with trimodal TEA-seq (single-cell ATAC, RNA, and surface protein), we classified 36 immune cell types, including 4 myeloid, 6 B cell, 5 NK cell, 6 CD4 T cell, and 15 CD8 T cell subtypes. Cell frequencies from published scRNA-seq and new scATAC-seq labels were highly correlated (median ρ = 0.84). Labels were applied to our longitudinal multi-modal dataset of 206 samples spanning over 3 million PBMCs from 78 healthy human donors. Results We used these annotations to define baseline epigenetic states, age-associated differences, and epigenetic changes following influenza vaccination. Our analysis revealed extensive sets of differentially accessible tiles and enriched transcription factor motifs that define cell type-specific regulatory identities. Linking these chromatin regions and transcription factors to differentially expressed target genes enabled the construction of gene regulatory circuits associated with cell type, aging, and vaccination. Additionally, we trained a classification model for high resolution cell type labeling and doublet detection in new scATAC-seq datasets. Conclusion Together, this multi-modal atlas and associated cell type-labeling model provide an unprecedented reference for immune cell gene regulatory circuits and a valuable resource for exploring the epigenome of human immune cells. Funding Source n/a Topic Categories Computational and Systems Immunology (COMP)

The Journal of ImmunologyVol. 215(Supplement_1)
Allen Institute for Brain Science (US), Allen Institute for Immunology (US), Allen Institute (US), Benaroya Research Institute
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
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