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

S Sydney Kuhl (Allen Institute for Immunology) U Upaasana Krishnan A Andreas Tjaernberg (Allen Institute for Brain Science) M Morgan Weiss (Allen Institute for Immunology) J Jane Bucker (Benaroya Research Institute) C Cate Speake A Alan DenAdel (Allen Institute for Immunology) E Emma Kuan (Allen Institute for Immunology) T Troy Torgerson (Allen Institute for Immunology) T Tom Bumol (Allen Institute for Immunology) P Peter Skene (Allen Institute for Immunology) M Mariano Gabitto (Allen Institute for Brain Science) M Mark-Phillip Pebworth Z Ziyuan He (Allen Institute for Immunology) M Marla Glass (Allen Institute for Immunology) C Claire Gustafson (Allen Institute for Immunology) X Xiao-Jun Li

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)

Article Details

Volume / Issue Vol. 215, Issue Supplement_1
Published August 01, 2026
ISSN 0022-1767
Publisher American Association of Immunologists

Authors (17)

S

Sydney Kuhl

Allen Institute for Immunology

U

Upaasana Krishnan

A

Andreas Tjaernberg

Allen Institute for Brain Science

M

Morgan Weiss

Allen Institute for Immunology

J

Jane Bucker

Benaroya Research Institute

C

Cate Speake

A

Alan DenAdel

Allen Institute for Immunology

E

Emma Kuan

Allen Institute for Immunology

T

Troy Torgerson

Allen Institute for Immunology

T

Tom Bumol

Allen Institute for Immunology

P

Peter Skene

Allen Institute for Immunology

M

Mariano Gabitto

Allen Institute for Brain Science

M

Mark-Phillip Pebworth

Z

Ziyuan He

Allen Institute for Immunology

M

Marla Glass

Allen Institute for Immunology

C

Claire Gustafson

Allen Institute for Immunology

X

Xiao-Jun Li