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Updated: Sep 13, 2025

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
Published on: March 25, 2020
Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution
Ryuya Edahiro1,2,3, Go Sato4,5,6, Tatsuhiko Naito4,5
1Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. r.edahiro@imed3.med.osaka-u.ac.jp.
Abstract:
Current molecular quantitative trait locus catalogs are mostly at bulk resolution and centered on Europeans. Here, we constructed an immune cell atlas with single-cell transcriptomics of >1.5 million peripheral blood mononuclear cells, host genetics, plasma proteomics and gut metagenomics from 235 Japanese persons, including patients with coronavirus disease 2019 (COVID-19) and healthy individuals. We mapped germline genetic effects on gene expression within immune cell types and across cell states. We elucidated cell type- and context-specific human leukocyte antigen (HLA) and genome-wide associations with T and B cell receptor repertoires. Colocalization using dynamic genetic regulation provided better understanding of genome-wide association signals. Differential gene and protein expression analyses depicted cell type- and context-specific effects of polygenic risks. Various somatic mutations including mosaic chromosomal alterations, loss of Y chromosome and mitochondrial DNA (mtDNA) heteroplasmy were projected into single-cell resolution. We identified immune features specific to somatically mutated cells. Overall, immune cells are dynamically regulated in a cell state-dependent manner characterized with multiomic profiles.
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