Deciphering state-dependent immune features from multi-layer omics data at single-cell resolution

Area of Science:

• Immunology
• Genomics
• Proteomics
• Metagenomics

Background:

• Existing genetic trait locus catalogs lack single-cell resolution and diversity.
• Understanding immune cell regulation requires multiomic and diverse population data.

Purpose of the Study:

• To construct a high-resolution immune cell atlas using multiomic data from Japanese individuals.
• To investigate germline genetic effects on immune cell gene expression and T/B cell receptor repertoires.
• To explore somatic mutations and their impact on immune cell features.

Main Methods:

• Single-cell transcriptomics of over 1.5 million peripheral blood mononuclear cells.
• Integration of host genetics, plasma proteomics, and gut metagenomics data.
• Analysis of germline genetic effects, HLA and genome-wide associations, and somatic mutations.

Main Results:

• Mapped genetic effects on gene expression across immune cell types and states.
• Elucidated cell type- and context-specific genetic associations with T and B cell receptors.
• Identified immune features associated with somatic mutations like mtDNA heteroplasmy and mosaic chromosomal alterations.
• Revealed cell state-dependent immune cell regulation through multiomic profiles.

Conclusions:

• The study provides a comprehensive, single-cell resolution immune cell atlas from a diverse population.
• Germline and somatic genetic variations significantly influence immune cell function and repertoire.
• Immune cell dynamics are intricately regulated by cell state and multiomic interactions.