Charting immune variation through genetics and single-cell genomics.

Area of Science:

• Immunology
• Genomics
• Computational Biology

Background:

• Existing human immune variation studies are often Eurocentric and lack detailed cell-type resolution or multi-modal data.
• Single-cell genomics has revolutionized understanding of immune cell diversity.

Purpose of the Study:

• To address gaps in immune cell genomics by creating a comprehensive multi-omics atlas of the Chinese population.
• To identify novel regulators of immune cell identity and function.

Main Methods:

• Profiling 428 healthy Chinese adults using integrated single-cell RNA sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq).
• Analyzing over 10 million immune cells to identify distinct subsets and construct gene regulatory networks.

Main Results:

• Identification of 73 distinct immune cell subsets.
• Construction of cell-type-specific gene regulatory networks linking enhancers to target genes.
• Delineation of hundreds of enhancer modules (eRegulons), revealing known and novel immune cell regulators.

Conclusions:

• The Chinese Immune Multi-Omics Atlas (CIMA) enhances global reference atlases by increasing ancestral diversity and data modalities.
• Aligning transcriptomic and epigenomic data reveals new insights into immune cell biology.
• This study highlights the importance of diverse populations and multi-omics approaches in immune cell genomics.