Single-Cell Genomics Elucidates Molecular Variations and Regulatory Mechanisms in Circulating Immune Cells
Yin, J.; Zheng, Y.; Huang, Z.; Zhou, W.; Yuan, Y.; Cai, P.; Bai, Y.; Yang, S.; Gao, Y.; Duan, S.; Wang, Y.; Zhang, W.; Zhang, X.; Wei, Y.; Xu, Z.; Huang, Y.; Liu, Y.; Wang, W.; Yang, T.; Lv, J.; Zhang, Z.; Chen, X.; Zhang, X.; Li, F.; Zhang, Y.; Zeng, G.; Wang, X.; Ma, W.; Hou, G.; Hao, S.; Liu, C.; Lai, Y.; Wang, B.; Li, Y.; Zhang, W.; Gao, P.; Xie, J.; Esteban, M. A.; Gu, Y.; Ji, J.; Qi, T.; Liu, B.; Wang, J.; Yang, J.; Xu, X.; Liu, L.; Jin, X.; Liu, C.
Show abstract
The human peripheral blood displays diverse molecular characteristics across populations, understanding the drivers and underlying mechanisms of which remains challenging. Here, we introduce the Chinese Immune Multi-Omics Atlas (CIMA), elucidating sex-, age-, and genetic-related molecular variations by analyzing multi-omics data from 428 adults with over 10 million immune cells. CIMA generated an enhancer-driven gene regulatory network, identifying 237 high-quality regulons and revealing cell type-specific regulatory mechanisms. Additionally, 11,521 lead cis-expression quantitative trait loci (eQTLs) and 46,339 chromatin accessibility QTLs (caQTLs) were identified at cell type level. CIMA also uncovered pleiotropic associations among immune-related disease risk loci, eQTLs, and caQTLs in a cell type-specific manner. Lastly, a novel cell language model, CIMA-CLM, was developed to predict chromatin accessibility and noncoding variant effects using chromatin sequences and gene expressions. This work represents a population-scale multi-omics resource of human immune cells, providing a valuable reference for future investigation of immune-related diseases.
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