Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes

基于上下文感知的单细胞多组学方法可识别细胞类型特异性肺癌易感基因

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作者:Erping Long # ,Jinhu Yin # ,Ju Hye Shin # ,Yuyan Li # ,Bolun Li ,Alexander Kane ,Harsh Patel ,Xinti Sun ,Cong Wang ,Thong Luong ,Jun Xia ,Younghun Han ,Jinyoung Byun ,Tongwu Zhang ,Wei Zhao ,Maria Teresa Landi ,Nathaniel Rothman ,Qing Lan ,Yoon Soo Chang ,Fulong Yu ,Christopher I Amos ,Jianxin Shi ,Jin Gu Lee ,Eun Young Kim ,Jiyeon Choi

Abstract

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.

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