Cell type-specific eQTL analysis of COVID-19 based on single-cell transcriptomic data

Genome-wide association study analysis has revealed the significant influence of genetic factors in the progression of COVID-19. However, the impact of these genetic variants on gene expression in various cell types remains largely unexplored. Here, we profiled immune cells from 42 COVID-19 cases (involving five stages) and 11 healthy individuals, and performed a single-cell RNA-seq assay with >200 000 cells to investigate cell type-specific and stage-specific genetic effects of genetic variants. Single-cell expression quantitative trait loci analysis of eight distinct cell types showed that the expression of 2593 genes is significantly associated with common genetic polymorphisms, and that the majority of these genes show their most prominent effects in specific cell types. Furthermore, we also discovered new gene associations for COVID-19-risk variants identified from genome-wide association studies and highlighted the monocytes in which their effects are most prominent. We found that 57 genes were regulated by variants associated with COVID-19, with significant enrichment for dynamic effects. In summary, our results highlight the importance of studying context-specific genetic regulation of gene expression and provide insights into the mechanisms underlying genetic susceptibility to COVID-19.

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Publication Details

Journal
NAR Genomics and Bioinformatics
Published
2025-10-07
DOI
https://doi.org/10.1093/nargab/lqaf130
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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Cell type-specific eQTL analysis of COVID-19 based on single-cell transcriptomic data

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Single-cell and spatial transcriptomics
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Cell type-specific eQTL analysis of COVID-19 based on single-cell transcriptomic data

Zijun Zhu, Duoyi Zhang, Miao‐qiao Du, Liang Cheng, Chao Wang, Hailong Li, Sainan Zhang, Sin Lam Tan, Xinyu Chen, Jingqiao Bai, Guanzhi He
article en

Abstract

Genome-wide association study analysis has revealed the significant influence of genetic factors in the progression of COVID-19. However, the impact of these genetic variants on gene expression in various cell types remains largely unexplored. Here, we profiled immune cells from 42 COVID-19 cases (involving five stages) and 11 healthy individuals, and performed a single-cell RNA-seq assay with >200 000 cells to investigate cell type-specific and stage-specific genetic effects of genetic variants. Single-cell expression quantitative trait loci analysis of eight distinct cell types showed that the expression of 2593 genes is significantly associated with common genetic polymorphisms, and that the majority of these genes show their most prominent effects in specific cell types. Furthermore, we also discovered new gene associations for COVID-19-risk variants identified from genome-wide association studies and highlighted the monocytes in which their effects are most prominent. We found that 57 genes were regulated by variants associated with COVID-19, with significant enrichment for dynamic effects. In summary, our results highlight the importance of studying context-specific genetic regulation of gene expression and provide insights into the mechanisms underlying genetic susceptibility to COVID-19.

NAR Genomics and BioinformaticsVol. 7(4)
Harbin Medical University (CN), Second Affiliated Hospital of Harbin Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 75%
Single-cell and spatial transcriptomics
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