Abstract
Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection.
【초록키워드】 COVID-19, coronavirus disease, Coronavirus disease 2019, Gene Expression, severe COVID-19, eQTL, variant, COVID-19 severity, Infectious disease, Regulatory, COVID-19 infection, Whole blood, Japan, phenotype, Japanese, disease, eQTLs, expression, Quantitative, mechanism, Differential gene expression, Analysis, COVID-19 cases, deaths, Task Force, Regulation, increased expression, expression quantitative trait loci, functions, loci, RNA-seq data, differential gene expression analysis, force, single variant, independent, highlight, transcriptional, CLEC4C, COVID-19 phenotype, MYBL2, STING1, TOR1AIP1, evaluate, caused, example, provide, genotyped, COVID-19 infected individual, QTL, REST, splice, 【제목키워드】 COVID-19, Whole blood, Japan, transcriptional regulation, force,