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Exploring COVID-19 causal genes through disease-specific Cis-eQTLs.

Sainan Zhang, Ping Wang, Lei Shi, Chao Wang, Zijun Zhu, Changlu Qi, Yubin Xie, Shuofeng Yuan, Liang Cheng, Xin Yin, Xue Zhang

Virus research(2024)

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Abstract
Genome-wide association study (GWAS) analysis has exposed that genetic factors play important roles in COVID-19. Whereas a deeper understanding of the underlying mechanism of COVID-19 was hindered by the lack of expression of quantitative trait loci (eQTL) data specific for disease. To this end, we identified COVID-19-specific cis-eQTLs by integrating nucleotide sequence variations and RNA-Seq data from COVID-19 samples. These identified eQTLs have different regulatory effect on genes between patients and controls, indicating that SARS-CoV-2 infection may cause alterations in the human body's internal environment. Individuals with the TT genotype in the rs1128320 region seemed more susceptible to SARS-CoV-2 infection and developed into severe COVID-19 due to the abnormal expression of IFITM1. We subsequently discovered potential causal genes, of the result, a total of 48 genes from six tissues were identified. siRNA-mediated depletion assays in SARS-CoV-2 infection proved that 14 causal genes were directly associated with SARS-CoV-2 infection. These results enriched existing research on COVID-19 causal genes and provided a new sight in the mechanism exploration for COVID-19.
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Key words
COVID-19,Expression quantitative trait loci,Summary data-based mendelian randomization,siRNA transfection
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