Network-based analysis revealed significant interactions between risk genes of severe COVID-19 and host genes interacted with SARS-CoV-2 proteins.

生物 2019年冠状病毒病(COVID-19) 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 基因 计算生物学 2019-20冠状病毒爆发 病毒学 冠状病毒 遗传学 病毒 爆发
作者
Hao-Xiang Qi,Qi-Dong Shen,Hong-Yi Zhao,Guo-Zhen Qi,Lei Gao
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
标识
DOI:10.1093/bib/bbab372
摘要

Whether risk genes of severe coronavirus disease 2019 (COVID-19) from genome-wide association study could play their regulatory roles by interacting with host genes that were interacted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator (https://github.com/Haoxiang-Qi/Network-Calculator.git). By using Network Calculator, we identified a network composed of 13 risk genes and 28 SARS-CoV-2 interacted host genes that had the highest network proximity with each other, with a hub gene HNRNPK identified. Among these genes, 14 of them were identified to be differentially expressed in RNA-seq data from severe COVID-19 cases. Besides, by expression enrichment analysis in single-cell RNA-seq data, compared with mild COVID-19, these genes were significantly enriched in macrophage, T cell and epithelial cell for severe COVID-19. Meanwhile, 74 pathways were significantly enriched. Our analysis provided insights for the underlying genetic etiology of severe COVID-19 from the perspective of network biology.

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