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作者

Qi, Hao-xiang 1 Shen, Qi-dong 1 Zhao, Hong-yi 1 Qi, Guo-zhen 1 Gao, Lei 1

作者单位

Department of Bioinformatics, School of Life Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an 271099, Shandong, China

刊名

Briefings in Bioinformatics

年份

2022

卷号

Vol.23 No.1

页码

bbab372

ISSN

1467-5463

关键词

severe COVID-19 network risk genes SARS-CoV-2 interacted host genes cell types.

摘要

Whether risk genes of severe coronavirus disease 2019 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 proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator . By using Network Calculator, we identified a network composed of 13 risk genes and 28 SARS-CoV-2 interacted host genes ...更多

Whether risk genes of severe coronavirus disease 2019 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 proteins was worthy of exploration. In this study, we implemented a network-based approach by developing a user-friendly software Network Calculator . 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.收起

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