Researchers curate RNA-Seq datasets to develop an interactive portal for intuitive investigation on SARS-CoV-2 related transcriptomes

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans could cause coronavirus disease 2019 (COVID-19). Since its first discovery in Dec 2019, SARS-CoV-2 has become a global pandemic and caused 3.3 million direct/indirect deaths (2021 May). Amongst the scientific community’s response to COVID-19, data sharing has emerged as an essential aspect of the combat against SARS-CoV-2. Despite the ever-growing studies about SARS-CoV-2 and COVID-19, to date, only a few databases were curated to enable access to gene expression data. Furthermore, these databases curated only a small set of data and do not provide easy access for investigators without computational skills to perform analyses.

To fill this gap and advance open-access to the growing gene expression data on this deadly virus, researchers from St. Jude Children’s Research Hospital, collected about 1,500 human bulk RNA-seq datasets from publicly available resources, developed a database and visualization tool, named CovidExpress. This open access database will allow research investigators to examine the gene expression in various tissues, cell lines, and their response to SARS-CoV-2 under different experimental conditions, accelerating the understanding of the etiology of this disease in order to inform the drug and vaccine development. Our integrative analysis of this big dataset highlights a set of commonly regulated genes in SARS-CoV-2 infected lung and nasal tissues, including OASL that were under-studied in COVID-19 related reports. Our results also suggested a potential FURIN positive feedback loop that might explain the evolutional advantage of SARS-CoV-2.

Availabilityhttps://stjudecab.github.io/covidexpress

Djekidel MN, Rosikiewicz W, Peng JC, Kanneganti TD, Hui Y, Jin H, Hedges D, Schreiner P, Fan Y, Wu G, Xu B. (2021) CovidExpress: an interactive portal for intuitive investigation on SARS-CoV-2 related transcriptomes. bioRXiv [online preprint]. [abstract]

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