Reconstructing SARS-CoV-2 response signaling and regulatory networks

BioRxiv : the Preprint Server for Biology
Jun DingZiv Bar-Joseph

Abstract

Several molecular datasets have been recently compiled to characterize the activity of SARS-CoV-2 within human cells. Here we extend computational methods to integrate several different types of sequence, functional and interaction data to reconstruct networks and pathways activated by the virus in host cells. We identify the key proteins in these networks and further intersect them with genes differentially expressed at conditions that are known to impact viral activity. Several of the top ranked genes do not directly interact with virus proteins though some were shown to impact other coronaviruses highlighting the importance of large-scale data integration for understanding virus and host activity. Software and interactive visualization: https://github.com/phoenixding/sdremsc.

Datasets Mentioned

BETA
GSE153277

Methods Mentioned

BETA
RNA-seq
scRNA-Seq

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