RNA-seq exploration of host responses and viral genomic diversity in SARS-CoV-2 infection

Abstract

Since the discovery of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there have been over 700 million cases and over 7 million deaths worldwide. Although some patients develop severe symptoms such as multiple system organ failure, others can be asymptomatic. This reflects the role of the immune system in disease progression. Although there exist standard PCR and antigen-based tests for SARS-CoV-2 detection and diagnostics, an important research goal is the identification of predictive biomarkers that are indicative of COVID-19 severity.

In this thesis, I performed bioinformatic analyses of two original RNA-seq datasets generated by collaborators to gain insights into the mechanisms and host responses of SARS-CoV-2 infection. The first dataset consisted of transcriptomic data from SARS-CoV-2 infected human lung cells as well as bat (Eptesicus fuscus) derived cells, providing insights into host responses of multiple mammalian species. The second dataset consisted of transcriptomic data from nasopharyngeal swabs collected from COVID-19 patients. A bioinformatic approach was used in both datasets to identify host genes that were up-regulated and down-regulated by SARS-CoV-2 infection as well as to identify biologically relevant viral mutations. The analysis resulted in the discovery of a novel R685P mutation in the SARS-CoV-2 spike glycoprotein, that had increased frequency in the Eptesicus fuscus derived cell line. Variant analysis from the clinical nasopharyngeal swab RNA-seq dataset also revealed the existence of a SARS-CoV-2 quasispecies containing multiple distinct viral genotypes with a unique population structure in each patient.

Despite each dataset being distinct, a similar bioinformatic analysis was applied to both datasets to reveal host response patterns and visualize the evolution and mutational spectrum of SARS-CoV-2. Although COVID-19 is no longer considered a global emergency, furthering our knowledge of the SARS-CoV-2 infection can aid in the development in new therapeutics and diagnostic tools.