Generation and Functional Analysis of Defective Viral Genomes during SARS-CoV-2 Infection
Discipline: Data Science
Session: 1
Room: 5 - Embassy A
Nora J. Gilliam - University of Rochester School of Medicine and Dentistry, NY, USA
Co-Author(s): Terry Zhou, University of Rochester School of Medicine and Dentistry, NY, USA; Sizhen Li, Oregon State University, OR, USA; Simone Spandau, University of Rochester School of Medicine and Dentistry, NY, USA; Raven M. Osborn, University of Rochester School of Medicine and Dentistry, NY, USA; Sarah Connor, University of Rochester School of Medicine and Dentistry, NY, USA; Christopher S. Anderson, University of Rochester School of Medicine and Dentistry, NY, USA; Thomas J. Mariani, University of Rochester School of Medicine and Dentistry, NY, USA; Juilee Thakar, University of Rochester School of Medicine and Dentistry, NY, USA; Stephen Dewhurst, University of Rochester School of Medicine and Dentistry, NY, USA; David H. Mathews, University of Rochester School of Medicine and Dentistry, NY, USA; Liang Huang, Oregon State University, OR, USA; Yan Sun, University of Rochester School of Medicine and Dentistry, NY, USA
Defective viral genomes (DVGs) are a critical factor influencing RNA viral pathogenesis and host innate immunity and are considered a new approach in antiviral therapeutics and vaccine development. During viral genome replication, several RNA products are generated from nonhomologous recombination by viral polymerase: subgenomic mRNAs, structural variants, and DVGs are some of these such products. DVGs are therefore truncated forms of viral genomes. When generated at high levels, DVGs can interfere with full-length viral genome production by sequestering essential viral elements from full-length viruses, as demonstrated in previous studies on DVG generation in various non-coronaviruses. However, the generation and function of DVGs during infection of SARS-CoV-2 are less known. In this study, we employed a DVG-specific pipeline using the analysis tool ViReMa (virus recombination mapper) and RStudio filtering to 1) identify SARS-CoV-2 DVGs in publicly available next-generation sequencing (NGS) datasets, and 2) functionally analyze SARS-COV-2 DVGs’ role in host immune responses both in vitro and in COVID-19 patients. Our findings show DVGs are ubiquitously generated in selected RNA-seq datasets of in vitro infections, autopsy lung tissues of COVID-19 patients. To further validate ViReMa-extracted DVG junction reads, 15 randomly selected DVG sequences were verified using BLAST+ for orientation and junction positions, with all reads matching or closely aligning with ViReMa-identified junction sites. Normalized DVG levels, measured as junction frequency (Jfreq = total DVG count/total viral read counts) were mostly <0.1% in both autopsy tissue and cell lines with a positive correlation between total DVG count and viral read counts in autopsy tissues (p 100) compared to low (<50) and mid counts, suggesting a positive correlation between DVG abundance and immune-stimulation. Finally, we observed a significantly higher amount of DVG counts and Jfreq (p <0.001 and p <0.0001 respectively, by two-sided Mann-Whitney U test) in symptomatic COVID-19 patients compared to asymptomatic patients in the NGS public cohort dataset. Together, our findings elucidate the first evidence regarding the critical role of DVGs in modulating host IFN responses and symptom development during SARS-CoV-2 infection. Hence, further inquiry into the effect of DVG-driven immunomodulation, and thus host immunocompetence, on COVID-19 severity is needed.
Funder Acknowledgement(s): This work was supported by the University of Rochester Institutional Program Unifying Population and Laboratory Based Sciences Award from the Burroughs Wellcome Fund, Request ID 1014095; National Center for Advancing Translational Sciences, TL1-TR002000; NIH-NHLBI Human Tissue Core (Gloria Pryhuber, Principal Investigator, U01 HL148861and U01 HL148861-S1) for the Lung Molecular Atlas Program; University of Rochester Technology Development Fund, OP346177; University of Rochester School of Medicine and Dentistry Scientific Advisory Committee Incubator Award; University of Rochester HSCCI OP211341; University of Rochester School of Medicine and Dentistry OP211968; NIH grant T32GM007356-44 to N.J.G.; and NIH grant R35GM145283 to D.H.M.
Faculty Advisor: Yan Sun, PhD, yan_sun@urmc.rochester.edu
Role: DVG analysis and graphing for all bulk RNA-seq, DVG analysis and graphing for tiled-PCR sequencing, manuscript writing