Host, Viral, and Environmental Transcriptome Profiles of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

Daniel J Butler; Christopher Mozsary; Cem Meydan; David C Danko; Jonathan Foox; Joel Rosiene; Alon Shaiber; Ebrahim Afshinnekoo; Matthew MacKay; Fritz J Sedlazeck; Nikolay A Ivanov; Maria A Sierra; Diana Pohle; Michael Zeitz; Vijendra Ramlall; Undina Gisladottir; Craig D Westover; Krista Ryon; Benjamin Young; Chandrima Bhattacharya; Phyllis Ruggiero; Bradley W Langhorst; Nathan A Tanner; Justyn Gawrys; Dmitry Meleshko; Dong Xu; Jenny Xiang; Angelika Iftner; Daniela Bezdan; John Sipley; Lin Cong; Arryn Craney; Priya Velu; Ari Melnick; Iman A Hajirasouliha; Thomas Iftner; Mirella Salvatore; Massimo Loda; Lars F Westblade; Shawn Levy; Melissa Cushing; Nicholas P Tatonetti; Marcin Imielinski; Hanna Rennert; Christopher Mason

To provide orthogonal validation of our LAMP assay and further investigate the biological characteristics of clinical SARS-Cov2+ positive and negative samples, we developed a shotgun metatranscriptomics platform utilizing total RNA-seq (RNA-sequencing with ribosomal RNA depletion) to comprehensively profile human, microbial, fungal, and viral RNAs. We aligned total RNA-seq reads to several NCBI databases and classified those of non-human origin using Kraken2 (Wood et al., 2019) . Applying this platform to a full set of 338 COVID-19 specimens (including the 199 tested with LAMP), we obtained an average of 63.2M read pairs per total RNA-seq library.