Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
Zigui Chen, Rita Way Yin Ng, Grace Lui, Lowell Ling, Chit Chow, Apple Chung Man Yeung, Siaw Shi Boon, Maggie Haitian Wang, Kate Ching Ching Chan, Renee W. Y. Chan, David S.C. Hui, Paul K.S. Chan
Abstract
Attempts to use subgenomic RNAs (sgRNAs) of SARS-CoV-2 to identify active infection of COVID-19 have produced diverse results. In this work, we applied next-generation sequencing and RT-PCR to profile the full spectrum of SARS-CoV-2 sgRNAs in a large cohort of respiratory and stool samples collected throughout infection. Numerous known and novel discontinuous transcription events potentially encoding full-length, deleted and frameshift proteins were observed. In particular, the expression profile of canonical sgRNAs was associated with genomic RNA level and clinical characteristics. Our study found sgRNAs as potential biomarkers for monitoring infectivity and progression of SARS-CoV-2 infection, which provides an alternative target for the management and treatment of COVID-19 patients.