Effects of sample processing modes on high-throughput sequencing of coronavirus whole genome

Abstract

Objective To study the effects of different pre-sequencing sample processing modes on the results of whole genome sequencing with high-throughput sequencing (HTS) by taking the largest RNA virus (human coronavirus, HCoV) as the representative. Methods Cell-cultured human coronavirus HCoV-OC43 strains were used as the representative samples and divided into different groups based on pre-sequencing processing modes as follows: untreated group, DNase and RNase treatment before nucleic acid extraction group, DNase treatment after nucleic acid extraction group, and DNase and RNase treatment before nucleic acid extraction and DNase treatment after nucleic acid extraction group. Nucleic acid samples of each group were analyzed by direct RNA sequencing (without amplification) and DNA sequencing after sequence independent single primer amplification (SISPA), respectively. Results No significant difference in viral genome coverage rates was observed between different groups. The highest genome coverage and sequencing accuracy were obtained in DNase treatment after nucleic acid extraction group by direct RNA sequencing, and the ratio of viral reads and the sequencing depth of each locus were effectively improved by SISPA amplification. Conclusions This study provided an optimized technical strategy for whole genome sequencing of RNA viruses such as coronavirus. Key words: Human coronavirus; Sequence independent single primer amplification; Whole genome sequencing; High-throughput sequencing