Effects of sample processing modes on high-throughput sequencing of coronavirus whole genome/ 不同样本测序前处理方案对冠状病毒基因组高通量测序结果的影响

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.