Multiple approaches for massively parallel sequencing of HCoV-19 (SARS-CoV-2) genomes directly from clinical samples

Xiao, Minfeng; Liu, Xiaoqing; Ji, Jingkai; Li, Min; Li, Jiandong; Yang, Lin; Sun, Wanying; Ren, Peidi; Yang, Guifang; Zhao, Jincun; Liang, Tianzhu; Ren, Huahui; Chen, Tian; Zhong, Huanzi; Song, Wenchen; Wang, Yanqun; Deng, Ziqing; Zhao, Yanping; Ou, Zhihua; Wang, Daxi; Cai, Jielun; Cheng, Xinyi; Feng, Taiqing; Wu, Honglong; Gong, Yanping; Yang, Huanming; Wang, Jian; Xu, Xun; Zhu, Shida; Chen, Fang; Zhang, Yanyan; Chen, Weijun; Li, Yimin; Li, Junhua

COVID-19 has caused a major epidemic worldwide, however, much is yet to be known about the epidemiology and evolution of the virus. One reason is that the challenges underneath sequencing HCoV-19 directly from clinical samples have not been completely tackled. Here we illustrate the application of amplicon and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of HCoV-19 from clinical samples covering a range of sample types and viral load. We also examine and compare the bias, sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. This is, to date, the first work systematically implements amplicon and capture approaches in sequencing HCoV-19, as well as the first comparative study across methods. Our work offers practical solutions for genome sequencing and analyses of HCoV-19 and other emerging viruses.