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Xiao M, Liu X, Ji J, Li M, Li J, Yang L, Sun W, Ren P, Yang G, Zhao J, Liang T, Ren H, Chen T, Zhong H, Song W, Wang Y, Deng Z, Zhao Y, Ou Z, Wang D, Cai J, Cheng X, Feng T, Wu H, Gong Y, Yang H, Wang J, Xu X, Zhu S, Chen F, Zhang Y, Chen W, Li Y, Li J. Multiple approaches for massively parallel sequencing of SARS-CoV-2 genomes directly from clinical samples. Genome Med 2020; 12:57. [PMID: 32605661 PMCID: PMC7325194 DOI: 10.1186/s13073-020-00751-4] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 06/10/2020] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. METHODS We applied a novel multiplex PCR amplicon (amplicon)-based 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 SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. RESULTS We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. CONCLUSIONS This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses.
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Affiliation(s)
- Minfeng Xiao
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | - Xiaoqing Liu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jingkai Ji
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Min Li
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Jiandong Li
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Lin Yang
- MGI, BGI-Shenzhen, Shenzhen, 518083, China
| | - Wanying Sun
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Peidi Ren
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Jincun Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Institute of Infectious Disease, Guangzhou Eighth People's Hospital of Guangzhou Medical University, Guangzhou, China
| | - Tianzhu Liang
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Tian Chen
- MGI, BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Wenchen Song
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | - Yanqun Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziqing Deng
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | - Yanping Zhao
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | - Zhihua Ou
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | - Daxi Wang
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Xinyi Cheng
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | | | - Honglong Wu
- BGI PathoGenesis Pharmaceutical Technology, Shenzhen, China
| | - Yanping Gong
- BGI PathoGenesis Pharmaceutical Technology, Shenzhen, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Science, Hangzhou, 310008, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen, 518083, China
- James D. Watson Institute of Genome Science, Hangzhou, 310008, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, 518120, China
| | - Shida Zhu
- BGI-Shenzhen, Shenzhen, 518083, China
- Shenzhen Engineering Laboratory for Innovative Molecular Diagnostics, BGI-Shenzhen, Shenzhen, 518120, China
| | - Fang Chen
- BGI-Shenzhen, Shenzhen, 518083, China
- MGI, BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Weijun Chen
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China.
- BGI PathoGenesis Pharmaceutical Technology, Shenzhen, China.
| | - Yimin Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
| | - Junhua Li
- BGI-Shenzhen, Shenzhen, 518083, China.
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 518083, China.
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
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