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MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples

Chen Chen, Jizhou Li, Lin Di, Qiuyu Jing, Pengcheng Du, Chuan Song, Jiarui Li, Qiong Li, Yunlong Cao, X. Sunney Xie, View ORCID ProfileAngela R. Wu, Hui Zeng, Yanyi Huang, Jianbin Wang
doi: https://doi.org/10.1101/2020.04.25.060947
Chen Chen
aInstitute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University and Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
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Jizhou Li
bSchool of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
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Lin Di
cBeijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
dSchool of Life Sciences, Peking University, Beijing 100871, China
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Qiuyu Jing
eDivision of Life Science, Hong Kong University of Science and Technology, Hong Kong SAR, China
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Pengcheng Du
aInstitute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University and Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
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Chuan Song
aInstitute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University and Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
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Jiarui Li
aInstitute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University and Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
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Qiong Li
bSchool of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
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Yunlong Cao
cBeijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
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X. Sunney Xie
cBeijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
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Angela R. Wu
eDivision of Life Science, Hong Kong University of Science and Technology, Hong Kong SAR, China
fDepartment of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, China
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  • ORCID record for Angela R. Wu
Hui Zeng
aInstitute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University and Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China
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  • For correspondence: jianbinwang@tsinghua.edu.cn yanyi@pku.edu.cn zenghui@ccmu.edu.cn
Yanyi Huang
cBeijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
gCollege of Chemistry and Molecular Engineering, Beijing 100871, China
hInstitute for Cell Analysis, Shenzhen Bay Laboratory, Guangdong 518132, China
iChinese Institute for Brain Research (CIBR), Beijing 102206, China
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  • For correspondence: jianbinwang@tsinghua.edu.cn yanyi@pku.edu.cn zenghui@ccmu.edu.cn
Jianbin Wang
bSchool of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
iChinese Institute for Brain Research (CIBR), Beijing 102206, China
jBeijing Advanced Innovation Center for Structural Biology (ICSB), Tsinghua University, Beijing 100084, China
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  • For correspondence: jianbinwang@tsinghua.edu.cn yanyi@pku.edu.cn zenghui@ccmu.edu.cn
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Abstract

The novel coronavirus disease 2019 (COVID-19) pandemic poses a serious public health risk. Analyzing the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from clinical samples is crucial for the understanding of viral spread and viral evolution, as well as for vaccine development. Existing sample preparation methods for viral genome sequencing are demanding on user technique and time, and thus not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance on viral genomes. We have developed MetagenomIc RNA EnRichment VirAl sequencing (MINERVA), a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. This approach uses direct tagmentation of RNA/DNA hybrids using Tn5 transposase to greatly simplify the sequencing library construction process, while subsequent targeted enrichment can generate viral genomes with high sensitivity, coverage, and depth. We demonstrate the utility of MINERVA on pharyngeal, sputum and stool samples collected from COVID-19 patients, successfully obtaining both whole metatranscriptomes and complete high-depth high-coverage SARS-CoV-2 genomes from these clinical samples, with high yield and robustness. MINERVA is compatible with clinical nucleic extracts containing carrier RNA. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate monitoring of viral genetic variations during outbreaks, both current and future.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted April 25, 2020.
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MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples
Chen Chen, Jizhou Li, Lin Di, Qiuyu Jing, Pengcheng Du, Chuan Song, Jiarui Li, Qiong Li, Yunlong Cao, X. Sunney Xie, Angela R. Wu, Hui Zeng, Yanyi Huang, Jianbin Wang
bioRxiv 2020.04.25.060947; doi: https://doi.org/10.1101/2020.04.25.060947
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MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples
Chen Chen, Jizhou Li, Lin Di, Qiuyu Jing, Pengcheng Du, Chuan Song, Jiarui Li, Qiong Li, Yunlong Cao, X. Sunney Xie, Angela R. Wu, Hui Zeng, Yanyi Huang, Jianbin Wang
bioRxiv 2020.04.25.060947; doi: https://doi.org/10.1101/2020.04.25.060947

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