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Costanzi JM, Stosic MS, Løvestad AH, Ambur OH, Rounge TB, Christiansen IK. Changes in intrahost genetic diversity according to lesion severity in longitudinal HPV16 samples. J Med Virol 2024; 96:e29641. [PMID: 38708811 DOI: 10.1002/jmv.29641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 04/17/2024] [Accepted: 04/21/2024] [Indexed: 05/07/2024]
Abstract
Human papillomavirus type 16 (HPV16) is the most common cause of cervical cancer, but most infections are transient with lesions not progressing to cancer. There is a lack of specific biomarkers for early cancer risk stratification. This study aimed to explore the intrahost HPV16 genomic variation in longitudinal samples from HPV16-infected women with different cervical lesion severity (normal, low-grade, and high-grade). The TaME-seq deep sequencing protocol was used to generate whole genome HPV16 sequences of 102 samples collected over time from 40 individuals. Single nucleotide variants (SNVs) and intrahost SNVs (iSNVs) were identified in the viral genomes. A majority of individuals had a unique set of SNVs and these SNVs were stable over time. Overall, the number of iSNVs and APOBEC3-induced iSNVs were significantly lower in high-grade relative to normal and low-grade samples. A significant increase in the number of APOBEC3-induced iSNVs over time was observed for normal samples when compared to high-grade. Our results indicates that the lower incidence of iSNVs and APOBEC3-induced iSNVs in high-grade lesions may have implications for novel biomarkers discoveries, potentially aiding early stratification of HPV-induced cervical precancerous lesions.
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Affiliation(s)
- Jean-Marc Costanzi
- Department of Microbiology and Infection Control, Akershus University Hospital, Lørenskog, Norway
- Centre of Bioinformatics, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Milan S Stosic
- Department of Microbiology and Infection Control, Akershus University Hospital, Lørenskog, Norway
- Department of Life Sciences and Health, Faculty of Health Sciences, OsloMet-Oslo Metropolitan University, Oslo, Norway
| | - Alexander H Løvestad
- Department of Microbiology and Infection Control, Akershus University Hospital, Lørenskog, Norway
- Department of Life Sciences and Health, Faculty of Health Sciences, OsloMet-Oslo Metropolitan University, Oslo, Norway
- Clinical Molecular Biology (EpiGen), Akershus University Hospital Lørenskog, Norway and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole H Ambur
- Department of Life Sciences and Health, Faculty of Health Sciences, OsloMet-Oslo Metropolitan University, Oslo, Norway
| | - Trine B Rounge
- Centre of Bioinformatics, Department of Pharmacy, University of Oslo, Oslo, Norway
- Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway
| | - Irene K Christiansen
- Department of Microbiology and Infection Control, Akershus University Hospital, Lørenskog, Norway
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2
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Makhsous N, Goya S, Avendaño CC, Rupp J, Kuypers J, Jerome KR, Boeckh M, Waghmare A, Greninger AL. Within-Host Rhinovirus Evolution in Upper and Lower Respiratory Tract Highlights Capsid Variability and Mutation-Independent Compartmentalization. J Infect Dis 2024; 229:403-412. [PMID: 37486790 PMCID: PMC10873175 DOI: 10.1093/infdis/jiad284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/13/2023] [Accepted: 07/17/2023] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND Rhinovirus (RV) infections can progress from the upper (URT) to lower (LRT) respiratory tract in immunocompromised individuals, causing high rates of fatal pneumonia. Little is known about how RV evolves within hosts during infection. METHODS We sequenced RV complete genomes from 12 hematopoietic cell transplant patients with infection for up to 190 days from both URT (nasal wash, NW) and LRT (bronchoalveolar lavage, BAL). Metagenomic and amplicon next-generation sequencing were used to track the emergence and evolution of intrahost single nucleotide variants (iSNVs). RESULTS Identical RV intrahost populations in matched NW and BAL specimens indicated no genetic adaptation is required for RV to progress from URT to LRT. Coding iSNVs were 2.3-fold more prevalent in capsid over nonstructural genes. iSNVs modeled were significantly more likely to be found in capsid surface residues, but were not preferentially located in known RV-neutralizing antibody epitopes. Newly emergent, genotype-matched iSNV haplotypes from immunocompromised individuals in 2008-2010 could be detected in Seattle-area community RV sequences in 2020-2021. CONCLUSIONS RV infections in immunocompromised hosts can progress from URT to LRT with no specific evolutionary requirement. Capsid proteins carry the highest variability and emergent mutations can be detected in other, including future, RV sequences.
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Affiliation(s)
- Negar Makhsous
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Stephanie Goya
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Carlos C Avendaño
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Jason Rupp
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Jane Kuypers
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
| | - Keith R Jerome
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA
| | - Michael Boeckh
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA
- Department of Medicine, University of Washington, Seattle, USA
| | - Alpana Waghmare
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA
- Department of Pediatrics, University of Washington, Seattle, USA
| | - Alexander L Greninger
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, USA
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3
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Kimbrel J, Moon J, Avila-Herrera A, Martí JM, Thissen J, Mulakken N, Sandholtz SH, Ferrell T, Daum C, Hall S, Segelke B, Arrildt KT, Messenger S, Wadford DA, Jaing C, Allen JE, Borucki MK. Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples. Viruses 2022; 14:v14122775. [PMID: 36560780 PMCID: PMC9788161 DOI: 10.3390/v14122775] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/23/2022] [Accepted: 12/06/2022] [Indexed: 12/15/2022] Open
Abstract
Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, "Mappgene", was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.
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Affiliation(s)
- Jeffrey Kimbrel
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Joseph Moon
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | | | - James Thissen
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Nisha Mulakken
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | - Tyshawn Ferrell
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Chris Daum
- Lawrence Berkeley National Laboratory, US Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | - Sara Hall
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Brent Segelke
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | - Sharon Messenger
- Viral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, CA 94804, USA
| | - Debra A. Wadford
- Viral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, CA 94804, USA
| | - Crystal Jaing
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | - Monica K. Borucki
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
- Correspondence:
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4
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Huo S, Hai Y, Guo Y, Nie L, Li H, Qiao P, Zong K, Li X, Guo Y, Song J, Zhao H, Lei W, Lan Y, Liu WJ, Gao GF. Intra-host variation and evolutionary dynamics of adenoviruses correlate to neutrophils in infected patients. J Med Virol 2022; 94:3863-3875. [PMID: 35355288 DOI: 10.1002/jmv.27744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 03/26/2022] [Accepted: 03/30/2022] [Indexed: 11/10/2022]
Abstract
With deep sequencing of virus genomes within the hosts, intra-host single nucleotide variations (iSNVs) have been used for analyses of virus genome variation and evolution, which is indicated to correlate with viral pathogenesis and disease severity. Little is known about the features of iSNVs among DNA viruses. We performed the epidemiological and laboratory investigation of one outbreak of adenovirus. The whole genomes of viruses in both original oral swabs and cell-cultured virus isolates were deeply sequenced. We identified 737 iSNVs in the viral genomes sequenced from original samples and 46 viral iSNVs in cell cultured isolates, with 33 iSNVs shared by original samples and cultured isolates. Meanwhile, we found these 33 iSNVs were shared by different patients, among which, three hot-spot areas 6367-6401, 9213-9247 and 10584-10606 within the functional genes of the adenovirus genome were found. Notably, the substitution rates of iSNVs were closely correlated with the clinical and immune indicators of the patients. Especially a positive correlation to neutrophils was found, indicating a predictable biomarker of iSNV dynamics. Our findings demonstrated the neutrophil-correlated dynamic evolution features of the iSNVs within adenoviruses, which indicates a virus-host interaction during human infection of a DNA virus. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Shuting Huo
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, China.,NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Yan Hai
- Inner Mongolia Center for Disease Control and Prevention, Hohhot, 010031, China
| | - Yaxin Guo
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Li Nie
- Tongliao Center for Disease Control and Prevention, Tongliao, 028000, China
| | - Hongmei Li
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, China.,NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Peiwen Qiao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Kexin Zong
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, China.,NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Xin Li
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, China.,NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Yuanyuan Guo
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China.,School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing, 211816, China
| | - Jingdong Song
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China.,State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Honglan Zhao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Wenwen Lei
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Yu Lan
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - William J Liu
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, China.,NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - George F Gao
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, China.,NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China.,CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
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5
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Zhu Z, Liu G, Meng K, Yang L, Liu D, Meng G. Rapid Spread of Mutant Alleles in Worldwide SARS-CoV-2 Strains Revealed by Genome-Wide Single Nucleotide Polymorphism and Variation Analysis. Genome Biol Evol 2021; 13:evab015. [PMID: 33512495 PMCID: PMC7883668 DOI: 10.1093/gbe/evab015] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [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] [Accepted: 01/22/2021] [Indexed: 12/13/2022] Open
Abstract
The novel coronavirus (SARS-CoV-2) has become a pandemic and is threatening human health globally. Here, we report nine newly evolved SARS-CoV-2 single nucleotide polymorphism (SNP) alleles those underwent a rapid increase (seven cases) or decrease (two cases) in their frequency for 30-80% in the initial four months, which are further confirmed by intrahost single nucleotide variation analysis using raw sequence data including 8,217 samples. The nine SNPs are mostly (8/9) located in the coding region and are mainly (6/9) nonsynonymous substitutions. The nine SNPs show a complete linkage in SNP pairs and belong to three different linkage groups, named LG_1 to LG_3. Analyses in population genetics show signatures of adaptive selection toward the mutants in LG_1, but no signal of selection for LG_2. Population genetic analysis results on LG_3 show geological differentiation. Analyses on geographic COVID-19 cases and published clinical data provide evidence that the mutants in LG_1 and LG_3 benefit virus replication and those in LG_1 have a positive correlation with the disease severity in COVID-19-infected patients. The mutants in LG_2 show a bias toward mildness of the disease based on available public clinical data. Our findings may be instructive for epidemiological surveys and disease control of COVID-19 in the future.
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Affiliation(s)
- Zhenglin Zhu
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Gexin Liu
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Kaiwen Meng
- College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Liuqing Yang
- Chongqing Occupational Disease Prevention Hospital, Chongqing, China
| | - Di Liu
- CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for 25 Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, China
| | - Geng Meng
- College of Veterinary Medicine, China Agricultural University, Beijing, China
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6
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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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