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      Analytical validity of nanopore sequencing for rapid SARS-CoV-2 genome analysis

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          Abstract

          Viral whole-genome sequencing (WGS) provides critical insight into the transmission and evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Long-read sequencing devices from Oxford Nanopore Technologies (ONT) promise significant improvements in turnaround time, portability and cost, compared to established short-read sequencing platforms for viral WGS (e.g., Illumina). However, adoption of ONT sequencing for SARS-CoV-2 surveillance has been limited due to common concerns around sequencing accuracy. To address this, here we perform viral WGS with ONT and Illumina platforms on 157 matched SARS-CoV-2-positive patient specimens and synthetic RNA controls, enabling rigorous evaluation of analytical performance. We report that, despite the elevated error rates observed in ONT sequencing reads, highly accurate consensus-level sequence determination was achieved, with single nucleotide variants (SNVs) detected at >99% sensitivity and >99% precision above a minimum ~60-fold coverage depth, thereby ensuring suitability for SARS-CoV-2 genome analysis. ONT sequencing also identified a surprising diversity of structural variation within SARS-CoV-2 specimens that were supported by evidence from short-read sequencing on matched samples. However, ONT sequencing failed to accurately detect short indels and variants at low read-count frequencies. This systematic evaluation of analytical performance for SARS-CoV-2 WGS will facilitate widespread adoption of ONT sequencing within local, national and international COVID-19 public health initiatives.

          Abstract

          Nanopore sequencing (ONT) has been used in SARS-CoV-2 studies, however adoption of ONT for SARS-CoV-2 surveillance has been limited due to common concerns around sequencing accuracy. Here, the authors perform a comprehensive evaluation of ONT analytical performance on 157 matched SARS-CoV-2-positive patient specimens and synthetic RNA controls.

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

              Summary Background In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. Methods We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. Findings The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. Interpretation 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. Funding National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.
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                Author and article information

                Contributors
                i.deveson@garvan.org.au
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                9 December 2020
                9 December 2020
                2020
                : 11
                : 6272
                Affiliations
                [1 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, The Kirby Institute for Infection and Immunity, University of New South Wales, ; Sydney, NSW Australia
                [2 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Medical Sciences, Faculty of Medicine, University of New South Wales, ; Sydney, NSW Australia
                [3 ]GRID grid.415306.5, ISNI 0000 0000 9983 6924, Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, ; Sydney, NSW Australia
                [4 ]GRID grid.413249.9, ISNI 0000 0004 0385 0051, NSW Health Pathology, Department of Infectious Diseases and Microbiology, , Royal Prince Alfred Hospital, ; Sydney, NSW Australia
                [5 ]GRID grid.415193.b, Virology Research Laboratory, Serology and Virology Division (SAViD), NSW Health Pathology, Prince of Wales Hospital, ; Sydney, NSW Australia
                [6 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Computer Science and Engineering, University of New South Wales, ; Sydney, NSW Australia
                [7 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Women’s and Children’s Health, Faculty of Medicine, University of New South Wales, ; Sydney, NSW Australia
                [8 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, Marie Bashir Institute for Infectious Diseases and Biosecurity & Sydney Medical School, The University of Sydney, ; Sydney, NSW Australia
                [9 ]GRID grid.452919.2, ISNI 0000 0001 0436 7430, Centre for Virus Research, Westmead Institute for Medical Research, ; Sydney, NSW Australia
                [10 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, ; Sydney, NSW Australia
                [11 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, Central Clinical School, University of Sydney, ; Sydney, NSW Australia
                [12 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, St Vincent’s Clinical School, Faculty of Medicine, University of New South Wales, ; Sydney, NSW Australia
                Author information
                http://orcid.org/0000-0002-6192-6937
                http://orcid.org/0000-0002-4045-4571
                http://orcid.org/0000-0002-7713-1979
                http://orcid.org/0000-0002-9034-9905
                http://orcid.org/0000-0003-1374-3551
                http://orcid.org/0000-0001-5852-4155
                http://orcid.org/0000-0003-3861-0472
                Article
                20075
                10.1038/s41467-020-20075-6
                7726558
                33298935
                5365305a-7949-47a4-8cdf-62648f0293fc
                © Crown 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 July 2020
                : 11 November 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001171, Cancer Institute NSW (Cancer Institute New South Wales);
                Funded by: Medical Research Futures Fund, Investigator Grant APP1173594 Cancer Institute NSW, Early Career Fellowship 2018/ECF013
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                © The Author(s) 2020

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                next-generation sequencing,viral genetics
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                next-generation sequencing, viral genetics

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