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      SARS-CoV-2 variants associated with vaccine breakthrough in the Delaware Valley through summer 2021

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      research-article
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      medRxiv
      Cold Spring Harbor Laboratory
      SARS-CoV-2, COVID-19, coronavirus, genome sequencing, Philadelphia

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The severe acute respiratory coronavirus-2 (SARS-CoV-2) is the cause of the global outbreak of COVID-19. Evidence suggests that the virus is evolving to allow efficient spread through the human population, including vaccinated individuals. Here we report a study of viral variants from surveillance of the Delaware Valley, including the city of Philadelphia, and variants infecting vaccinated subjects. We sequenced and analyzed complete viral genomes from 2621 surveillance samples from March 2020 to September 2021 and compared them to genome sequences from 159 vaccine breakthroughs. In the early spring of 2020, all detected variants were of the B.1 and closely related lineages. A mixture of lineages followed, notably including B.1.243 followed by B.1.1.7 (alpha), with other lineages present at lower levels. Later isolations were dominated by B.1.617.2 (delta) and other delta lineages; delta was the exclusive variant present by the last time sampled. To investigate whether any variants appeared preferentially in vaccine breakthroughs, we devised a model based on Bayesian autoregressive moving average logistic multinomial regression to allow rigorous comparison. This revealed that B.1.617.2 (delta) showed three-fold enrichment in vaccine breakthrough cases (odds ratio of 3; 95% credible interval 0.89–11). Viral point substitutions could also be associated with vaccine breakthroughs, notably the N501Y substitution found in the alpha, beta and gamma variants (odds ratio 2.04; 95% credible interval of 1.25–3.18). This study thus provides a detailed picture of viral evolution in the Delaware Valley and a geographically matched analysis of vaccine breakthroughs; it also introduces a rigorous statistical approach to interrogating enrichment of viral variants.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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

                Journal
                medRxiv
                MEDRXIV
                medRxiv
                Cold Spring Harbor Laboratory
                17 November 2021
                : 2021.10.18.21264623
                Affiliations
                [1 ]Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
                [2 ]Pulmonary, Allergy and Critical Care Division; Department of Medicine; University of Pennsylvania Perelman School of Medicine; Philadelphia, PA.
                [3 ]Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, PA.
                [4 ]Division of Gastroenterology, Hepatology & Nutrition, Children’s Hospital of Philadelphia, Philadelphia, PA.
                [5 ]Division of COVID-19 Containment, Philadelphia Department of Public Health, Philadelphia, PA.
                [6 ]Department of Microbiology & Immunology, Center for Genomic Sciences, Drexel University College of Medicine. Philadelphia, PA.
                [7 ]Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
                [8 ]Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, NY.
                [9 ]Molecular & Genomic Pathology Laboratory, Thomas Jefferson University Hospital, Philadelphia, PA.
                [10 ]Jefferson Occupational Health Network for Employees and Students (JOHN), Thomas Jefferson University, Philadelphia, PA.
                [11 ]Department of Anatomy, Pathology, and Cell Biology, Thomas Jefferson University Hospital, Philadelphia, PA.
                [12 ]Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA.
                [13 ]Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia, PA.
                [14 ]Division of Infectious Diseases; Department of Medicine & Department of Biostatistics, Epidemiology, and Informatics; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
                [15 ]Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
                [16 ]Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
                Author notes
                [*]

                co-first authors

                Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contacts, Frederic D. Bushman, Brendan Kelly, and Kyle Rodino.

                Author contributions

                ADM, JE, SS-M, RGC, KR, BJK and FDB designed the study; SAW, JG-W, LAK, ASF, ADM, CB, SR, JH, RD, LD, AA, EK, SC, CN, JCM, PP, CC, KS, AG, MF, RGC, KR, AJ-B, LC, SL, AG and BJK managed acquisition of clinical specimens; ADM, CB, SR, LD, AA, JCM, PP, NB, Z-XW, PH, AMR, AG, AM, and FDB carried out sequencing; ADM, AMM, CB, SR, AA, JCM, PP, SS-M, BJK, JE and FDB carried out bioinformatic and statistical analysis; ADM, SS-M, JE, KR, BJK, RGC, and FDB wrote the paper.

                Article
                10.1101/2021.10.18.21264623
                8547530
                34704098
                d08ca4f5-23da-44f4-81c5-31003f4c77f7

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.

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                sars-cov-2,covid-19,coronavirus,genome sequencing,philadelphia

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