1
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Lemoine F, Gascuel O. The Bayesian Phylogenetic Bootstrap and its Application to Short Trees and Branches. Mol Biol Evol 2024; 41:msae238. [PMID: 39514774 PMCID: PMC11600590 DOI: 10.1093/molbev/msae238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 10/24/2024] [Accepted: 10/29/2024] [Indexed: 11/16/2024] Open
Abstract
Felsenstein's bootstrap is the most commonly used method to measure branch support in phylogenetics. Current sequencing technologies can result in massive sampling of taxa (e.g. SARS-CoV-2). In this case, the sequences are very similar, the trees are short, and the branches correspond to a small number of mutations (possibly 0). Nevertheless, these trees contain a strong signal, with unresolved parts but a low rate of false branches. With such data, Felsenstein's bootstrap is not satisfactory. Due to the frequentist nature of bootstrap sampling, the expected support of a branch corresponding to a single mutation is ∼63%, even though it is highly likely to be correct. Here, we propose a Bayesian version of the phylogenetic bootstrap in which sites are assigned uninformative prior probabilities. The branch support can then be interpreted as a posterior probability. We do not view the alignment as a small subsample of a large sample of sites, but rather as containing all available information (e.g. as with complete viral genomes, which are becoming routine). We give formulas for expected supports under the assumption of perfect phylogeny, in both the frequentist and Bayesian frameworks, where a branch corresponding to a single mutation now has an expected support of ∼90%. Simulations show that these theoretical results are robust to realistic data. Analyses on low-homoplasy viral and nonviral datasets show that Bayesian bootstrap support is easier to interpret, with high supports for branches very likely to be correct. As homoplasy increases, the two supports become closer and strongly correlated.
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Affiliation(s)
- Frédéric Lemoine
- National Reference Center for Respiratory Viruses, Institut Pasteur, Université Paris Cité, Paris 75015, France
- Bioinformatics and Biostatistics Hub, Institut Pasteur, Université Paris Cité, Paris 75015, France
| | - Olivier Gascuel
- Institut de Systématique Evolution, Biodiversité (ISYEB UMR7205—CNRS, Muséum National d’Histoire Naturelle, SU, EPHE, UA), Paris 75005, France
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2
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Lado S, Thannesberger J, Spettel K, Arapović J, Ferreira BI, Lavitrano M, Steininger C. Unveiling Inter- and Intra-Patient Sequence Variability with a Multi-Sample Coronavirus Target Enrichment Approach. Viruses 2024; 16:786. [PMID: 38793667 PMCID: PMC11125942 DOI: 10.3390/v16050786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/08/2024] [Accepted: 05/11/2024] [Indexed: 05/26/2024] Open
Abstract
Amid the global challenges posed by the COVID-19 pandemic, unraveling the genomic intricacies of SARS-CoV-2 became crucial. This study explores viral evolution using an innovative high-throughput next-generation sequencing (NGS) approach. By taking advantage of nasal swab and mouthwash samples from patients who tested positive for COVID-19 across different geographical regions during sequential infection waves, our study applied a targeted enrichment protocol and pooling strategy to increase detection sensitivity. The approach was extremely efficient, yielding a large number of reads and mutations distributed across 10 distinct viral gene regions. Notably, the genes Envelope, Nucleocapsid, and Open Reading Frame 8 had the highest number of unique mutations per 1000 nucleotides, with both spike and Nucleocapsid genes showing evidence for positive selection. Focusing on the spike protein gene, crucial in virus replication and immunogenicity, our findings show a dynamic SARS-CoV-2 evolution, emphasizing the virus-host interplay. Moreover, the pooling strategy facilitated subtle sequence variability detection. Our findings painted a dynamic portrait of SARS-CoV-2 evolution, emphasizing the intricate interplay between the virus and its host populations and accentuating the importance of continuous genomic surveillance to understand viral dynamics. As SARS-CoV-2 continues to evolve, this approach proves to be a powerful, versatile, fast, and cost-efficient screening tool for unraveling emerging variants, fostering understanding of the virus's genetic landscape.
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Affiliation(s)
- Sara Lado
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine 1, Medical University of Vienna, 1090 Vienna, Austria; (S.L.); (J.T.)
| | - Jakob Thannesberger
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine 1, Medical University of Vienna, 1090 Vienna, Austria; (S.L.); (J.T.)
| | - Kathrin Spettel
- Division of Clinical Microbiology, Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria;
- Division of Biomedical Science, University of Applied Sciences, FH Campus Wien, 1100 Vienna, Austria
| | - Jurica Arapović
- Department of Medical Biology, School of Medicine, University of Mostar, Bijeli Brijeg b.b., 88000 Mostar, Bosnia and Herzegovina
| | - Bibiana I. Ferreira
- Faculty of Medicine and Biomedical Sciences, University of Algarve, Campus de Gambelas, Edf. 2, 8005-139 Faro, Portugal;
- Algarve Biomedical Center Research Institute, Campus de Gambelas, Edf. 2, lab 3.67, 8005-139 Faro, Portugal
| | | | - Christoph Steininger
- Division of Infectious Diseases and Tropical Medicine, Department of Medicine 1, Medical University of Vienna, 1090 Vienna, Austria; (S.L.); (J.T.)
- Karl-Landsteiner Institute for Microbiome Research, Medical University of Vienna, 1090 Vienna, Austria
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3
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Hayman E, Ignatieva A, Hein J. Recoverability of ancestral recombination graph topologies. Theor Popul Biol 2023; 154:27-39. [PMID: 37544486 DOI: 10.1016/j.tpb.2023.07.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 07/25/2023] [Accepted: 07/27/2023] [Indexed: 08/08/2023]
Abstract
Recombination is a powerful evolutionary process that shapes the genetic diversity observed in the populations of many species. Reconstructing genealogies in the presence of recombination from sequencing data is a very challenging problem, as this relies on mutations having occurred on the correct lineages in order to detect the recombination and resolve the ordering of coalescence events in the local trees. We investigate the probability of reconstructing the true topology of ancestral recombination graphs (ARGs) under the coalescent with recombination and gene conversion. We explore how sample size and mutation rate affect the inherent uncertainty in reconstructed ARGs, which sheds light on the theoretical limitations of ARG reconstruction methods. We illustrate our results using estimates of evolutionary rates for several organisms; in particular, we find that for parameter values that are realistic for SARS-CoV-2, the probability of reconstructing genealogies that are close to the truth is low.
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Affiliation(s)
- Elizabeth Hayman
- Department of Mathematics, University of Oxford, Andrew Wiles Building, Oxford OX2 6GG, UK.
| | - Anastasia Ignatieva
- Department of Statistics, University of Warwick, Coventry CV4 7AL, UK; Department of Statistics, University of Oxford, 24-29 St Giles', Oxford OX1 3LB, UK
| | - Jotun Hein
- Department of Statistics, University of Oxford, 24-29 St Giles', Oxford OX1 3LB, UK; The Alan Turing Institute, British Library, London NW1 2DB, UK
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4
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Gazeau S, Deng X, Ooi HK, Mostefai F, Hussin J, Heffernan J, Jenner AL, Craig M. The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions. IMMUNOINFORMATICS (AMSTERDAM, NETHERLANDS) 2023; 9:100021. [PMID: 36643886 PMCID: PMC9826539 DOI: 10.1016/j.immuno.2023.100021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 11/16/2022] [Accepted: 01/03/2023] [Indexed: 01/09/2023]
Abstract
The COVID-19 pandemic has revealed the need for the increased integration of modelling and data analysis to public health, experimental, and clinical studies. Throughout the first two years of the pandemic, there has been a concerted effort to improve our understanding of the within-host immune response to the SARS-CoV-2 virus to provide better predictions of COVID-19 severity, treatment and vaccine development questions, and insights into viral evolution and the impacts of variants on immunopathology. Here we provide perspectives on what has been accomplished using quantitative methods, including predictive modelling, population genetics, machine learning, and dimensionality reduction techniques, in the first 26 months of the COVID-19 pandemic approaches, and where we go from here to improve our responses to this and future pandemics.
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Affiliation(s)
- Sonia Gazeau
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Canada
- Sainte-Justine University Hospital Research Centre, Montréal, Canada
| | - Xiaoyan Deng
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Canada
- Sainte-Justine University Hospital Research Centre, Montréal, Canada
| | - Hsu Kiang Ooi
- Digital Technologies Research Centre, National Research Council Canada, Toronto, Canada
| | - Fatima Mostefai
- Montréal Heart Institute Research Centre, Montréal, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Canada
| | - Julie Hussin
- Montréal Heart Institute Research Centre, Montréal, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Canada
| | - Jane Heffernan
- Modelling Infection and Immunity Lab, Mathematics Statistics, York University, Toronto, Canada
- Centre for Disease Modelling (CDM), Mathematics Statistics, York University, Toronto, Canada
| | - Adrianne L Jenner
- School of Mathematical Sciences, Queensland University of Technology, Brisbane Australia
| | - Morgan Craig
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Canada
- Sainte-Justine University Hospital Research Centre, Montréal, Canada
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5
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Aroldi A, Angaroni F, D’Aliberti D, Spinelli S, Crespiatico I, Crippa V, Piazza R, Graudenzi A, Ramazzotti D. Characterization of SARS-CoV-2 Mutational Signatures from 1.5+ Million Raw Sequencing Samples. Viruses 2022; 15:7. [PMID: 36680048 PMCID: PMC9864147 DOI: 10.3390/v15010007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/01/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022] Open
Abstract
We present a large-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) substitutions, considering 1,585,456 high-quality raw sequencing samples, aimed at investigating the existence and quantifying the effect of mutational processes causing mutations in SARS-CoV-2 genomes when interacting with the human host. As a result, we confirmed the presence of three well-differentiated mutational processes likely ruled by reactive oxygen species (ROS), apolipoprotein B editing complex (APOBEC), and adenosine deaminase acting on RNA (ADAR). We then evaluated the activity of these mutational processes in different continental groups, showing that some samples from Africa present a significantly higher number of substitutions, most likely due to higher APOBEC activity. We finally analyzed the activity of mutational processes across different SARS-CoV-2 variants, and we found a significantly lower number of mutations attributable to APOBEC activity in samples assigned to the Omicron variant.
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Affiliation(s)
- Andrea Aroldi
- Hematology and Clinical Research Unit, San Gerardo Hospital, Via G. B. Pergolesi 33, 20900 Monza, Italy
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
| | - Fabrizio Angaroni
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Viale Sarca 336, 20100 Milano, Italy
- Computational Biology Research Centre, Human Technopole, Viale Rita Levi Montalcini 1, 20157 Milano, Italy
| | - Deborah D’Aliberti
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
| | - Silvia Spinelli
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
| | - Ilaria Crespiatico
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
| | - Valentina Crippa
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
| | - Rocco Piazza
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Center—B4, Via Follereau 3, 20854 Vedano al Lambro, Italy
| | - Alex Graudenzi
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Viale Sarca 336, 20100 Milano, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Center—B4, Via Follereau 3, 20854 Vedano al Lambro, Italy
| | - Daniele Ramazzotti
- Department of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy
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6
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Hassan SS, Kodakandla V, Redwan EM, Lundstrom K, Choudhury PP, Serrano-Aroca Á, Azad GK, Aljabali AAA, Palu G, Abd El-Aziz TM, Barh D, Uhal BD, Adadi P, Takayama K, Bazan NG, Tambuwala M, Sherchan SP, Lal A, Chauhan G, Baetas-da-Cruz W, Uversky VN. Non-uniform aspects of the SARS-CoV-2 intraspecies evolution reopen question of its origin. Int J Biol Macromol 2022; 222:972-993. [PMID: 36174872 PMCID: PMC9511875 DOI: 10.1016/j.ijbiomac.2022.09.184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/04/2022] [Accepted: 09/20/2022] [Indexed: 12/01/2022]
Abstract
Several hypotheses have been presented on the origin of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) from its identification as the agent causing the current coronavirus disease 19 (COVID-19) pandemic. So far, no solid evidence has been found to support any hypothesis on the origin of this virus, and the issue continue to resurface over and over again. Here we have unfolded a pattern of distribution of several mutations in the SARS-CoV-2 proteins in 24 geo-locations across different continents. The results showed an evenly uneven distribution of the unique protein variants, distinct mutations, unique frequency of common conserved residues, and mutational residues across these 24 geo-locations. Furthermore, ample mutations were identified in the evolutionarily conserved invariant regions in the SARS-CoV-2 proteins across almost all geo-locations studied. This pattern of mutations potentially breaches the law of evolutionary conserved functional units of the beta-coronavirus genus. These mutations may lead to several novel SARS-CoV-2 variants with a high degree of transmissibility and virulence. A thorough investigation on the origin and characteristics of SARS-CoV-2 needs to be conducted in the interest of science and for the preparation of meeting the challenges of potential future pandemics.
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Affiliation(s)
- Sk Sarif Hassan
- Department of Mathematics, Pingla Thana Mahavidyalaya, Maligram, Paschim Medinipur, 721140, West Bengal, India.
| | - Vaishnavi Kodakandla
- Department of Life sciences, Sophia College For Women, University of Mumbai, Bhulabhai Desai Road, Mumbai 400026, India
| | - Elrashdy M Redwan
- Biological Science Department, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia; Therapeutic and Protective Proteins Laboratory, Protein Research Department, Genetic Engineering and Biotechnology Research Institute, City of Scientific Research and Technological Applications, New Borg EL-Arab 21934, Alexandria, Egypt.
| | | | - Pabitra Pal Choudhury
- Indian Statistical Institute, Applied Statistics Unit, 203 B T Road, Kolkata 700108, India
| | - Ángel Serrano-Aroca
- Biomaterials and Bioengineering Lab, Centro de Investigacion Traslacional San Alberto Magno, Universidad Cat'olica de Valencia San Vicente Martir, c/Guillem de Castro, 94, 46001 Valencia, Valencia, Spain.
| | | | - Alaa A A Aljabali
- Department of Pharmaceutics and Pharmaceutical Technology, Yarmouk University, Faculty of Pharmacy, Irbid 566, Jordan.
| | - Giorgio Palu
- Department of Molecular Medicine, University of Padova, Via Gabelli 63, 35121 Padova, Italy.
| | - Tarek Mohamed Abd El-Aziz
- Zoology Department, Faculty of Science, Minia University, El-Minia 61519, Egypt; Department of Cellular and Integrative Physiology, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229-3900, USA.
| | - Debmalya Barh
- Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur, WB, India; Departamento de Geńetica, Ecologia e Evolucao, Instituto de Cíencias Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Bruce D Uhal
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Parise Adadi
- Department of Food Science, University of Otago, Dunedin 9054, New Zealand
| | - Kazuo Takayama
- Center for iPS Cell Research and Application, Kyoto University, Kyoto 6068507, Japan.
| | - Nicolas G Bazan
- Neuroscience Center of Excellence, School of Medicine, LSU Health New Orleans, New Orleans, LA 70112, USA.
| | - Murtaza Tambuwala
- School of Pharmacy and Pharmaceutical Science, Ulster University, Coleraine BT52 1SA, Northern Ireland, UK.
| | - Samendra P Sherchan
- Lincoln Medical School, University of Lincoln, Brayford Pool Campus, Lincoln LN6 7TS, UK.
| | - Amos Lal
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
| | - Gaurav Chauhan
- School of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, 64849 Monterrey, Nuevo León, Mexico.
| | - Wagner Baetas-da-Cruz
- Translational Laboratory in Molecular Physiology, Centre for Experimental Surgery, College of Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
| | - Vladimir N Uversky
- Department of Molecular Medicineand USF Health Byrd Alzheimer's Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA; Research Center for Molecular Mechanisms of Aging and Age-Related Diseases, Moscow Institute of Physics and Technology, Institutskiy pereulok, 9, Dolgoprudny 141700, Russia.
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7
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Attwood SW, Hill SC, Aanensen DM, Connor TR, Pybus OG. Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic. Nat Rev Genet 2022; 23:547-562. [PMID: 35459859 PMCID: PMC9028907 DOI: 10.1038/s41576-022-00483-8] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/23/2022] [Indexed: 01/05/2023]
Abstract
Determining the transmissibility, prevalence and patterns of movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is central to our understanding of the impact of the pandemic and to the design of effective control strategies. Phylogenies (evolutionary trees) have provided key insights into the international spread of SARS-CoV-2 and enabled investigation of individual outbreaks and transmission chains in specific settings. Phylodynamic approaches combine evolutionary, demographic and epidemiological concepts and have helped track virus genetic changes, identify emerging variants and inform public health strategy. Here, we review and synthesize studies that illustrate how phylogenetic and phylodynamic techniques were applied during the first year of the pandemic, and summarize their contributions to our understanding of SARS-CoV-2 transmission and control.
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Affiliation(s)
- Stephen W Attwood
- Department of Zoology, University of Oxford, Oxford, UK.
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK.
| | - Sarah C Hill
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Thomas R Connor
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
- School of Biosciences, Cardiff University, Cardiff, UK
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK.
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8
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Qin L, Meng J, Ding X, Jiang T. Mapping Genetic Events of SARS-CoV-2 Variants. Front Microbiol 2022; 13:890590. [PMID: 35910603 PMCID: PMC9329953 DOI: 10.3389/fmicb.2022.890590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 06/20/2022] [Indexed: 12/18/2022] Open
Abstract
Genetic mutation and recombination are driving the evolution of SARS-CoV-2, leaving many genetic imprints which could be utilized to track the evolutionary pathway of SARS-CoV-2 and explore the relationships among variants. Here, we constructed a complete genetic map, showing the explicit evolutionary relationship among all SARS-CoV-2 variants including 58 groups and 46 recombination types identified from 3,392,553 sequences, which enables us to keep well informed of the evolution of SARS-CoV-2 and quickly determine the parents of novel variants. We found that the 5' and 3' of the spike and nucleoprotein genes have high frequencies to form the recombination junctions and that the RBD region in S gene is always exchanged as a whole. Although these recombinants did not show advantages in community transmission, it is necessary to keep a wary eye on the novel genetic events, in particular, the mutants with mutations on spike and recombinants with exchanged moieties on spike gene.
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Affiliation(s)
- Luyao Qin
- Institute of Systems Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- Suzhou Institute of Systems Medicine, Suzhou, China
| | - Jing Meng
- Institute of Systems Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- Suzhou Institute of Systems Medicine, Suzhou, China
| | - Xiao Ding
- Institute of Systems Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- Suzhou Institute of Systems Medicine, Suzhou, China
| | - Taijiao Jiang
- Institute of Systems Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- Suzhou Institute of Systems Medicine, Suzhou, China
- Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
- Guangzhou Laboratory, Guangzhou, China
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9
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Zahradník J, Nunvar J, Schreiber G. Perspectives: SARS-CoV-2 Spike Convergent Evolution as a Guide to Explore Adaptive Advantage. Front Cell Infect Microbiol 2022; 12:748948. [PMID: 35711666 PMCID: PMC9197234 DOI: 10.3389/fcimb.2022.748948] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 04/19/2022] [Indexed: 01/22/2023] Open
Abstract
Viruses rapidly co-evolve with their hosts. The 9 million sequenced SARS-CoV-2 genomes by March 2022 provide a detailed account of viral evolution, showing that all amino acids have been mutated many times. However, only a few became prominent in the viral population. Here, we investigated the emergence of the same mutations in unrelated parallel lineages and the extent of such convergent evolution on the molecular level in the spike (S) protein. We found that during the first phase of the pandemic (until mid 2021, before mass vaccination) 31 mutations evolved independently ≥3-times within separated lineages. These included all the key mutations in SARS-CoV-2 variants of concern (VOC) at that time, indicating their fundamental adaptive advantage. The omicron added many more mutations not frequently seen before, which can be attributed to the synergistic nature of these mutations, which is more difficult to evolve. The great majority (24/31) of S-protein mutations under convergent evolution tightly cluster in three functional domains; N-terminal domain, receptor-binding domain, and Furin cleavage site. Furthermore, among the S-protein receptor-binding motif mutations, ACE2 affinity-improving substitutions are favoured. Next, we determined the mutation space in the S protein that has been covered by SARS-CoV-2. We found that all amino acids that are reachable by single nucleotide changes have been probed multiple times in early 2021. The substitutions requiring two nucleotide changes have recently (late 2021) gained momentum and their numbers are increasing rapidly. These provide a large mutation landscape for SARS-CoV-2 future evolution, on which research should focus now.
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Affiliation(s)
- Jiri Zahradník
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Jaroslav Nunvar
- Department of Genetics and Microbiology, Faculty of Science, Charles University, Prague, Czechia
- Biotechnology and Biomedicine Centre of the Academy of Sciences and Charles University (BIOCEV), Vestec, Czechia
| | - Gideon Schreiber
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
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10
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Ramazzotti D, Maspero D, Angaroni F, Spinelli S, Antoniotti M, Piazza R, Graudenzi A. Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data. iScience 2022; 25:104487. [PMID: 35677393 PMCID: PMC9162787 DOI: 10.1016/j.isci.2022.104487] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 05/06/2022] [Accepted: 05/24/2022] [Indexed: 11/19/2022] Open
Affiliation(s)
- Daniele Ramazzotti
- Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy
- Corresponding author
| | - Davide Maspero
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Segrate, Milan, Italy
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Fabrizio Angaroni
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
| | - Silvia Spinelli
- Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy
| | - Marco Antoniotti
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Centre – B4, Milan, Italy
| | - Rocco Piazza
- Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Centre – B4, Milan, Italy
| | - Alex Graudenzi
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Segrate, Milan, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Centre – B4, Milan, Italy
- Corresponding author
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11
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Lin MJ, Rachleff VM, Xie H, Shrestha L, Lieberman NAP, Peddu V, Addetia A, Casto AM, Breit N, Mathias PC, Huang ML, Jerome KR, Greninger AL, Roychoudhury P. Host-pathogen dynamics in longitudinal clinical specimens from patients with COVID-19. Sci Rep 2022; 12:5856. [PMID: 35393464 PMCID: PMC8987511 DOI: 10.1038/s41598-022-09752-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 03/16/2022] [Indexed: 12/30/2022] Open
Abstract
Rapid dissemination of SARS-CoV-2 sequencing data to public repositories has enabled widespread study of viral genomes, but studies of longitudinal specimens from infected persons are relatively limited. Analysis of longitudinal specimens enables understanding of how host immune pressures drive viral evolution in vivo. Here we performed sequencing of 49 longitudinal SARS-CoV-2-positive samples from 20 patients in Washington State collected between March and September of 2020. Viral loads declined over time with an average increase in RT-QPCR cycle threshold of 0.87 per day. We found that there was negligible change in SARS-CoV-2 consensus sequences over time, but identified a number of nonsynonymous variants at low frequencies across the genome. We observed enrichment for a relatively small number of these variants, all of which are now seen in consensus genomes across the globe at low prevalence. In one patient, we saw rapid emergence of various low-level deletion variants at the N-terminal domain of the spike glycoprotein, some of which have previously been shown to be associated with reduced neutralization potency from sera. In a subset of samples that were sequenced using metagenomic methods, differential gene expression analysis showed a downregulation of cytoskeletal genes that was consistent with a loss of ciliated epithelium during infection and recovery. We also identified co-occurrence of bacterial species in samples from multiple hospitalized individuals. These results demonstrate that the intrahost genetic composition of SARS-CoV-2 is dynamic during the course of COVID-19, and highlight the need for continued surveillance and deep sequencing of minor variants.
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Affiliation(s)
- Michelle J Lin
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Victoria M Rachleff
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.,Program in Molecular and Cellular Biology, University of Washington School of Medicine, Seattle, WA, USA
| | - Hong Xie
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Lasata Shrestha
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Nicole A P Lieberman
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Vikas Peddu
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Amin Addetia
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Amanda M Casto
- Division of Allergy and Infectious Diseases, University of Washington School of Medicine, Seattle, WA, USA
| | - Nathan Breit
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Patrick C Mathias
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA
| | - Meei-Li Huang
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Keith R Jerome
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA. .,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Alexander L Greninger
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA. .,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
| | - Pavitra Roychoudhury
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98102, USA. .,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
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12
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Ramazzotti D, Angaroni F, Maspero D, Mauri M, D’Aliberti D, Fontana D, Antoniotti M, Elli EM, Graudenzi A, Piazza R. Large-Scale Analysis of SARS-CoV-2 Synonymous Mutations Reveals the Adaptation to the Human Codon Usage During the Virus Evolution. Virus Evol 2022; 8:veac026. [PMID: 35371557 PMCID: PMC8971538 DOI: 10.1093/ve/veac026] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/11/2022] [Accepted: 03/22/2022] [Indexed: 11/27/2022] Open
Abstract
Many large national and transnational studies have been dedicated to the analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) genome, most of which focused on missense and nonsense mutations. However, approximately 30 per cent of the SARS-CoV-2 variants are synonymous, therefore changing the target codon without affecting the corresponding protein sequence. By performing a large-scale analysis of sequencing data generated from almost 400,000 SARS-CoV-2 samples, we show that silent mutations increasing the similarity of viral codons to the human ones tend to fixate in the viral genome overtime. This indicates that SARS-CoV-2 codon usage is adapting to the human host, likely improving its effectiveness in using the human aminoacyl-tRNA set through the accumulation of deceitfully neutral silent mutations. One-Sentence Summary. Synonymous SARS-CoV-2 mutations related to the activity of different mutational processes may positively impact viral evolution by increasing its adaptation to the human codon usage.
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Affiliation(s)
- Daniele Ramazzotti
- Dept. of Medicine and Surgery, Università degli Studi di Milano-Bicocca; Monza, Italy
| | - Fabrizio Angaroni
- Dept. of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca; Milan, Italy
| | - Davide Maspero
- Dept. of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca; Milan, Italy
- Inst. of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR); Segrate, Milan, Italy
| | - Mario Mauri
- Dept. of Medicine and Surgery, Università degli Studi di Milano-Bicocca; Monza, Italy
| | - Deborah D’Aliberti
- Dept. of Medicine and Surgery, Università degli Studi di Milano-Bicocca; Monza, Italy
| | - Diletta Fontana
- Dept. of Medicine and Surgery, Università degli Studi di Milano-Bicocca; Monza, Italy
| | - Marco Antoniotti
- Dept. of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca; Milan, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Center – B4; Milan, Italy
| | - Elena Maria Elli
- Dept. of Medicine and Surgery, Università degli Studi di Milano-Bicocca; Monza, Italy
- Hematology and Clinical Research Unit, San Gerardo Hospital, Monza, Italy
| | - Alex Graudenzi
- Inst. of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR); Segrate, Milan, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Center – B4; Milan, Italy
| | - Rocco Piazza
- Dept. of Medicine and Surgery, Università degli Studi di Milano-Bicocca; Monza, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Center – B4; Milan, Italy
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13
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Jiang H, Xi H, Juhas M, Zhang Y. Biosensors for Point Mutation Detection. Front Bioeng Biotechnol 2021; 9:797831. [PMID: 34976987 PMCID: PMC8714947 DOI: 10.3389/fbioe.2021.797831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 11/17/2021] [Indexed: 11/25/2022] Open
Affiliation(s)
- Hanlin Jiang
- College of Science, Harbin Institute of Technology, Shenzhen, China
| | - Hui Xi
- College of Science, Harbin Institute of Technology, Shenzhen, China
| | - Mario Juhas
- Medical and Molecular Microbiology Unit, Department of Medicine, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Yang Zhang
- College of Science, Harbin Institute of Technology, Shenzhen, China
- *Correspondence: Yang Zhang,
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14
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Maspero D, Angaroni F, Porro D, Piazza R, Graudenzi A, Ramazzotti D. VirMutSig: Discovery and assignment of viral mutational signatures from sequencing data. STAR Protoc 2021. [DOI: 10.1016/j.xpro.2021.100911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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15
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Van Egeren D, Novokhodko A, Stoddard M, Tran U, Zetter B, Rogers MS, Joseph-McCarthy D, Chakravarty A. Controlling long-term SARS-CoV-2 infections can slow viral evolution and reduce the risk of treatment failure. Sci Rep 2021; 11:22630. [PMID: 34799659 PMCID: PMC8604936 DOI: 10.1038/s41598-021-02148-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 10/27/2021] [Indexed: 12/23/2022] Open
Abstract
The rapid emergence and expansion of novel SARS-CoV-2 variants threatens our ability to achieve herd immunity for COVID-19. These novel SARS-CoV-2 variants often harbor multiple point mutations, conferring one or more evolutionarily advantageous traits, such as increased transmissibility, immune evasion and longer infection duration. In a number of cases, variant emergence has been linked to long-term infections in individuals who were either immunocompromised or treated with convalescent plasma. In this paper, we used a stochastic evolutionary modeling framework to explore the emergence of fitter variants of SARS-CoV-2 during long-term infections. We found that increased viral load and infection duration favor emergence of such variants. While the overall probability of emergence and subsequent transmission from any given infection is low, on a population level these events occur fairly frequently. Targeting these low-probability stochastic events that lead to the establishment of novel advantageous viral variants might allow us to slow the rate at which they emerge in the patient population, and prevent them from spreading deterministically due to natural selection. Our work thus suggests practical ways to achieve control of long-term SARS-CoV-2 infections, which will be critical for slowing the rate of viral evolution.
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Affiliation(s)
- Debra Van Egeren
- Harvard Medical School, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | | | | | - Uyen Tran
- Fractal Therapeutics, Cambridge, MA, USA
| | - Bruce Zetter
- Harvard Medical School, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Michael S Rogers
- Harvard Medical School, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
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16
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Sashittal P, Zhang C, Peng J, El-Kebir M. Jumper enables discontinuous transcript assembly in coronaviruses. Nat Commun 2021; 12:6728. [PMID: 34795232 PMCID: PMC8602663 DOI: 10.1038/s41467-021-26944-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 10/20/2021] [Indexed: 11/17/2022] Open
Abstract
Genes in SARS-CoV-2 and other viruses in the order of Nidovirales are expressed by a process of discontinuous transcription which is distinct from alternative splicing in eukaryotes and is mediated by the viral RNA-dependent RNA polymerase. Here, we introduce the DISCONTINUOUS TRANSCRIPT ASSEMBLYproblem of finding transcripts and their abundances given an alignment of paired-end short reads under a maximum likelihood model that accounts for varying transcript lengths. We show, using simulations, that our method, JUMPER, outperforms existing methods for classical transcript assembly. On short-read data of SARS-CoV-1, SARS-CoV-2 and MERS-CoV samples, we find that JUMPER not only identifies canonical transcripts that are part of the reference transcriptome, but also predicts expression of non-canonical transcripts that are supported by subsequent orthogonal analyses. Moreover, application of JUMPER on samples with and without treatment reveals viral drug response at the transcript level. As such, JUMPER enables detailed analyses of Nidovirales transcriptomes under varying conditions.
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Affiliation(s)
- Palash Sashittal
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Chuanyi Zhang
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jian Peng
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- College of Medicine, University of ILlinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Mohammed El-Kebir
- Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
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17
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De Maio N, Walker CR, Turakhia Y, Lanfear R, Corbett-Detig R, Goldman N. Mutation Rates and Selection on Synonymous Mutations in SARS-CoV-2. Genome Biol Evol 2021; 13:evab087. [PMID: 33895815 PMCID: PMC8135539 DOI: 10.1093/gbe/evab087] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2021] [Indexed: 12/23/2022] Open
Abstract
The COVID-19 pandemic has seen an unprecedented response from the sequencing community. Leveraging the sequence data from more than 140,000 SARS-CoV-2 genomes, we study mutation rates and selective pressures affecting the virus. Understanding the processes and effects of mutation and selection has profound implications for the study of viral evolution, for vaccine design, and for the tracking of viral spread. We highlight and address some common genome sequence analysis pitfalls that can lead to inaccurate inference of mutation rates and selection, such as ignoring skews in the genetic code, not accounting for recurrent mutations, and assuming evolutionary equilibrium. We find that two particular mutation rates, G →U and C →U, are similarly elevated and considerably higher than all other mutation rates, causing the majority of mutations in the SARS-CoV-2 genome, and are possibly the result of APOBEC and ROS activity. These mutations also tend to occur many times at the same genome positions along the global SARS-CoV-2 phylogeny (i.e., they are very homoplasic). We observe an effect of genomic context on mutation rates, but the effect of the context is overall limited. Although previous studies have suggested selection acting to decrease U content at synonymous sites, we bring forward evidence suggesting the opposite.
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Affiliation(s)
- Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, United Kingdom
| | - Conor R Walker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, United Kingdom
- Department of Genetics, University of Cambridge, United Kingdom
| | - Yatish Turakhia
- Department of Biomolecular Engineering, University of California, Santa Cruz, California, USA
- Genomics Institute, University of California, Santa Cruz, California, USA
| | - Robert Lanfear
- Department of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, ACT, Australia
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz, California, USA
- Genomics Institute, University of California, Santa Cruz, California, USA
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, United Kingdom
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18
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Sapoval N, Mahmoud M, Jochum MD, Liu Y, Elworth RAL, Wang Q, Albin D, Ogilvie HA, Lee MD, Villapol S, Hernandez KM, Maljkovic Berry I, Foox J, Beheshti A, Ternus K, Aagaard KM, Posada D, Mason CE, Sedlazeck FJ, Treangen TJ. SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission. Genome Res 2021; 31:635-644. [PMID: 33602693 PMCID: PMC8015855 DOI: 10.1101/gr.268961.120] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 02/12/2021] [Indexed: 12/23/2022]
Abstract
The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.
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Affiliation(s)
- Nicolae Sapoval
- Department of Computer Science, Rice University, Houston, Texas 77005, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Michael D Jochum
- Department of Obstetrics and Gynecology, Baylor College of Medicine and Texas Children's Hospital, Houston, Texas 77030, USA
| | - Yunxi Liu
- Department of Computer Science, Rice University, Houston, Texas 77005, USA
| | - R A Leo Elworth
- Department of Computer Science, Rice University, Houston, Texas 77005, USA
| | - Qi Wang
- Systems, Synthetic, and Physical Biology (SSPB) Graduate Program, Rice University, Houston, Texas 77005, USA
| | - Dreycey Albin
- Systems, Synthetic, and Physical Biology (SSPB) Graduate Program, Rice University, Houston, Texas 77005, USA
| | - Huw A Ogilvie
- Department of Computer Science, Rice University, Houston, Texas 77005, USA
| | - Michael D Lee
- Exobiology Branch, NASA Ames Research Center, Mountain View, California 94043, USA
- Blue Marble Space Institute of Science, Seattle, Washington 98104, USA
| | - Sonia Villapol
- Department of Neurosurgery, Houston Methodist Research Institute, Houston, Texas 77030, USA
| | - Kyle M Hernandez
- Department of Medicine, University of Chicago, Chicago, Illinois 60637, USA
- Center for Translational Data Science, University of Chicago, Chicago, Illinois 60637, USA
| | | | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York 10021, USA
| | - Afshin Beheshti
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, California 94035, USA
| | | | - Kjersti M Aagaard
- Department of Obstetrics and Gynecology, Baylor College of Medicine and Texas Children's Hospital, Houston, Texas 77030, USA
| | - David Posada
- CINBIO, Universidade de Vigo, 36310 Vigo, Spain
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, 36310 Vigo, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York 10021, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Todd J Treangen
- Department of Computer Science, Rice University, Houston, Texas 77005, USA
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19
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Graudenzi A, Maspero D, Angaroni F, Piazza R, Ramazzotti D. Mutational signatures and heterogeneous host response revealed via large-scale characterization of SARS-CoV-2 genomic diversity. iScience 2021; 24:102116. [PMID: 33532709 PMCID: PMC7842190 DOI: 10.1016/j.isci.2021.102116] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 11/09/2020] [Accepted: 01/22/2021] [Indexed: 01/03/2023] Open
Abstract
To dissect the mechanisms underlying the inflation of variants in the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) genome, we present a large-scale analysis of intra-host genomic diversity, which reveals that most samples exhibit heterogeneous genomic architectures, due to the interplay between host-related mutational processes and transmission dynamics. The decomposition of minor variants profiles unveils three non-overlapping mutational signatures related to nucleotide substitutions and likely ruled by APOlipoprotein B Editing Complex (APOBEC), Reactive Oxygen Species (ROS), and Adenosine Deaminase Acting on RNA (ADAR), highlighting heterogeneous host responses to SARS-CoV-2 infections. A corrected-for-signatures dN/dS analysis demonstrates that such mutational processes are affected by purifying selection, with important exceptions. In fact, several mutations appear to transit toward clonality, defining new clonal genotypes that increase the overall genomic diversity. Furthermore, the phylogenomic analysis shows the presence of homoplasies and supports the hypothesis of transmission of minor variants. This study paves the way for the integrated analysis of intra-host genomic diversity and clinical outcomes of SARS-CoV-2 infections.
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Affiliation(s)
- Alex Graudenzi
- Inst. of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR), Segrate, Milan, Italy
- Bicocca Bioinformatics, Biostatistics and Bioimaging Centre – B4, Milan, Italy
| | - Davide Maspero
- Inst. of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR), Segrate, Milan, Italy
- Department of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy
| | - Fabrizio Angaroni
- Department of Informatics, Systems and Communication, Univ. of Milan-Bicocca, Milan, Italy
| | - Rocco Piazza
- Department of Medicine and Surgery, Univ. of Milan-Bicocca, Monza, Italy
| | - Daniele Ramazzotti
- Department of Medicine and Surgery, Univ. of Milan-Bicocca, Monza, Italy
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