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The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2
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The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2

A special issue of COVID (ISSN 2673-8112).

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 19601

Special Issue Editor

Dr. Tohru Suzuki

E-Mail Website
Guest Editor
National Institute of Animal Health, NARO, Ibaraki 305-0856, Japan
Interests: reverse genetics technique; enteric virus; coronavirus; rotavirus; calicivirus; VLPs (virus-like particles); anti-IgY; animal coronaviruses; animal rotaviruses; pathogenicity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, there were three pandemics in humans by coronaviruses (SARS-CoV, MERS-CoV, and SARS-COV-2) new-emerged with approximately 10 years interval. Their origins might be all derived from animal sources. To prepare for possible emergence of novel coronaviruses, and accelerate development of their prevention and control, it is important to accumulate insights into mechanism of genomic diversity and mutations, dynamics in populations, and evolutionary process of cross-species transmission etc. 

The purpose of this Special Issue is to bring together a series of articles (reviews, research articles, and short communications etc.) related to the genetic diversity, evolution and epidemiology of SARS-CoV-2 related coronaviruses. This virus has still many unclear and interesting things. We welcome submission from many possible areas of interest such as veterinary sciences, environmental and social sciences, theoretical and computational sciences as well as virology, and topics such as predicting SARS-CoV-2 outbreaks in future, discovering new strains in animals and humans, and finding mutations which alter virulence or transmissibility.

Dr. Tohru Suzuki
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. COVID is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • SARS-CoV-2
  • Coronavirus
  • Genetic diversity
  • Evolution
  • Epidemiology
  • Zoonosis

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Published Papers (6 papers)

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8 pages, 666 KiB  
Communication
Genetic Diversity and Spatiotemporal Distribution of SARS-CoV-2 Alpha Variant in India
by Jahnavi Parasar, Rudra Kumar Pandey, Yashvant Patel, Prajjval Pratap Singh, Anshika Srivastava, Rahul Kumar Mishra, Bhupendra Kumar, Niraj Rai, Vijaya Nath Mishra, Pankaj Shrivastava, P. B. Kavi Kishor, Prashanth Suravajhala, Rakesh Tamang, Ajai Kumar Pathak and Gyaneshwer Chaubey
COVID 2023, 3(4), 472-479; https://doi.org/10.3390/covid3040035 - 31 Mar 2023
Cited by 1 | Viewed by 2564
Abstract
After the spill to humans, in the evolutionary timeline of SARS-CoV-2, several positively selected variants have emerged. A phylogeographic study on these variants can reveal their spatial and temporal distribution. In December 2020, the alpha variant of the severe acute respiratory syndrome coronavirus [...] Read more.
After the spill to humans, in the evolutionary timeline of SARS-CoV-2, several positively selected variants have emerged. A phylogeographic study on these variants can reveal their spatial and temporal distribution. In December 2020, the alpha variant of the severe acute respiratory syndrome coronavirus (SARS-CoV-2), which has been designated as a variant of concern (VOC) by the WHO, was discovered in the south-eastern United Kingdom (UK). Slowly, it expanded across India, with a considerable number of cases, particularly in North India. This study focuses on determining the prevalence and expansion of the Alpha variants in various parts of India mainly by using phylospatial analysis. The genetic diversity estimation has helped us to understand various evolutionary forces that have shaped the spatial distribution of this variant during its peak. Overall, our study paves the way to understanding the evolution and expansion of a virus variant, which may help to mitigate in the case of any future wave. Full article
(This article belongs to the Special Issue The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2)
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10 pages, 1702 KiB  
Article
SARS-CoV-2 Lineage P.4 Detection in Southeast Brazil: A Retrospective Genomic and Clinical Overview
by Mirele Daiana Poleti, Jéssika Cristina Chagas Lesbon, Elisângela Chicaroni de Mattos Oliveira, José Salvatore Leister Patané, Luan Gaspar Clemente, Vincent Louis Viala, Gabriela Ribeiro, Jéssica Fernanda Perissato Pinheiro, Marta Giovanetti, Luiz Carlos Junior Alcantara, Loyze Paola Oliveira de Lima, Antonio Jorge Martins, Claudia Renata dos Santos Barros, Elaine Cristina Marqueze, Jardelina de Souza Todão Bernardino, Debora Botequio Moretti, Ricardo Augusto Brassaloti, Raquel de Lello Rocha Campos Cassano, Pilar Drummond Sampaio Corrêa Mariani, Svetoslav Nanev Slavov, Rafael dos Santos Bezerra, Evandra Strazza Rodrigues, Elaine Vieira Santos, Josiane Serrano Borges, Debora Glenda Lima de La Roque, João Paulo Kitajima, Bibiana Santos, Patrícia Akemi Assato, Felipe Allan da Silva da Costa, Cecília Ártico Banho, Lívia Sacchetto, Beatriz de Carvalho Marques, Rejane Maria Tommasini Grotto, Jayme A. Souza-Neto, Maurício Lacerda Nogueira, Luiz Lehmann Coutinho, Rodrigo Tocantins Calado, Raul Machado Neto, Dimas Tadeu Covas, Simone Kashima, Maria Carolina Elias, Sandra Coccuzzo Sampaio and Heidge Fukumasuadd Show full author list remove Hide full author list
COVID 2022, 2(12), 1768-1777; https://doi.org/10.3390/covid2120127 - 5 Dec 2022
Cited by 1 | Viewed by 2148
Abstract
São Paulo state has been the epicenter of the Coronavirus Disease 2019 (COVID-19) in Brazil, ranking first by state with over six million reported cases. In February 2021, the P.4 lineage was reported in 21 cities across the state by public health authorities [...] Read more.
São Paulo state has been the epicenter of the Coronavirus Disease 2019 (COVID-19) in Brazil, ranking first by state with over six million reported cases. In February 2021, the P.4 lineage was reported in 21 cities across the state by public health authorities due to the L452R mutation. Here, by analyzing 17,304 genome sequences of SARS-CoV-2 sampled between February and August of 2021 in 476 distinct cities in São Paulo, we assess the transmission dynamics of the P.4 lineage and other SARS-CoV-2 variants that were, at the time of the study, co-circulating in the state. Additionally, clinical parameters from the city of Araras, São Paulo (N = 251) were considered to estimate the potential risk and mortality rate associated with the P.4 lineage since its higher prevalence was observed in that city. Our data suggest a low frequency (0.55%) of the P.4 lineage across the state, with the gamma variant being the dominant form in all regions (90%) at that time. Furthermore, no evidence of increased transmissibility and disease severity related to the P.4 lineage was observed. The displacement through the time of different lineages in São Paulo highlights how challenging genomic surveillance appears to track the emergence of new SARS-CoV-2 lineages, which could better guide the implementation of control measures. Full article
(This article belongs to the Special Issue The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2)
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9 pages, 14912 KiB  
Communication
Evolution of SARS-CoV-2 Strains in Senegal: From a Wild Wuhan Strain to the Omicron Variant
by Khadim Gueye, Abdou Padane, Cyrille Kouligueul Diédhiou, Samba Ndiour, Ndéye Diabou Diagne, Aminata Mboup, Moustapha Mbow, Cheikh Ibrahima Lo, Nafissatou Leye, Aissatou Sow Ndoye, Anna Julienne Selbé Ndiaye, Seyni Ndiaye, Gora Lo, Djibril Wade, Ambroise Ahouidi, Papa Alassane Diaw, Marièma Sarr, Mamadou Beye, Badara Cissé, Cheikh Sokhna, Makhtar Camara, Ndéye Coumba Touré Kane and Souleymane Mboupadd Show full author list remove Hide full author list
COVID 2022, 2(8), 1116-1124; https://doi.org/10.3390/covid2080082 - 9 Aug 2022
Cited by 4 | Viewed by 4386
Abstract
The coronavirus disease 2019 (COVID-19) is a contagious disease caused by a new coronavirus called SARS-CoV-2. The first case was discovered in Wuhan, China, in December 2019, raising concerns about the emergence of a new coronavirus that poses a significant public health risk. [...] Read more.
The coronavirus disease 2019 (COVID-19) is a contagious disease caused by a new coronavirus called SARS-CoV-2. The first case was discovered in Wuhan, China, in December 2019, raising concerns about the emergence of a new coronavirus that poses a significant public health risk. The objective of this study, based on data collected and sequenced at the Institut de Recherche en Santé, de Surveillance Epidémiologique et de Formations (IRESSEF), is to characterize the pandemic evolution, establish a relationship between the different strains in each wave, and finally determine the phylodynamic evolution of the pandemic, utilizing microreact simulations. The study shows that SARS-CoV-2 strains have evolved over time and the variability of the virus is characterized by sequencing during each wave, as is its contagiousness (the speed at which it spreads). The pandemic has spread at a rate of 44.34 cases/week during the first wave. Twelve weeks later it has risen to 185.33 cases/week during the second wave. Twenty-three weeks into the pandemic, the numbers have reached 681.77 cases/week during the third wave. During the fourth wave, the rate of infection was found to decrease slightly at 646 cases/week between early December 2021 and mid-January 2022. Data collected during this study also provided us with a geographical distribution of COVID-19, indicating that the epidemic started in Dakar before spreading inland. Full article
(This article belongs to the Special Issue The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2)
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19 pages, 4230 KiB  
Article
Variant Analysis and Strategic Clustering to Sub-Lineage of Double Mutant Strain B.1.617 of SARS-CoV-2
by Vishal Mevada, Rajesh Patel, Pravin Dudhagara, Himani Gandhi, Urvisha Beladiya, Nilam Vaghamshi, Manoj Godhaniya and Anjana Ghelani
COVID 2022, 2(5), 513-531; https://doi.org/10.3390/covid2050038 - 20 Apr 2022
Cited by 2 | Viewed by 2665
Abstract
SARS-CoV-2 is an RNA coronavirus responsible for Acute Respiratory Syndrome (COVID-19). In January 2021, the re-occurrence of COVID-19 infection was at its peak, considered the second wave of epidemics. In the initial stage, it was considered a double mutant strain due to two [...] Read more.
SARS-CoV-2 is an RNA coronavirus responsible for Acute Respiratory Syndrome (COVID-19). In January 2021, the re-occurrence of COVID-19 infection was at its peak, considered the second wave of epidemics. In the initial stage, it was considered a double mutant strain due to two significant mutations observed in their Spike protein (E484Q and L452R). Although it was first detected in India later on, it was spread to several countries worldwide, causing high fatality due to this strain. In the present study, we investigated the spreading of B.1.617 strain worldwide through 822 genome sequences submitted in GISAID on 21 April 2021. All genome sequences were analyzed for variations in genome sequences based on their effects due to changes in nucleotides. At Allele frequency 0.05, there were a total of 47 variations in ORF1ab, 22 in Spike protein gene, 6 variations in N gene, 5 in ORF8 and M gene, four mutations in Orf7a, and one nucleotide substitution observed for ORF3a, ORF6 and ORF7b gene. The clustering for similar mutations mentioned B.1.617 sub-lineages. The outcome of this study established relative occurrence and spread worldwide. The study’s finding represented that “double mutant” strain is not only spread through traveling but it is also observed to evolve naturally with different mutations observed in B.1.617 lineage. The information extracted from the study helps to understand viral evolution and genome variations of B.1.617 lineage. The results support the need of separating B.1.617 into sub-lineages. Full article
(This article belongs to the Special Issue The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2)
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14 pages, 2498 KiB  
Article
Forecast of Omicron Wave Time Evolution
by Reinhard Schlickeiser and Martin Kröger
COVID 2022, 2(3), 216-229; https://doi.org/10.3390/covid2030017 - 24 Feb 2022
Cited by 6 | Viewed by 2853
Abstract
The temporal evolution of the omicron wave in different countries is predicted, upon adopting an early doubling time of three days for the rate of new infections with this mutant. The forecast is based on the susceptible–infectious–recovered/removed (SIR) epidemic compartment model with a [...] Read more.
The temporal evolution of the omicron wave in different countries is predicted, upon adopting an early doubling time of three days for the rate of new infections with this mutant. The forecast is based on the susceptible–infectious–recovered/removed (SIR) epidemic compartment model with a constant stationary ratio k=μ(t)/a(t) between the infection (a(t)) and recovery (μ(t)) rates. The assumed fixed early doubling time then uniquely relates the initial infection rate a0 to the ratio k; this way the full temporal evolution of the omicron wave is determined here. Three scenarios (optimistic, pessimistic, intermediate) and the resulting pandemic parameters are considered for 12 different countries. Parameters include the total number of infected persons, the maximum rate of new infections, the peak time and the maximum 7-day incidence per 100,000 persons. The monitored data from Great Britain underwent a clear maximum SDI of 1865 on 7 January 2022. This maximum is a factor 5.0 smaller than our predicted value in the optimistic case and may indicate a dark number of omicron infections of 5.0 in Great Britain. For Germany we predict peak times of the omicron wave ranging from 32 to 38 and 45 days after the start of the omicron wave in the optimistic, intermediate and pessimistic scenario, respectively, with corresponding maximum SDI values of 7090, 13,263 and 28,911. Adopting 1 January 2022 as the starting date our predictions imply the maximum of the omicron wave to be reached between 1 February and 15 February 2022. Rather similar values are predicted for Switzerland. Due to an order of magnitude smaller omicron hospitalization rate, in concert with a high percentage of vaccinated and boosted population, the German health system can cope with a maximum omicron SDI value of 2800 which is about a factor 2.5 smaller than the corresponding value 7090 for the optimistic case. By either reducing the duration of intensive care during peak time, and/or by making use of the nonuniform spread of the omicron wave across Germany, it seems that the German health system can barely cope with the omicron wave and thus avoid triage decisions. The reduced omicron hospitalization rate also causes significantly smaller mortality rates compared to the earlier mutants in Germany. Within the optimistic scenario, we predict 7445 fatalities and a maximum number of 418 deaths/day due to omicron. These numbers range in order of magnitude below the ones known from the beta mutant. Full article
(This article belongs to the Special Issue The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2)
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12 pages, 3075 KiB  
Brief Report
Nonself Mutations in the Spike Protein Suggest an Increase in the Antigenicity and a Decrease in the Virulence of the Omicron Variant of SARS-CoV-2
by Joji M. Otaki, Wataru Nakasone and Morikazu Nakamura
COVID 2022, 2(3), 407-418; https://doi.org/10.3390/covid2030029 - 17 Mar 2022
Cited by 4 | Viewed by 3370
Abstract
Despite extensive worldwide vaccination, the current COVID-19 pandemic caused by SARS-CoV-2 continues. The Omicron variant is a recently emerged variant of concern and is now overtaking the Delta variant. To characterize the potential antigenicity of the Omicron variant, we examined the distributions of [...] Read more.
Despite extensive worldwide vaccination, the current COVID-19 pandemic caused by SARS-CoV-2 continues. The Omicron variant is a recently emerged variant of concern and is now overtaking the Delta variant. To characterize the potential antigenicity of the Omicron variant, we examined the distributions of SARS-CoV-2 nonself mutations (in reference to the human proteome) as five amino acid stretches of short constituent sequences (SCSs) in the Omicron and Delta proteomes. The number of nonself SCSs did not differ much throughout the Omicron, Delta, and reference sequence (RefSeq) proteomes but markedly increased in the receptor binding domain (RBD) of the Omicron spike protein compared to those of the Delta and RefSeq proteins. In contrast, the number of nonself SCSs decreased in non-RBD regions in the Omicron spike protein, compensating for the increase in the RBD. Several nonself SCSs were tandemly present in the RBD of the Omicron spike protein, likely as a result of selection for higher binding affinity to the ACE2 receptor (and, hence, higher infectivity and transmissibility) at the expense of increased antigenicity. Taken together, the present results suggest that the Omicron variant has evolved to have higher antigenicity and less virulence in humans despite increased infectivity and transmissibility. Full article
(This article belongs to the Special Issue The Genetic Diversity, Evolution and Epidemiology of SARS-CoV-2)
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