SARS‐CoV‐2 worldwide replication drives rapid rise and selection of mutations across the viral genome: a time‐course study – potential challenge for vaccines and therapies
2021; Springer Nature; Volume: 13; Issue: 6 Linguagem: Inglês
10.15252/emmm.202114062
ISSN1757-4684
AutoresStefanie Weber, Christina M. Ramirez, Barbara Weiser, Harold Burger, Walter Doerfler,
Tópico(s)Plant Virus Research Studies
ResumoArticle31 May 2021Open Access Transparent process SARS-CoV-2 worldwide replication drives rapid rise and selection of mutations across the viral genome: a time-course study – potential challenge for vaccines and therapies Stefanie Weber Stefanie Weber Institute for Clinical and Molecular Virology, Friedrich-Alexander University (FAU), Erlangen, Germany Search for more papers by this author Christina M Ramirez Christina M Ramirez Department of Biostatistics, UCLA School of Public Health, Los Angeles, CA, USA Search for more papers by this author Barbara Weiser Barbara Weiser Department of Medicine, University of California, Davis, Sacramento, CA, USA Search for more papers by this author Harold Burger Harold Burger Department of Medicine, University of California, Davis, Sacramento, CA, USA Search for more papers by this author Walter Doerfler Corresponding Author Walter Doerfler [email protected] orcid.org/0000-0002-9971-0138 Institute for Clinical and Molecular Virology, Friedrich-Alexander University (FAU), Erlangen, Germany Institute of Genetics, University of Cologne, Cologne, Germany Search for more papers by this author Stefanie Weber Stefanie Weber Institute for Clinical and Molecular Virology, Friedrich-Alexander University (FAU), Erlangen, Germany Search for more papers by this author Christina M Ramirez Christina M Ramirez Department of Biostatistics, UCLA School of Public Health, Los Angeles, CA, USA Search for more papers by this author Barbara Weiser Barbara Weiser Department of Medicine, University of California, Davis, Sacramento, CA, USA Search for more papers by this author Harold Burger Harold Burger Department of Medicine, University of California, Davis, Sacramento, CA, USA Search for more papers by this author Walter Doerfler Corresponding Author Walter Doerfler [email protected] orcid.org/0000-0002-9971-0138 Institute for Clinical and Molecular Virology, Friedrich-Alexander University (FAU), Erlangen, Germany Institute of Genetics, University of Cologne, Cologne, Germany Search for more papers by this author Author Information Stefanie Weber1,†, Christina M Ramirez2,†, Barbara Weiser3, Harold Burger3 and Walter Doerfler *,1,4 1Institute for Clinical and Molecular Virology, Friedrich-Alexander University (FAU), Erlangen, Germany 2Department of Biostatistics, UCLA School of Public Health, Los Angeles, CA, USA 3Department of Medicine, University of California, Davis, Sacramento, CA, USA 4Institute of Genetics, University of Cologne, Cologne, Germany † These authors contributed equally to this work *Corresponding author. Tel: +49 171 205 1587; E-mail: [email protected] EMBO Mol Med (2021)13:e14062https://doi.org/10.15252/emmm.202114062 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Scientists and the public were alarmed at the first large viral variant of SARS-CoV-2 reported in December 2020. We have followed the time course of emerging viral mutants and variants during the SARS-CoV-2 pandemic in ten countries on four continents. We examined > 383,500 complete SARS-CoV-2 nucleotide sequences in GISAID (Global Initiative of Sharing All Influenza Data) with sampling dates extending until April 05, 2021. These sequences originated from ten different countries: United Kingdom, South Africa, Brazil, United States, India, Russia, France, Spain, Germany, and China. Among the 77 to 100 novel mutations, some previously reported mutations waned and some of them increased in prevalence over time. VUI2012/01 (B.1.1.7) and 501Y.V2 (B.1.351), the so-called UK and South Africa variants, respectively, and two variants from Brazil, 484K.V2, now called P.1 and P.2, increased in prevalence. Despite lockdowns, worldwide active replication in genetically and socio-economically diverse populations facilitated selection of new mutations. The data on mutant and variant SARS-CoV-2 strains provided here comprise a global resource for easy access to the myriad mutations and variants detected to date globally. Rapidly evolving new variant and mutant strains might give rise to escape variants, capable of limiting the efficacy of vaccines, therapies, and diagnostic tests. Synopsis This 2020/21 time course study shows the rapid rise of new SARS-CoV-2 mutants and variants across the entire genome during worldwide viral replication. In 10 countries, 40 to 65% of mutants were C to T transitions. Viral mutations will affect vaccination programs. We analyzed > 383,500 SARS-CoV-2 RNA sequences for the occurrence of mutations across the entire genome. The time course of mutations emerging between 01/2020 and 03/2021 was determined. We initially identified ~ 10 prevalent mutations. About 77 to 100 new mutations arose concomitant with the spread of Covid-19 between March/April 2020 and January 2021, followed by the emergence of variants in December 2020. A study of the pathogenicity of viral mutations will help understand Covid-19 outbreaks and symptoms. Monitoring mutant selection will aid Covid-19 diagnosis, vaccine development and therapy. New mutants will compromise vaccine efficiency. Among the SARS-CoV-2 mutants, C to U transitions at a frequency between 40 to 65% were prevalent. Cellular cytosine deaminases, possibly of the APOBEC type, likely drive viral mutagenesis. The paper explained Problem Upon extensive worldwide replication, SARS-CoV-2 mutants with increasing pathogenetic potential were rapidly selected. Details of viral mutagenesis and selection regimes are not understood. Vigorous vaccination programs against SARS-CoV-2 might be met in time by even more dangerous SARS-CoV-2 mutations. Results In several time intervals between January 2020 and March 2021, we inspected >383,500 complete SARS-CoV-2 RNA sequences from 10 different countries for the occurrence of mutations. In >1,700 sequences, the amino acid exchanges were also assigned. While up to April 2020, about 10 mutations were prevalent, the 77 to 100 new mutations expanded gradually in time intervals up to January 2021 when the complex variants of concern evolved in England, South Africa, and Brazil. Mutations were not confined to the spike protein but spanned the viral genome, and replacements rose up to 90% of RNA molecules. The disproportionate incidence of cytidine to uracil transitions might be due to cellular cytidine deaminases, possibly of the APOBEC type. Impact Our data document speed and efficiency of SARS-CoV-2 mutant selection that might gradually cause problems for therapeutic and vaccination programs. Viral mutant watch must go beyond the spike glycoprotein and include replication functions, the nucleocapsid phosphoprotein, and the poorly charted open reading frames of the viral genome. Introduction Between December 2019 and January 28, 2021, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has expanded worldwide to 219 countries and territories; about 101.9 million people have been infected, and about 2.2 million (2.16%) have lost their lives according to Johns Hopkins (Dong et al, 2020). Note added in proof: As of May 04, 2021, 154.4 million COVID-19 cases and 3.23 million fatalities (2.09%) have been reported worldwide (https://www.worldometers.info/coronavirus/). In our laboratory, we have set out to follow the rapid rise of new mutations in the SARS-CoV-2 genome as COVID-19 cases soared worldwide. We identified mutation hotspots in different populations. Initially, we analyzed SARS-CoV-2 sequences that had been deposited in databases between January and May/June of 2020. At least 10 prevalent sites of sequence mutations were observed and up to 80% of nucleotides at the mutated site had been exchanged (Weber et al, 2020). Several of these mutations led to non-synonymous amino acid changes in different open reading frames across the viral genome. These alterations in functional viral proteins were selected during active worldwide replication of SARS-CoV-2. We have now extended the time frame of mutant analyses to January 20 and for that of variants further to March 31, 2021 and found increased prevalence of mutations along the genome worldwide. We specifically examined mutations from the United States, India, Brazil, Russia, the UK, France, Spain, Germany, South Africa, and China that were deposited in the GISAID (Global Initiative of Sharing All Influenza Data) database (Elbe & Buckland-Merritt, 2017). As of January 28, 2021, infection rates worldwide were extremely high, surpassing the levels seen at the peak in April 2020 (Dong et al, 2020). The uncontrolled spread has led to a proliferation of mutants and variants, which we define as viruses with a specific set of mutations. The so-called UK variant, also known as B.1.1.7 or alternatively VOC202012/01, was first identified in England in September 2020 and reported on December 8 as a rapidly spreading variant of concern that had 14 mutations in total and three deletions (for details, see Table 1) (https://virological.org/t/preliminary-genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-the-uk-defined-by-a-novel-set-of-spike-mutations/563). Some of the mutations involve the gene for the Spike protein, which mediates binding, fusion, and entry of the virus into the host cell. One of these deletions, H69/V70 del (ΔH69/ΔV70), has been reported to emerge during convalescent plasma treatment (preprint: Kemp et al, 2021). Another Spike mutation, N501Y, is of concern, has been suggested to interact with ACE2, and could reduce the effectiveness of neutralizing antibodies (Yi et al, 2020). This variant has been associated with higher transmissibility (https://khub.net/documents/135939561/338928724/SARS-CoV-2+variant+under+investigation%2C+meeting+minutes.pdf/962e866b-161f-2fd5-1030-32b6ab467896; Volz et al, 2021) and at least one confirmed case of reinfection (Harrington et al, 2021) leading to lockdowns and travel bans in efforts to contain its spread. On December 23, 2020, the time of the lockdown, the variant was already found in Australia, Denmark, and Italy. As of April 5, 2021, this variant has been reported in 108 countries according to GISAID (https://www.gisaid.org/hcov19-variants) (Table 2). Table 1. Mutations associated with variants B.1.1.7 (UK), B.1.135 (South Africa), P.1 (Brazil), P.2 (Brazil), B.1.525 (New York), B.1.526 (New York), B.1.427 (California), and B.1.429 (California). Gene B. 1. 1.7 B.1.135 P.1 P.2 B.1.525 B.1.526 B.1.427 B.1.429 Mutation Mutation Mutation Mutation Mutation Mutation Mutation Mutation ORF1ab T1001I P314F P314L L452R S13I A1708D T2007O Q1011H D614G W152C I2230T T265I L452R L3201P D614G SGF 3675-3677 del SGF 3675-3677 del SGF 3675-3677 del 3575-3677 del nsp5 L205V nsp6 Spike H69/V70 del L18F A67V L5F* Y144 del D80A H68/V70del T95I N501Y D215G Y144del D253G A570D R246I S477N* P681H K417N K417N T716I E484K E484K E484K E484K E484K* S982A N501Y N501Y D614G D118H A701Y V1176F Q677H *not in all sequences F888L Orf8 Q27stop R52I Y73C Nucleocapsid D3L A119S A12G S235F R203K T205I G204R M234I Table 2. B.1.1.7, B.1.351, P.1, B.1.427 + B.1.429, B.1.525: Variants of concern/interest of SARS-CoV-2 by country as of March 31, 2021. Currently, new variants are being detected and characterized in rapid succession. This Table could be outdated by the time of publication. For updating of data, consult GISAID (Shu & McCauley, 2017). Country B.1.1.7 B.1.351 P.1 B.1.429 & B.1.427 B.1.525 Albania 28 0 0 0 0 Angola 6 7 0 0 1 Argentina 2 0 0 1 0 Aruba 120 2 1 31 0 Australia 242 38 4 17 8 Austria 414 167 0 2 3 Bangladesh 10 19 0 0 0 Barbados 3 0 0 0 0 Belarus 1 0 0 0 0 Belgium 5,302 655 223 1 24 Bonaire 91 0 0 0 0 Bosnia and Herzegovina 21 0 0 0 0 Botswana 0 54 0 0 0 Brazil 71 1 641 0 0 British Virgin Islands 0 0 0 1 0 Brunei 0 1 0 0 0 Bulgaria 659 0 0 0 0 Cambodia 7 0 0 2 0 Cameroon 0 1 0 0 1 Canada 2,395 38 150 13 13 Cayman Islands 2 0 0 0 0 Chile 30 0 42 10 0 China 14 1 0 0 0 Colombia 0 0 23 1 0 Comoros 0 6 0 0 0 Costa Rica 4 2 0 3 1 Cote d'Ivoire 7 0 0 0 4 Croatia 352 7 0 0 0 Curacao 107 0 0 0 0 Cyprus 10 0 0 0 0 Czech Republic 863 8 0 0 0 Democratic Republic of the Congo 2 1 0 0 0 Denmark 4,889 12 0 25 121 Dominican Republic 4 0 0 0 0 Ecuador 14 0 0 0 0 England 1 0 0 0 0 Estonia 273 3 0 0 0 Eswatini 0 20 0 0 0 Faroe Islands 0 0 1 0 0 Finland 400 9 0 1 4 France 6,290 537 38 4 30 French Guiana 4 0 8 0 0 Gambia 3 0 0 0 0 Georgia 2 0 0 0 0 Germany 21,038 652 63 6 123 Ghana 116 4 0 0 6 Gibraltar 131 0 0 0 0 Greece 70 0 0 0 0 Guadeloupe 9 1 0 3 2 Guam 0 0 0 7 0 Hungary 29 0 0 0 0 Iceland 20 0 0 0 0 India 151 15 0 0 17 Indonesia 10 34 0 0 0 Iran 1 65 0 0 0 Ireland 4,583 39 11 0 16 Israel 1,769 0 0 7 0 Italy 6,909 0 394 1 73 Jamaica 4 0 0 0 0 Japan 456 22 25 17 11 Jordan 50 2 3 0 2 Kenya 20 37 0 0 0 Kosovo 3 0 0 0 0 Kuwait 1 0 0 0 0 Latvia 150 0 0 0 0 Lebanon 2 0 0 0 0 Lesotho 0 14 0 0 0 Lithuania 413 5 0 0 0 Luxembourg 669 180 3 0 1 Malawi 1 152 0 0 0 Malaysia 3 9 0 0 2 Martinique 6 0 0 0 0 Mauritius 1 2 0 0 0 Mayotte 1 378 0 0 1 Mexico 33 0 5 146 0 Moldova 3 0 0 0 0 Monaco 1 1 0 0 0 Montenegro 7 0 0 0 0 Morocco 1 0 0 0 0 Mozambique 0 58 0 0 0 Namibia 0 9 0 0 0 Netherlands 6,854 341 59 5 36 New Zealand 98 23 4 4 0 Nigeria 128 0 0 0 0 North Macedonia 60 0 0 1 106 Northern Mariana Islands 0 0 0 1 0 Norway 1,630 190 1 2 22 Oman 1 0 0 0 0 Pakistan 7 0 0 0 0 Panama 0 1 0 0 0 Paraguay 0 0 5 0 0 Peru 3 0 23 0 0 Philippines 39 0 0 0 0 Poland 1,987 10 0 0 9 Portugal 1,701 48 20 0 3 Reunion 0 16 0 0 0 Romania 191 1 2 0 0 Russia 11 3 0 0 0 Rwanda 3 11 0 0 5 Saint Lucia 9 0 0 0 0 Senegal 3 0 0 0 0 Serbia 2 0 0 0 0 Singapore 88 71 0 4 3 Sint Maarten 27 0 1 13 30 Slovakia 609 7 0 0 0 Slovenia 839 25 1 0 0 South Africa 1 1,670 0 0 0 South Korea 103 5 1 47 1 Spain 4,352 31 20 2 18 Sri Lanka 19 1 0 0 1 Sweden 4,290 296 15 2 0 Switzerland 5,134 125 29 4 9 Taiwan 5 6 0 7 0 Thailand 12 0 0 0 1 Togo 2 1 0 0 0 Trinidad and Tobago 1 0 0 0 0 Tunisia 1 0 0 0 0 Turkey 522 112 5 2 12 Ukraine 22 0 0 0 0 United Arab Emirates 21 5 0 0 0 United Kingdom 187,267 434 31 16 275 United States 15,117 290 252 23,328 182 Vietnam 11 0 0 0 0 Zambia 0 31 0 0 0 Zimbabwe 0 194 0 0 0 On December 18, 2020, another variant of concern, unrelated to the UK variant but also having the N501Y mutation, was announced in South Africa and was dubbed 501Y.V2 or B.1.351 (Tegally et al, 2021). This variant is characterized by eight mutations in the Spike including K417N, E484K, and N501Y (https://virological.org/t/a-preliminary-selection-analysis-of-the-south-african-v501-v2-sars-cov-2-clade/573; Tegally et al, 2021) (Table 1). As of January 29, 2021, this variant has been reported in 68 countries and five continents. Also rising independently are two Brazil variants that are now called P.1 and P.2. P.1 that have 17 unique amino acid changes, three deletions, four synonymous mutations, and one 4 nucleotide insertion (preprint: Faria et al, 2021) (Table 1). P.1 shares the N501Y and a deletion in ORF1ab with both the UK and the South Africa variant. It is interesting to note that the N501Y mutation was not widely spread in Brazil before this variant was described while the E484K is more prevalent, although Brazil is not sequencing large numbers of samples. The E484K and the N501Y mutations are of particular concern in that they have been suggested to reduce neutralization by antibodies and increase the affinity for ACE2. P.1 and B.1.351 share both mutations N501Y and E484K (Table 1). P.1 has been associated with a case of documented reinfection (https://virological.org/t/sars-cov-2-reinfection-by-the-new-variant-of-concern-voc-p-1-in-amazonas-brazil/596), and 225 cases have been reported in the United States, and cases from 32 other countries have been deposited into GISAID. P.2, unrelated to P.1, is characterized by the E484K mutation and has been implicated in two cases of reinfection (Nonaka et al, 2021; https://virological.org/t/spike-e484k-mutation-in-the-first-sars-cov-2-reinfection-case-confirmed-in-brazil-2020/584). Analysis of samples in Southern California led to the identification of the "California variant" (Zhang et al, 2021) also known as B.1.429 or B.1.427 (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/COVID-Variants.aspx) depending on the pattern of mutations. Table 1 describes the pattern of mutations. The New York variant was described during the same time period (preprint: Annavajhala et al, 2021; preprint: West et al, 2021), although it is not deemed a variant of concern yet. The B.1.525 was also found in New York and is a variant of interest (https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/variant-surveillance/variant-info.html). These variants have caused concerns regarding efficacy of the vaccines. Recently, preprint: Wang et al (2021) described the efficacy of mRNA-1273 vaccine against many spike mutations tested both separately and in combination. They show that sera from both vaccinated non-human primates and vaccinated humans are effective against the UK variant and various other spike mutations. They also found neutralization, albeit at lower levels, against the full South Africa variant B.1.135. It has been shown that the Pfizer BNT162b2 vaccine is effective against the N501Y mutant alone (Xie et al, 2021) as well as the UK variant B.1.117 (Collier et al, 2021). There have also been preliminary data from two other vaccine manufacturers showing efficacy against the South African variant. To illustrate the rise of mutations and variants over time, we list the number of variants and mutations deposited in GISAID worldwide across time (Figure 1). Table 2 lists the number of variant sequences deposited in GISIAD by country. Figure 1.Relative proportions of mutations and variants of concern deposited to GISAID as of March 31. Time course study. Download figure Download PowerPoint The rapid appearance of the variants across the world illustrates the importance of sequencing viral pathogens and tracking mutations. There is emerging evidence that these variants may alter transmissibility and have the potential to reduce the efficacy of existing COVID-19 vaccines. Sequencing SARS-CoV-2 is both a scientific and clinical imperative (https://www.cogconsortium.uk/wp-content/uploads/2021/01/Report-2_COG-UK_SARS-CoV-2-Mutations.pdf). Because nucleic acid sequencing of SARS-CoV-2 samples is not part of routine clinical practice at this time, it is necessary to institute programs to monitor sequence variation as a matter of course in order to detect mutations in the viral genome. A consequence of the lack of routine viral sequencing is that it may contribute to selection bias. Sequences deposited to GISAID may not be representative of viral prevalence as different countries contribute different numbers of sequences. It is also possible that selection bias may be inherent, as different countries deposit sequences at different rates and often not at random. It may be the case that more interesting samples or those deemed more likely to be a variant are preferentially sequenced. This is a likely case for samples that are selected for sequencing due to SGTF (spike gene target failure). It has been found that the Spike ΔH69/ΔV70 causes the so-called S dropout, rendering the nucleic acid test (NAT) negative for Spike (S) and positive for nucleocapsid (N). As this is one of the mutations in B.1.1.7, it has been used as a screening tool for this variant (preprint: Washington et al, 2021). While useful for screening, this deletion might create selection bias because patients who were positive for SARS-CoV-2 with an S dropout may have their samples preferentially sequenced as the prevalence for the new variant is being assessed. Rapid increases in the number and types of new SARS-CoV-2 mutations in the world population within a time span of weeks to months are a remarkable biologic event. The uncontrolled rapid replication of SARS-CoV-2 in an immunologically naïve world population since early 2020 constituted a wake-up call of the need to sequence and track the evolution of novel pathogens as these mutations and variants have raised concerns regarding increased transmissibility, immune escape, and the efficacy of vaccines and the validity of diagnostic tests. Results Time course of emerging mutations in ten different countries We examined mutations in 383,570 complete sequences with known sampling dates in GISAID up until January 20, 2021. Figure 1 shows the worldwide distribution of Spike mutations as well as other variants of interest over time from April 2020 to March 31, 2021, from complete sequences with a known collection date deposited in GISAID. Table 1 lists the signature mutations for the variants. Table 2 shows the total number of complete sequences each variant of interest (B.1.1.7 (the UK variant), 501Y.V2 (the South African variant) and 484K.V2 (B.1.1 lineage with S: E484K/D614G, V1176F N: A199S/R203K/G204R) deposited in GISAID by each country as of March 31, 2021. Selection of novel mutations in humans was rapid and frequent in 2020. Among the novel mutations discovered in the current study, some were seen only in one country and others occurred in several different countries. We will present the identified mutations arising in the SARS-CoV-2 RNA country by country for the designated time periods (Tables 3–12). The data covering time course analyses of the appearance of mutations and their nature in most of the ten different countries are presented in Tables 3A–12A. The corresponding B Tables summarize the total number of mutations in individual sequence position at a cutoff of 2% preponderance for the time period 01/19/2020 to 01/20/2021, i.e., of the entire first COVID-19 year. Of course, it can be argued that a cutoff for the registration of mutants at 2% incidence is arbitrary. However, we cannot predict with certainty which mutations at low incidence of occurrence at present will become more predominant in the future during rapid worldwide viral replication in the current pandemic. A feasible strategy will be to install mutant watch programs and remain on the alert for the rise of new mutations. This strategy can be implemented only by highly efficient SARS-CoV-2 RNA sequencing strategies that will have to be instituted as widely as possible and without delay. Table 3. United Kingdom. Position Location Mutation 01/19/2020–01/20/2021 Total Count Percentage 66nt 5´UTR C → T 2,787 3.9 204nt G → T 20,770 29.07 241nt C → T 69,160 96.81 445nt ORF1ab polyprotein → leader protein T → C 34,505 48.3 1,163nt nsp2 A → T 2,544 3.56 1,210nt G → T 1,440 2.02 1,513nt C → T 1,528 2.14 1,947nt T → C 1,576 2.21 1,987nt A → G 3,018 4.22 3,037nt nsp3 C → T 69,231 96.91 3,256nt T → C 2,523 3.53 4,002nt C → T 1,519 2.13 4,543nt C → T 1,516 2.12 6,286nt C → T 34,650 48.5 6,807nt C → T 2,220 3.11 7,528nt C → T 1,524 2.13 7,926nt C → T 2,818 3.94 8,683nt nsp4 C → T 2,189 3.06 9,745nt C → T 3,640 5.1 9,802nt G → T 1,449 2.03 10,097nt 3C-like proteinase G → A 2,954 4.13 10,870nt G → T 3,186 4.46 11,083nt nsp6 G → T 5,734 8.03 11,396nt C → T 2,286 3.2 11,533nt A → G 1,960 2.74 11,781nt A → G 2,368 3.31 12,067nt nsp7 G → T 1,709 2.39 13,536nt RNA-dependent RNA polymerase C → T 1,502 2.1 14,202nt G → T 2,522 3.53 14,408nt C → T 69,237 96.92 14,805nt C → T 1,860 2.6 15,406nt G → T 2,077 2.91 18,877nt 3'-to-5' exonuclease C → T 3,827 5.36 19,542nt G → T 2,582 3.61 19,718nt endoRNAse C → T 2,645 3.7 20,268nt A → G 1,999 2.8 21,255nt 2'-O-ribose methyltransferase G → C 34,494 48.28 21,575nt Spike glycoprotein C → T 1,502 2.1 21,614nt C → T 17,561 24.58 21,637nt C → T 2,697 3.78 22,227nt C → T 34,855 48.79 22,346nt G → T 2,244 3.14 22,377nt C → T 1,518 2.12 22,388nt C → T 2,540 3.56 22,444nt C → T 2,085 2.92 22,992nt G → A 1,636 2.29 23,403nt A → G 69,262 96.95 23,731nt C → T 2,940 4.12 24,334nt C → T 10,442 14.62 25,563nt ORF3a G → T 5,774 8.08 25,614nt C → T 2,737 3.83 26,060nt C → T 2,632 3.68 26,144nt G → T 1,748 2.45 26,424nt Envelope protein T → C 1,957 2.74 26,735nt Membrane glycoprotein C → T 3,760 5.26 26,801nt C → G 34,459 48.24 27,769nt ORF7b C → T 2,706 3.79 27,944nt ORF8 C → T 25,177 35.24 28,169nt A → G 2,693 3.77 28,854nt Nucleocapsid phosphoprotein C → T 3,683 5.16 28,881nt G → A 23,975 33.56 28,882nt G → A 23,947 33.52 28,883nt G → C 23,946 33.52 28,932nt C → T 34,536 48.34 29,227nt G → T 2,566 3.59 29,366nt C → T 1,743 2.44 29,466nt C → T 2,578 3.61 29,555nt At upstream downstream region of ORF10 ORF9 C → T 1,466 2.05 29,645nt ORF10 G → T 34,684 48.55 29,771nt 3´UTR A → G 2,475 3.46 Details of the mutant analyses of 7,144 SARS-CoV-2 isolates for deviations from the Wuhan reference sequence. These sequences were deposited in the GISAID initiative between 01/19/2020 and 01/20/2021. For design of Tables, see legend to Table 5. Table 4. South Africa. (A) 09/01–12/07/2020 Position Location Mutation Count Incidence 174nt 5´UTR GT → TT 12/95 DE,US noneffective 241nt CG → TG 95/95 Prevalent noneffective 1,059nt nsp2 CC → TC 10/95 Prevalent ACC (Threonine) → ATC (Isoleucine) 2,164nt GA → CA 11/95 IN GAGAAG (Glutamic Acid Lysine) → GACAAG (Aspartic Acid Lysine) 3,037nt nsp3 CT → TT 95/95 Prevalent noneffective 5,230nt GT → TT 12/95 DE AAGTGG (Lysine Tryptophan) → AATTGG (Asparagine Tryptophan) 6,762nt CT → TT 13/95 Unique ACT (Threonine) → ATT (Isoleucine) 10,323nt 3C-like proteinase AG → GG 11/95 Unique AAG (Lysine) → AGG (Arginine) 11,230nt nsp6 GC → TC 11/95 Unique ATGCCT (Methionine Proline) → ATTCCT (Isoleucine Proline) 12,503nt nsp8 TA → CA 26/95 Unique TAT (Tyrosine) → CAT (Histidine) 14,408nt RNA-dependent RNA polymerase CT → TT 95/95 Prevalent CCT (Proline) → CTT (Leucine) 20,268nt endoRNAse AG → GG 21/95 FR,ES,RU noneffective 21,801nt Spike glycoprotein AT → CT 10/95 Unique GAT (Aspartic Acid) → GCT (Alanine) 22,675nt CG → TG 10/95 Unique noneffective 22,813nt GA → TA 10/95 DE noneffective 23,012nt GA → AA 12/95 IN GAA (Glutamic Acid) → AAA (Lysine) 23,403nt AT → GT 95/95 Prevalent GAT (Aspartic Acid) → GGT (Glycine) 23,664nt CA → TA 14/95 ES,IN GCA (Alanine) → GTA (Valine) 25,563nt ORF3a protein GA → TA 10/95 Prevalent CAGAGC (Glutamine Serine) → CATAGC (Histidine Serine) 25,770nt GC → TC 20/95 RU AGGCTT (Arginine Leucine) → AGTCTT (Serine Leucine) 25,904nt CA → TA 10/95 BR,DE TCA (Serine) → TTA (Leucine) 26,456nt Envelope protein CT → TT 10/95 Unique CCT (Proline) → CTT (Leucine) 28,253nt ORF8 protein CA → TA 14/95 BR,DE,ES,FR,US noneffective 28,854nt Nucleocapsid phosphoprotein CA → TA 23/95 CN,DE,ES,FR,IN,RU TCA (Serine) → TTA (Leucine) 28,881nt GGG → AAC 61/95 Prevalent AGGGGA (Arginine Glycine) → AAACGA (Lysine Arginine) 28,887nt CT → TT 11/95 BR,CN,FR,IN,RU ACT (Threonine) → ATT (Isoleucine) 29,721nt 3´UTR CC → TC 26/95 Unique noneffective (B) 01/19/2020–01/20/2021 Position Location Mutation Total Count Percentage 174nt 5´UTR G → T 181 10.17 241nt C → T 1,772 99.61 355nt ORF1ab polyprotein → leader protein C → T 59 3.32 1,059nt nsp2 C → T 149 8.38 2,094nt C → T 38 2.14 2,164nt G → C 84 4.72 2,692nt A → T 41 2.3 3,037nt nsp3 C → T 1,746 98.15 4,002nt C → T 165 9.27 4,093nt C → T 48 2.7 5,230nt G → T 147 8.26 6,027nt C → T 46 2.59 6,762nt C → T 178 10.01 7,064nt A → G 124 6.97 8,660nt nsp4 C → T 69 3.88 8,964nt C → T 69 3.88 9,498nt T → C 36 2.02 10,097nt 3C-like proteinase G → A 163 9.16 10,323nt A → G 169 9.5 11,083nt nsp6 G → T 60 3.37 11,230nt G → T 75 4.22 11,447nt G → A 129 7.25 12,503nt nsp8 T → C 389 21.87 13,536nt RNA-dependent RNA polymerase C → T 170 9.56 14,408nt C → T 1,773 99.66 14,925nt C → T 71 3.99 16,376nt Helicase C → T 54 3.04 16,490nt C → T 39 2.19 16,853nt G → T 47 2.64 16,946nt C → T 43 2.42 18,747nt 3'-to-5' exonuclease C → T 115 6.46 20,234nt endoRNAse C → T 42 2.36 20,268nt A → G 209 11.75 21,801nt Spike glycoprotein A → C 142 7.98 22,206nt A → G 71 3.99 22,287nt T → A 86 4.83 22,299nt G → T 69 3.88 22,675nt C → T 290 16.3 22,813nt G → T 139 7.81 23,012nt G → A 146 8.21 23,063nt A → T 140 7.87 23,403nt A → G 1,772 99.61 23,625nt C → T 53 2.98 23,664nt C → T 154 8.66 23,731nt C → T 161 9.05 25,455nt ORF3a G → T 65 3.65 25,521nt C → T 66 3.71 25,563nt G → T 148 8.32 25,770nt G → T 285 16.02 25,904nt C → T 143 8.04 26,456nt Envelope protein C → T 140 7.87 26,586nt Membrane glycoprotein C → T 62 3.49 27,384nt ORF6 T → C 120 6.75 27,504nt ORF7a T → C 50 2.81 28,077nt ORF8 G → T 74 4.16 28,253nt C → T 178 10.01 28,854nt Nucleocapsid phosphoprotein C → T 173 9.72 28,881nt G → A 1,238 69.59 28,882nt G → A 1,238 69.59 28,883nt G → C 1,238 69.59 28,887nt C → T 152 8.54 29,425nt G → T 117 6.58 29,721nt 3´UTR C → T 388 21.81 The Table presents characteristics of SARS-CoV-2 mutan
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