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. 2020 Dec 8;68(6):3288–3304. doi: 10.1111/tbed.13931

Global SNP analysis of 11,183 SARS‐CoV‐2 strains reveals high genetic diversity

Fangfeng Yuan 1, Liping Wang 2, Ying Fang 1, Leyi Wang 3,✉
PMCID: PMC7753349  PMID: 33207070

Abstract

Since first identified in December of 2019, COVID‐19 has been quickly spreading to the world in few months and COVID‐19 cases are still undergoing rapid surge in most countries worldwide. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), adapts and evolves rapidly in nature. With the availability of 16,092 SARS‐CoV‐2 full genomes in GISAID as of 13 May, we removed the poor‐quality genomes and performed mutational profiling analysis for the remaining 11,183 viral genomes. Global analysis of all sequences identified all single nucleotide polymorphisms (SNPs) across the whole genome and critical SNPs with high mutation frequency that contributes to five‐clade classification of global strains. A total of 119 SNPs were found with 74 non‐synonymous mutations, 43 synonymous mutations and two mutations in intergenic regions. Analysis of geographic pattern of mutational profiling for the whole genome reveals differences between each continent. A transition mutation from C to T represents the most mutation types across the genome, suggesting rapid evolution and adaptation of the virus in host. Amino acid (AA) deletions and insertions found across the genome results in changes in viral protein length and potential function alteration. Mutational profiling for each gene was analysed, and results show that nucleocapsid gene demonstrates the highest mutational frequency, followed by Nsp2, Nsp3 and Spike gene. We further focused on non‐synonymous mutational distributions on four key viral proteins, spike with 75 mutations, RNA‐dependent‐RNA‐polymerase with 41 mutations, 3C‐like protease with 22 mutations and Papain‐like protease with 10 mutations. Results show that non‐synonymous mutations on critical sites of these four proteins pose great challenge for development of anti‐viral drugs and other countering measures. Overall, this study provides more understanding of genetic diversity/variability of SARS‐CoV‐2 and insights for development of anti‐viral therapeutics.

Keywords: 3CLpro , complete genome sequence, PLpro , RdRp, S protein, SARS‐CoV‐2, SNP analysis

1. INTRODUCTION

Coronavirus (CoV) is a single‐stranded positive‐sense RNA virus in the order Nidovirales, family Coronaviridae. Based on genetic characterization, CoVs are classified into four genera, α, β, γ and δ (Fehr & Perlman, 2015). There are seven known human coronaviruses with two (229E and NL63) in α genus and five (OC43, HKU1, severe acute respiratory syndrome coronavirus (SARS‐CoV), Middle East Respiratory Syndrome CoV and SARS‐CoV‐2) in β genus (Liu et al., 2020; Ye et al., 2020). SARS‐CoV‐2 was reported to be the causative agent for the novel respiratory disease, COVID‐19 (Zhu et al., 2020). The disease was declared to be a pandemic by WHO early this year and has led to more than 32 million infected and 981,000 dead. SARS‐CoV‐2 RNA genome encodes 16 non‐structural proteins (Nsp) and at least 10 structural proteins including spike (S), ORF3a, envelop (E), membrane (M), open reading frame 6 (ORF6), ORF7a, ORF7b, ORF8, nucleocapsid (N) and ORF10 (Cagliani et al., 2020; Kim et al., 2020). S protein contains receptor‐binding domain (RBD) that directly binds to human receptor angiotensin‐converting enzyme 2 (ACE2) and induces neutralizing antibody response against SARS‐CoV‐2 (Cao et al., 2020; Lan et al., 2020). Previous studies showed that antibody response against SARS‐CoV‐2 is mainly against S and N proteins (Erasmus et al., 2020; To et al., 2020). RNA viruses possess a high mutation rate of genome and readily adapt to changing environmental conditions (Elena & Sanjuán, 2005). Thus, a swarm of variants exist in RNA virus populations. A systemic tracking of SARS‐CoV‐2 mutations allows monitoring of circulating strains around the world (Guan et al., 2020) and provides guidance for development of countering measures.

Since the first report of SARS‐CoV‐2, whole‐genome sequences of the virus have been uploaded to the public available website, GISAID. Nextstrain employed nomenclature through designation of SARS‐CoV‐2 clades to label well‐defined clades that reached geographic spread with significant frequency. Major clades were named by the year that emerged and a letter. Current clades on Nextstrain tree include 19A, 19B, 20A, 20B and 20C (Hadfield et al., 2018). Another clade definition in GISAID used genetic markers and defined six clades including S, L, V, G, GH and GR. L was split into G and V in March (Tang et al., 2020). In order to characterize the mutational patterns and distributions across the whole genome, we performed a mega data analysis of 11,183 high‐quality sequences from GISAID as of 13 May. Geographical distribution of mutations was analysed, and we further focused on four key viral proteins including S, RNA‐dependent‐RNA‐polymerase (RdRp), 3C‐like protease (3CLpro) and Papain‐like protease (PLpro). Potential functional impacts of mutations were evaluated. This study provides more evidence of SARS‐CoV‐2 genetic diversity, and mutations on key viral proteins may affect development of anti‐viral therapeutics.

2. METHODS AND METHODS

2.1. Sequence source and analysis

As of 13 May, there are 16,092 high coverage full genomes available in GISAID (Shu & McCauley, 2017). All were downloaded and of which 4,909 were removed due to their poor assembly quality resulting in 11,183 complete genomes used for subsequent analysis. MAFFT was employed for sequence alignment referenced to Wuhan‐hu‐1 strain (MN908947.3). Alignment results were further processed and analysed through CLC Genomics Workbench 11 (QIAGEN) and UGene (http://ugene.net). Statistical data analysis was performed on Excel (Microsoft) and GraphPad Prism software (GraphPad Software, Inc.). To determine the viral diversity and credibility of mutations across the genome, the entropy of nucleotide sequences was calculated using BioEdit software version 7.0.9.0 (Hall, 1999). [Correction added on 27 May 2021, after first online publication: In this paragraph, the reference “Shu & McCauley, 2017” has been included at the end of the first sentence in this current version.]

2.2. Protein structural analysis

Protein structures for RdRp, S and 3CLpro were obtained from the Protein Data Bank (PDB). For SARS‐CoV‐2 PLpro structure, homology modelling was carried out by using I‐TASSER (Yang et al., 2015) based on SARS‐CoV PLpro structure. Structural homology with highest C scores was selected for analysis. Visualization of protein structures was performed through PyMOL (PyMOL Molecular Graphics System, version 1.7; Schrödinger, LLC).

3. RESULTS

3.1. Global SNPs across the genome and their geographical distribution

A total of 16,092 complete genomes with high coverage as of 13 May were downloaded from GISAID. After removal of 4,909 problematic sequences using stringent inclusion criteria (any N in the genome), 11,183 sequences were included for analysis. Since a large number of sequences do not have authentic or high‐quality sequences for both 5’ and 3’ un‐translational region (Singh et al., 2020), terminal sequences for both ends were removed and only regions (266–29674nt) from polyprotein to the last open reading frame (Bal et al., 2020) sequences were included. Alignment against the reference strain, Wuhan‐hu‐1 (MN908947.3), was performed using MAFFT (Katoh et al., 2017; Rozewicki et al., 2019). For global sequences analysed, an initial threshold setting of 1% (>111) was made to identify classified clades around the globe (Table 1). A low threshold of 0.3% (>33) was also set to identify a site of interest (Table S1). A 0.3% threshold was also applied to countries/regions with more than 333 sequences, and for those countries/regions with less than 333 sequences, single nucleotide polymorphisms (SNPs) with at least two sequences were recorded.

TABLE 1.

Global nucleotide and amino acid mutations across the genome for threshold above 1%

Name (Clade) Position Count Gene Nucleotide change Amino acid change Entropy Name (Clade) Position Count Gene Nucleotide change Amino acid change Entropy
313 127 NSP1 C/T Synonymous 0.06307 18877 380 NSP14 C/T Synonymous 0.14832
490 132 NSP1 T/A D/E 0.06413 18998 133 NSP14 C/T A/V 0.06453
514 112 NSP1 T/C Synonymous 0.06019 19839 112 NSP15 T/C Synonymous 0.05607
A (20C) 1059 2679 NSP2 C/T T/I 0.55524 20268 576 NSP15 A/G Synonymous 0.20476
1397 140 NSP2 G/A V/I 0.06728 J (19A) 23403 7590 Spike A/G D/G 0.63444
1440 164 NSP2 G/A G/D 0.07648 23731 142 Spike C/T synonymous 0.07145
2416 188 NSP2 C/T Synonymous 0.08535 23929 125 Spike C/T Synonymous 0.06319
2480 258 NSP2 A/G I/V 0.11068 24034 150 Spike C/T Synonymous 0.07208
2558 282 NSP2 C/T P/S 0.11862 25429 164 ORF3a G/T V/L 0.07820
2891 152 NSP3 G/A A/T 0.07873 K (20C) 25563 3276 ORF3a G/T Q/H 0.61047
B (19A) 3037 7552 NSP3 C/T Synonymous 0.63571 L (19A) 26144 772 ORF3a G/T G/V 0.25430
3177 134 NSP3 C/T P/L 0.06664 26530 120 M A/G D/G 0.06549
6312 128 NSP3 C/A T/K 0.06766 26729 138 M T/C Synonymous 0.06650
C (19B) 8782 1480 NSP4 C/T Synonymous 0.39487 26735 149 M C/T Synonymous 0.07169
10097 138 3CLpro G/A G/S 0.06897 27046 260 M C/T T/M 0.11227
D (19A) 11083 1161 NSP6 G/T L/F 0.35912 27964 251 ORF8 C/T S/L 0.10741
11916 179 NSP7 C/T S/L 0.08298 28077 144 ORF8 G/ V/L 0.08078
13730 147 RdRp C/T A/ L 0.07000 M (19A) 28144 1476 ORF8 T/C L/ S 0.39349
E (20A) 14408 7564 RdRp C/ T P/ L 0.63513 28311 149 N C/T P/ L 0.07730
F 14805 816 RdRp C/ T Synonymous 0.26613 28688 136 N T/C Synonymous 0.06756
15324 292 RdRp C/ T Synonymous 0.12187 28854 243 N C/T S/ L 0.03369
17247 317 NSP13 T/ C Synonymous 0.13213 O (20B) 28881 2046 N G/A R/ K 0.48311
G 17747 928 NSP13 C/ T P/ L 0.28916 P (20B) 28882 2041 N G/A synonymous 0.48170
H 17858 946 NSP13 A/ G Y/ C 0.28985 Q (20B) 28883 2040 N G/C G/ R 0.47915
I 18060 956 NSP14 C/ T Synonymous 0.29368 29540 133 Unknown G/T NA 0.06910
18736 128 NSP14 T/ C F/ L 0.06254 2553 211 Unknown G/A NA 0.09607
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Globally, with a threshold above 0.3%, we observed a total of 119 SNPs across the genome with 74 non‐synonymous mutations, 43 synonymous mutations and two mutations in intergenic region (Table 1 and Table S1). A new major clade can be proposed if it reaches 20% frequency globally. Five major clades (19A, 19B, 20A, 20B and 20C) are classified based on nomenclature data provided by Nextstrain (Figure S1). As shown in Table 1 and File S1, top SNPs with most counts include A23403G in S gene (Clade 19A, Count: 7,590, entropy: 0.63444), C14408T in RdRp (Clade 20A, Count: 7,564, entropy: 0.63513), C3037T in NSP3 (Clade 19A, Count: 7,552, entropy: 0.63571), G25563T in ORF3a (Clade 20C, Count: 3,276, entropy: 0.61047), C1059T in NSP2 (Clade 20C, Count: 2,679, entropy: 0.55524), G28881A (Clade 20B, Count: 2046, entropy: 0.48311), G28883C (Clade 20B, Count: 2040, entropy: 0.47915) and G28882A in N gene (Clade 20B, Count 2041, entropy: 0.4817). Clade 19B contains C8782T (Count: 1,480, entropy: 0.39487). Higher entropy value represents the mutational change in more sequences (Saha et al., 2020), and the pattern of entropy was found to be consistent with that of the SNP count (Figure S3, File S2). Another important SNP, C241T, was not included in this analysis. Different clades based on marker variants can also be defined according to GISAID. Clade 20A contains G clade (C241T, C3037T and A23403G), clade 20B contains GR clade (C241T, C3037T, A23403G and G28882A), clade 20C contains GH clade (C241T, C3037T, A23403G and G25563T), clade 19B contains S clade (C8782T and T28144C), and clade 19A contains V clade (G11083T and G26144T) (Hadfield et al., 2018; Rambaut et al., 2020). All clade classification criteria can be informed by statistical distribution of genome distances in phylogenetic clusters (Han et al., 2019). Mutations with high frequency found here contribute to the clade classification.

Among all 119 SNPs across the genome, there are 60 positions with nucleotide substitutions from C to T, accounting for half of SNPs (Figure 1). It has been reported that transition mutations are much more common than transversion mutations in viruses (Caudill et al., 2019). With most positions possessing C to T mutation, CpG sites decreased. The zinc‐finger anti‐viral protein binds specifically to CpG for degradation of viral RNA genomes. Researchers found that SARS‐CoV‐2 has the most extreme CpG deficiency in all known betacoronavirus genomes, indicating viral rapid evolution in the host (di Gioacchino et al., 2020; Xia, 2020). High‐frequent C to T mutation found in this study further demonstrates CpG deficiency and SARS‐CoV‐2 has adapted to new host with high zinc‐finger anti‐viral protein expression and evolved new ways for immune evasion. More than a third of SNPs across the genome are synonymous mutations (43), and among all non‐synonymous mutation sites, 9 were mutated from T to I, 6 from A to V and 6 also from S to L (Data not shown). Although synonymous mutation does not result in change in amino acid sequence, accumulation of these mutations has the capability to erase the characteristic compactness imprint of the single‐stranded viral RNA genomes (Tubiana et al., 2015). We also summarized SNPs in each gene of the viral genome. As shown in Figure 2, N gene has 15 nucleotide positions mutated, then nsp2 (13), nsp3 (13), S gene (10), nsp14 (8), nsp12(7), ORF3a (7), nsp13 (6) and nsp5 (5).

FIGURE 1.

FIGURE 1

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Global mutation types across the genome. A total of 119 nucleotide substitutions were analysed by its mutation type. Y‐axis denotes the type of substitution while the x‐axis represents the count of each mutation type. C to T (U) mutation represents the majority of nucleotide substitution type

FIGURE 2.

FIGURE 2

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Count of nucleotide positions with mutation in each gene. Total global mutations were grouped for each coding gene including sixteen non‐structural protein genes and ten structural protein genes. The x‐axis shows the name of each gene, and y‐axis indicates the number of nucleotide positions that have substitutions

To illustrate SNPs landscapes in each country/region, we further did analysis on countries/regions with the number of sequences above 40. Among 11,183 sequences around the globe, 2 North American countries include USA (3,599) and Canada (120); 16 European countries including UK (3,077), Iceland (405), Netherland (401), Denmark (350), Belgium (334), France (274), Austria (224), Spain (181), Russia (139), Germany (109), Sweden (104), Luxembourg (96), Portugal (95), Greece (64), Switzerland (55) and Italy (44); 7 Asia countries/regions including China (294), India (141), Saudi Arabia (127), Singapore (124), Japan (105), Taiwan (80) and Thailand (53); 1 South American country (Brazil, 40); and 1 Oceania country (Australia, 493). The remaining 55 sequences represent the rest of the world. Figure 3a (File S1) demonstrates a landscape comparison between globe and Asia countries/regions. With an exception of China, all other Asia countries/regions displayed a relatively higher mutation frequency across the viral genome, representing potential viral adaptation to hosts. Compared to globe and all other Asia countries/regions, variants from China exhibit much lower SNPs frequencies in terms of B (C3037T), E (C14408T), J (A23403G) and K (G25563T). Instead, SNPs frequencies in China regarding positions in C (C8782T) and M (T28144C) are obviously much higher, which is different from the rest of world that have SNP pattern featuring A23403G (aa: D614G) mutation. It reveals that D614G, which barely exist in China strains, gained more replicative advantages when the virus spread outside of China to the world. Reports from WHO have shown that the new COVID‐19 outbreak in Beijing, China exhibits sequence identities more closely to European strains with D614G mutation. For the three major dominant SNPs (Chen et al., 2020; Hillen et al., 2020; Lan et al., 2020; Mercurio et al., 2020; Walls et al., 2020), B (C3037T) and J (A23403G) contribute to 19A clade, and E (C14408T) contributes to 20A clade (Table 1). SNPs G (C17747T), H (A17858G) and I (C18060T) were found predominantly in variants from USA, Canada and Australia (Figure 3b). Interestingly, sequences from Brazil and all European countries displayed an apparently low SNPs frequencies except the three major markers, B (C3037T), J (A23403G) and E (C14408T) (Figure 3b,c, File S1). In other words, SARS‐CoV‐2 is relatively more stable in these countries. Thus, mutational patterns of SARS‐CoV‐2 in different regions differ from each other. In order to check the number of SNPs across the genome for different countries, we analysed those countries with more than 333 sequences. We chose threshold of 333 or 0.3% because countries below this threshold theoretically have only one count if SNP was observed. To reduce the inaccuracy, at least two counts should be recorded for a deemed mutation. As is shown in Figure 4, there are 119 SNPs across the genome globally, and Australia sequences contain the most SNPs of 201, while Denmark sequences only have 78 SNPs. Other countries have SNPs of 116 for USA, 132 for UK, 122 for Iceland, 115 for Netherland and 114 for Belgium. In addition, case‐fatality rate of selected countries/regions on 13 May has varied a lot from below 1% in Russia, Saudi Arabia, Iceland, Singapore to 19.25% in France, 16.29% in Belgium, 14.44% in UK, etc. (Figure S2). We are trying to find a genetic determinant causing different case‐fatality rates among different countries, but we did not find one. According to CDC report, clinical outcomes of COVID‐19 patients relate to a variety of factors, such as age, gender, poverty, medical conditions and even blood types (Ellinghaus et al., 2020; Li et al., 2020).

FIGURE 3.

FIGURE 3

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Landscape of mutations across the genome for (a) Asian countries, (b) North America, South America, and Oceania countries, and (c) European countries. Sequences up to 13 May were aligned and analysed by UGENE software. Referred to Wuhan‐Hu‐1 parental strain, each SNP across the genome was recorded. Mutational profiling of whole genome was analysed for both global strains and strains of a specific country/region. Country/region name was indicated with a total number of viral genomes in brackets. A schematic diagram is shown on the top of each figure. Alphabetical letters from A to P indicate corresponding mutations described in Table 1. The y‐axis represents counts of strains on each mutation; x‐axis denotes the whole‐genome landscape of SARS‐CoV‐2

FIGURE 4.

FIGURE 4

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Count of the number of nucleotide positions across the genome for countries with more than 300 sequences. The total SNPs across the whole genome were analysed for each country. Y‐axis shows countries with more than 300 sequences including Belgium, Denmark, Netherland, Iceland, Australia, UK, USA and the whole world as comparison; x‐axis shows the number of nucleotide substitutions across the genome

3.2. Analysis of mutations affecting protein synthesis

Genetic variation/SNPs contribute to alterations of protein translation. We observed multiple deletions and insertions across the genome in different countries/regions (Table 2). Three nucleotide deletion in 1605–1607nt region result in amino acid N deletion in position 267 of nsp2. Twenty‐nine counts of ninenucleotides deletion in 686–694nt lead to three amino acids deletions in nsp1 region. Another 9nt deletion (515–520nt) also occurs in nsp1 region, resulting in two amino acids (72V, 73M) missing. Deletion was also found in S gene with thre nucleotides deletion in 21991–21993nt. Accordingly, the single amino acid (Y) was missed in position 144 of S protein. In addition, insertion was found in nsp6. Three consecutive T insertion result in an extra amino acid (F) synthesized. All these deletions/insertions show a globally distributed pattern.

TABLE 2.

Deletions and insertions found across the whole genome

Type Nucleotide position in whole genome Amino acid Gene Average Entropy Total counts Geographic distribution
Deletion 1605–1607 267 N NSP2 0.12121 282 UK (153), Netherland (80), Australia (9), Belgium (10), Denmark (4), Iceland (7), USA (4), Portugal (3), France (2), Spain (2), Canada (1), Finland (1), New Zealand (1), Russia (1), Sweden (1), Taiwan (1), Latvia (1)
Deletion 686–694 129 KSF 131 NSP1 0.01895 29 USA (16), UK (8), Swedan (1), Iceland (1), Saudi Arabia (1), France (1), Canada (1)
Deletion 515–520 72 VM 73 NSP1 0.01402 22 USA (13), Australia (3), UK (2), Denmark (1), France (1), Greece (1), Netherland (1)
Deletion 21991–21993 144 Y spike 0.00779 11 USA (3), Slovenia (2), Saudi Arabia (2), Netherland (2), India (1), Belgium (1)
Insertion TTT inserted between 11,074 and 11075nt

35 F

inserted

 nsp6 0.00654 10 Australia (5), England (4), Switzerland (1)
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Non‐synonymous mutations sometimes result in immediate stop of translation and thus protein truncation. As is shown in Table 3, SNP A12050T in two Denmark strains leads to amino acid change from K to stop codon and a 14aa truncation of nsp7. Forty‐nine Belgium strains and 2 Denmark strains have T13402G mutation resulting in 14aa truncation of nsp10. Another SNP T13408A in nsp10 truncated 12aa. A much shorter length of nsp13 (217aa versus 601aa) was generated due to a A16888T mutation in three Denmark strains. A19513T in two Denmark strains results in 36aa truncated in nsp14 C terminal. For structural proteins, two Iceland strains have SNP C27661T resulting in 32aa shorter compared to the original one. Finally, three strains from China have G28041T mutation in ORF8 and also end up with a 72aa deletion in its C terminal. Instead of a change in stop codon, two Germany strains have start codon changed with G25395T and four amino acids are missed in ORF3a. In addition, SNPs in transcriptional regulatory sequence (TRS) may lead to impairment of 3’ end structural protein synthesis. Change of protein length could potentially damage its key function in viral replication/assembly/immune system antagonism. However, these may represent quasispecies of SARS‐CoV‐2 and with those critical mutations, the virus may not get replication advantages. Therefore, further studies are needed for exploring the role of those mutations in the virus replication.

TABLE 3.

Key mutations relating to protein expression change

Country Position Count Gene/region Entropy Nucleotide change Amino acid change Length Wuhan‐hu−1 Length after mutation
Denmark 12050 2 NSP7 0.00320 A/T K/Stop codon 249nt/83aa 210nt/69aa
Belgium 13402 49 NSP10 0.03333 T/G Y/Stop codon 417nt/139aa 378nt/125aa
Denmark 13402 2 NSP10 0.03333 T/G Y/Stop codon 417nt/139aa 378nt/125aa
Belgium 13408 2 NSP10 0.01049 T/A C/Stop codon 417nt/139aa 384nt/127aa
Denmark 16888 3 NSP13 0.00247 A/T K/Stop codon 1803nt/601aa 654nt/217aa
Denmark 19513 2 NSP14 0.00092 A/T R/stop codon 1581nt/527aa 1476nt/491aa
Germany 25395 2 ORF3a 0.00172 G/T Start codon changed 828nt/275aa 816nt/271aa
Iceland 27661 2 ORF7a 0.00172 C/T Q/stop codon 366nt/121aa 270nt/89aa
Austria 27393 2 TRS 0.00172 C/T NA acgaac acgaat
France 27893 2 TRS 0.00172 C/T NA acgaac acgaat
China 28041 3 ORF8 0.00247 G/T G/ Stop codon 366nt/ 121aa 150nt/49aa
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3.3. Mutations on key viral proteins

S: SARS‐CoV‐2 S protein is a major target of neutralizing antibodies and contributes to ACE2 binding and entry into host cells. SNPs on S gene potentially impact protein antigenicity and cellular tropism. In this study, there are total 75 non‐synonymous mutations found on Spike protein (Table 4), spanning from signal peptide (SP) to cytoplasmic domain (CP). C21575T (L5F) mutation with 70 counts of multiple countries lies in signal peptide region. This SNP was also recorded in Table S1 using a threshold above 0.3% globally. Signal peptides function to translocate spike protein to the membrane. It remains to be determined whether L5F mutation affects S protein translocation or not. A series of mutations with few counts in multiple countries was found in N terminal domain (NTD) of S protein. There are five SNPs found in receptor‐binding domain (RBD), among which V483A with 21 counts in USA only, N439K with 31 counts in UK only locate in receptor‐binding motif (RBM) and the rest of 3 SNPs (A344S with two counts in Saudi Arabia, N354D with two counts in China, V367F with eight counts in France and Netherland) locate in RBD. The well‐known D614G mutation lies in C terminal domain (CTD) of S1 and is close to S2. It has 7,544 counts with a geographic distribution of 27 countries. An increasing trend of D614G was observed globally, and it was reported that strains with this mutation lead to reduced S1 shedding and increased viral infectivity (Zhang et al., 2020). G614 became the global dominant variant and provided a boost of transmission ability of the virus since outbreaks out of China. However, its impact on therapeutic and vaccine design is limited (Korber et al., 2020). Instead of presence in the receptor‐binding domain (RBD), D614G is located in the interface between the spike protomers and was proposed to cause loss of hydrogen bonds between protomers, thus altering virus infectivity. Antibodies from D614 variant infected patients could cross‐neutralize G614 variant, indicating changes in this position have no impacts on antibody‐mediated B cell immunity (Grubaugh et al., 2020; Hu et al., 2020; Ozono et al., 2020). Beyond D614G, there are 8 SNPs with few counts in multiple countries located in CTD, followed by 5 SNPs before fusion peptide (FP) in S2 subunit. Taiwan region has six counts of sequences with T791I mutation in FP region. Twenty‐three counts of A829T mutation were found only in Thailand. Also, A831V was found only in Iceland samples with 24 counts. D839Y was found in three countries with 11 counts of sequences. Heptad repeat 1 (HR1) and heptad repeat 2 (HR2) interact with each other to form six‐helical bundle and facilitate cellular and viral membrane fusion. Six SNPs (D936V, D936Y, S940F, T941A, S943R and S943T) in HR1 and 2 in HR2 (D1163G and V1176F) were found. Interestingly, D936Y was found in 4 countries with total 73 counts of sequences, and S943R (22 counts) and S943T (23 counts) were found only in Belgium samples. Because of the special function in membrane fusion, researchers have been developing potent fusion inhibitors targeting HR1/HR2 of SARS‐CoV and MERS‐CoV (Xia et al., 2020). Mutations found in these two regions may potentially affect efficacy of fusion inhibitors. Followed by HR2, four and three non‐synonymous SNPs were found in transmembrane domain (TM) and cytoplasmic domain (CP), respectively. Notably, P1263L mutation in CP region has 56 counts of sequences from multiple countries. Critical mutations on RBD and mutations with top counts were also denoted through structural analysis (Figure 5a). No mutations were found on the N‐linked glycosylation sites, key amino acids for ACE2 binding and SPRRAR↓SV cleavage sites in S protein. Highly genetic variation and diversity observed in S protein poses potential challenge to anti‐viral vaccine and therapeutics development. Further studies are needed to determine the functional impacts of key S mutations found in this study.

TABLE 4.

Summarized mutations within spike gene

Nucleotide Amino acid Count Entropy Geographic distribution Region Nucleotide Amino acid Count Entropy Geographic distribution Region
Position Change Position Change Position Change Position Change
21575 C/ T 5 L/ F 70 0.04689 6 countries SP 23587 G/T 675 Q/ H 2 0.00952 Iceland CTD
21614 C/ T 18 L/ F 16 0.01346 UK NTD 23673 C/T 704 S/ L 2 0.00320 Australia S2
21648 C/ T 29 T/ I 4 0.00962 Australia, Netherland NTD 23679 C/T 706 A/ V 5 0.00590 Belgium S2
21707 C/ T 49 H/ Y 19 0.01780 China NTD 23732 A/T 724 T/ S 3 0.00000 Denmark S2
21711 C/ T 50 S/ L 4 0.00458 Australia NTD 23856 G/A 765 R/ H 4 0.00939 Iceland S2
21724 G/ T 54 L/ F 4 0.00872 France, India NTD 23856 G/T 765 R/ L 3 0.00939 Taiwan S2
21743 A/ T 61 N/ Y 4 0.00000 Denmark NTD 23934 C/T 791 T/ I 6 0.00590 Taiwan FP
21846 C/T 95 T/I 2 0.00617 Austria NTD 24047 G/A 829 A/ T 23 0.01478 Thailand S2
21855 C/T 98 S/F 2 0.00524 Iceland NTD 24054 C/T 831 A/ V 24 0.01696 Iceland S2
21920 G/A 120 V/I 4 0.00412 France NTD 24077 G/T 839 D/ Y 11 0.01288 3 countries S2
21974 G/C 138 D/H 3 0.00797 Australia NTD 24095 G/T 845 A/ S 3 0.00617 Portugal S2
22020 T/C 153 M/T 2 0.00247 China NTD 24099 C/T 846 A/ V 6 0.00779 Belgium S2
22032 T/C 157 F/S 2 0.00172 Canada NTD 24102 G/C 847 R/ T 2 0.00265 Austria S2
22103 G/C 181 G/A 3 0.00247 Denmark NTD 24117 C/T 852 A/ V 3 0.00247 Netherland S2
22151 A/G 197 I/V 4 0.00390 Greece, Spain NTD 24197 G/T 879 A/ S 6 0.01459 Austria S2
22205 G/C 215 D/H 2 0.00567 Saudi Arabia NTD 24369 A/T 936 D/ V 4 0.00000 Denmark HR1
22224 C/T 221 S/L 4 0.00412 Australia NTD 24368 G/T 936 D/ Y 73 0.04120 4 countries HR1
22277 C/A 239 Q/K 5 0.00590 Netherland NTD 24381 C/T 940 S/ F 2 0.00247 France HR1
22289 G/T 243 A/S 2 0.00412 India NTD 24383 A/G 941 T/ A 2 0.00172 Belgium HR1
22303 T/G 247 S/R 2 0.00172 China NTD 24389 A/C 943 S/ R 22 0.03317 Belgium HR1
22323 C/T 254 S/F 2 0.00630 Belgium NTD 24390 G/C 943 S/ T 23 0.03528 Belgium HR1
22344 G/T 261 G/V 3 0.00482 Netherland NTD 24621 C/T 1020 A/ V 4 0.00524 Austria S2
22346 G/A 262 A/T 4 0.00412 Australia NTD 24642 C/T 1027 T/ I 8 0.00654 Austria S2
22374 A/G 271 Q/R 2 0.00344 India NTD 24680 G/T 1040 V/ F 3 0.00247 China S2
22404 A/T 281 E/V 2 0.00587 Taiwan NTD 24794 G/T 1078 A/ S 6 0.00809 Belgium, Luxembourg S2
22592 G/T 344 A/S 2 0.00172 Saudi Arabia RBD 24812 G/T 1084 D/ Y 3 0.00247 China S2
22622 A/G 354 N/D 2 0.00265 China RBD 24863 C/G 1101 H/ D 3 0.00524 Denmark S2
22661 G/T 367 V/F 8 0.00902 France, Netherland RBD 24933 G/T 1124 G/ V 15 0.01638 Australia, India S2
22879 C/A 439 N/K 31 0.00524 UK RBD (RBM) 25050 A/G 1163 D/ G 2 0.00172 Australia HR2
23010 T/C 483 V/A 21 0.01366 USA RBD (RBM) 25088 G/T 1176 V/ F 4 0.00458 China, Denmark HR2
23271 C/T 570 A/V 3 0.00504 China CTD 25218 G/T 1219 G/ V 3 0.00524 France TM
23277 C/T 572 T/I 3 0.00524 India CTD 25249 G/T 1229 M/ I 4 0.00320 Belgium, Iceland TM
23311 G/T 583 E/D 3 0.00590 India CTD 25269 G/T 1236 C/ F 2 0.00247 Austria TM
23393 C/T 611 L/F 4 0.00320 Belgium CTD 25273 G/T 1237 M/ I 2 0.00492 Portugal TM
23401 G/T 613 Q/M 3 0.00320 Japan CTD 25290 G/T 1243 C/ F 2 0.00247 India CP
23403 A/G 614 D/G 7,544 0.63444 27 countries CTD 25340 G/A 1260 D/ N 3 0.00320 Australia CP
23576 G/T 672 A/S 2 0.00000 Denmark CTD 25350 C/T 1263 P/ L 56 0.03799 4 countries CP
23588 A/C 676 T/P 2 0.00092 Denmark CTD
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FIGURE 5.

FIGURE 5

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Non‐synonymous mutations on (a) spike, (b) RdRp, (c) 3CLpro and (d) PLpro. Protein structures for RdRp, S and 3CLpro were obtained from the Protein Data Bank (PDB) accession 6M71, 6vyb and 6M2Q, respectively. Homology modelling of SARS‐CoV‐2 PLpro structure was carried out by using I‐TASSER (Yang et al., 2015) based on SARS‐CoV PLpro structure. PyMOL was used for visualization of protein structure. Sphere with different colours including red, green, blue, yellow, magentas, cyans, oranges, tints and greys indicates corresponding non‐sysnonymous mutations on each protein. Amino acid mutations were also coloured in blue after the position number

RdRp: The core component of replication‐transcription complex is the catalytic subunit, RdRp (nsp12). In this study, multiple non‐synonymous SNPs were found in all regions of RdRp, such as beta‐hairpin (2 SNPs), nidovirus RdRp‐associated nucleotidyltransferase domain (NiRAN) (4 SNPs), interface domain (8 SNPs), fingers (10 SNPs), palm (7 SNPs) and thumb (4 SNPs) (Table 5). Notably, SNP C14408T (P323L) with 7,517 counts locates in interface domain and was distributed in 27 countries globally. Interface domain is still poorly studied and presumably interacts with other proteins regulating catalytic activity of RdRp. In most cases, spike D614G was accompanied by RdRp P323L. Structural analysis shows that P323L mutation results in considerable changes in secondary structure at this site and the substitution from proline to leucine could cause damage of structural integrity conferred by proline (Figure 5). Similarly, substitution of valine with a larger side chain at position 97 changes secondary structure of RdRp. It has been reported that A97V and P323L result in alteration of protein stability and intramolecular interactions, thus affecting RdRp functions (Chand et al., 2020). Studies have put more efforts on spike D614G impacts, whereas RdRp P323L may also play a role in viral genome replication and transcription. Other more frequent mutations include A97L with 124 counts in 7 countries, T141I in NiRAN domain with 63 sequence counts in three countries, A449V in fingers with 58 counts in 6 countries around the world. Some mutations only exist in specific countries, such as A43V in beta‐hairpin domain with 17 counts in Sweden only, E436G (fingers, 20 counts) and M601I (Palm, 18 counts) and G774S (Palm, 16 counts) in USA only, G228C (NiRAN, 11 counts) in Saudi Arabia only, S434F (Fingers, 11 counts) and M666I (Fingers, 19 counts) in UK only. Mutations with top counts were also shown on RdRp structure (Figure 5b). RdRp has been proposed to be the target of many anti‐viral drugs with nucleotide analogs. So many SNPs in RdRp, especially the high‐frequency mutation P323L could potentially reduce effectiveness of anti‐viral treatments. Due to the participation of RdRp in viral genome transcription, mutations such as P323L may potentially affect viral replicative ability and transmission. In addition, more knowledge is urgently needed to understand the impacts of RdRp P323L and A97L on polymerase activity and thus viral replication.

TABLE 5.

Summarized non‐synonymous mutations within RdRp gene

Nucleotide Amino acid Count Entropy Geographic distribution Region Nucleotide Amino acid Count Entropy Geographic distribution Region
Position change Position Change position CHANGE Position Change
13517 C/T 26 T/I 6 0.01288 France, Luxembourg 14653 G/T 405 V/F 2 0.00495 Austria Fingers
13537 A/T 33 R/W 3 0.00000 Denmark Beta‐hairpin 14741 C/T 434 S/F 11 0.00779 UK Fingers
13568 C/T 43 A/V 17 0.01422 Sweden Beta‐hairpin 14747 A/G 436 E/G 20 0.01310 USA Fingers
13617 G/T 59 K/N 2 0.00172 Spain 14786 C/T 449 A/V 58 0.03246 6 countries Fingers
13627 G/T 63 D/Y 21 0.01366 Australia, UK 14912 A/G 491 N/S 12 0.00841 USA Fingers
13730 C/T 97 A/L 124 0.07000 7 countries 14980 C/T 514 L/F 2 0.00247 Iceland Fingers
13862 C/T 141 T/I 63 0.03664 3 countries NiRAN 15243 G/T 601 M/I 18 0.01366 USA Palm
14109 A/G 223 I/M 2 0.00172 Saudi Arabia NiRAN 15277 C/T 613 H/Y 12 0.01196 Belgium Palm
14122 G/T 228 G/C 11 0.00902 Saudi Arabia NiRAN 15327 G/T 629 M/I 2 0.00550 Spain Fingers
14183 C/T 248 T/I 4 0.00550 Australia NiRAN 15380 G/T 647 S/I 10 0.01873 Austria, Germany Fingers
14195 C/A 252 T/N 3 0.00320 Sweden Interface 15438 G/T 666 M/I 19 0.01253 UK Fingers
14198 C/T 253 A/V 2 0.00247 China Interface 15535 G/T 699 A/S 2 0.00172 Netherland Palm
14267 C/T 276 T/M 2 0.00247 Greece Interface 15647 A/G 736 D/G 4 0.00320 China Palm
14270 A/C 277 E/A 2 0.00172 Belgium Interface 15760 G/A 774 G/S 16 0.01196 USA Palm
14274 G/C 278 E/D 2 0.00437 India Interface 15850 G/T 804 D/Y 2 0.00172 Iceland Palm
14408 C/T 323 P/L 7,517 0.63513 27 countries Interface 15860 A/G 807 K/R 9 0.00654 France Palm
14425 C/A 329 L/I 3 0.00247 India Interface 15919 G/T 827 V/L 2 0.00172 Greece Thumb
14511 G/T 357 Q/H 2 0.00172 Russia Interface 15982 G/T 848 V/L 2 0.00247 Australia Thumb
14585 C/T 382 A/V 5 0.00458 Taiwan 16054 C/T 872 H/Y 7 0.00524 Iceland Thumb
14,593 G/A 385 G/S 2 0.00265 Russia 16078 G/A 880 V/I 4 0.00320 India Thumb
14,636 C/T 399 A/V 2 0.00458 Singapore Fingers
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3CLpro : 3CLpro serve as a potential target by anti‐viral inhibitors due to its crucial cleavage activity and functions in viral replication. As shown in Table 6 and Figure 5c, most frequent mutations found in 3CLpro are G15S (138 counts, globe), T48I (17 counts, USA only), L75F (15 counts, USA only), L89F (32 counts, USA only), K90R (76 counts, China and Iceland), P108S (12 counts, Iceland and UK), L220F (22 counts, USA only), K236R (13 counts, USA only), D248E (43 counts, UK only), A266V (35 counts, Australia and USA) and N274D (13 counts, UK only). Key residues of 3CLpro responsible for SARS‐CoV catalytic activity, substrate binding and dimerization were checked, and none get changed in SARS‐CoV‐2. Anti‐viral drugs targeting 3CLpro typically dock within the Cys‐His catalytic dyad (Cys145 and His41) which contains active catalytic binding site (Chitranshi et al., 2020). Mutations were not found in these two sites, suggesting that pharmacological inhibitors of 3CLpro may still serve as therapeutics for SARS‐CoV‐2. However, with multiple high‐frequent mutations found in 3CLpro especially G15S, K90R and D248E, more studies about their impacts on cleavage activity and 3CLpro drug efficacies are needed.

TABLE 6.

Summarized non‐synonymous mutations within 3CLpro gene

Nucleotide Amino acid Count Entropy Geographic distribution
Position Change Position Change
10097 G/A 15 G/S 138 0.06897 Austria, Denmark, Iceland, Netherland, Russia, UK
10188 C/T 45 T/I 17 0.01138 USA
10208 C/T 52 P/S 2 0.00172 Russia
10265 G/A 71 G/S 2 0.00962 Denmark
10277 C/T 75 L/F 15 0.01080 USA
10319 C/T 89 L/F 32 0.02106 USA
10323 A/G 90 K/R 76 0.04422 China, Iceland
10376 C/T 108 P/S 12 0.00779 Iceland, UK
10377 C/T 108 P/L 2 0.00482 France
10449 C/T 132 P/L 2 0.00340 Russia
10478 A/C 142 N/H 2 0.00172 India
10479 A/T 142 N/I 2 0.00265 India
10508 A/G 152 I/V 2 0.00172 China
10604 C/T 184 P/S 4 0.00458 China
10631 G/A 193 A/T 3 0.00247 Australia
10641 C/T 196 T/M 2 0.00172 Iceland
10712 C/T 220 L/F 22 0.01422 USA
10761 A/G 236 K/R 13 0.00902 USA
10798 C/A 248 D/E 43 0.02522 UK
10851 C/T 266 A/V 35 0.02169 Australia, USA
10874 A/G 274 N/D 13 0.01113 UK
10889 C/T 279 R/C 3 0.00390 Australia
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PLpro : Same as 3CLpro, proteolytic processing of polyprotein is also mediated by PLpro. In this study, a total of 10 non‐synonymous SNPs were found in PLpro region (Table 7, Figure 5d). All of them are specific to a country. Seven sequence counts with L36F mutation were only distributed in China. I44V with 4 counts were only found in Canada. T63I with 40 sequence counts was found in Iceland only. In addition, T277I mutation was only distributed in USA with 15 sequences found. Spacious pockets for binding sites include residues Asp164, Val165, Arg166, Glu167, Met 208, Ala246, Pro247, Pro248, Tyr 264, Gly266, Asn267, Tyr 268, Gln269, Cys217, Gly271, Tyr273, Thr301 and Asp302 (Arya et al., 2020), among which only Proline in positive 247 was substituted to Leucine in two strains from Belgium. Essential properties like deISGylation and deubiquitination of PLpro affect viral replication. Coronavirus PLpro also serves as host innate immune antagonism. All these functions make PLpro to be a potential target for anti‐viral therapeutics. However, high‐frequent mutations in PLpro such as T63I may have negative effects on anti‐viral drug efficacies.

TABLE 7.

Summarized non‐synonymous mutations within PLP region

Nucleotide Amino acid Count Entropy Geographic distribution
Position Change Position Change
5062 G/T 36 L/F 7 0.01366 China
5084 A/G 44 I/V 4 0.00524 Canada
5142 C/T 63 T/I 40 0.02372 Iceland
5223 C/T 90 T/I 2 0.00172 Australia
5322 T/A 123 I/K 2 0.00172 Belgium
5457 C/T 168 T/I 2 0.00172 Luxembourg
5694 C/T 247 P/L 2 0.00265 Belgium
5730 C/T 259 T/I 2 0.00962 Iceland
5784 C/T 277 T/I 15 0.01138 USA
5845 A/T 297 K/N 2 0.00247 Japan
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4. DISCUSSION

By analysis of 11,183 whole genomes of SARS‐CoV‐2, we demonstrated a high genetic variability between different regions and detailed mutational profiling across the genome and for key viral proteins (S, RdRp, 3CLpro and PLpro). In the present study, 60 out of 119 SNPs are nucleotide substitutions from C to T, representing the most abundant transition. Consistent with previous studies, this observation increases the frequency of codons for hydrophobic amino acids and provides evidence of potential anti‐viral editing mechanisms driven by host (Matyasek & Kovarik, 2020; Mercatelli & Giorgi, 2020; Simmonds, 2020). On the other hand, more C to T transitions indicates less CpG abundancy, which is resulted from cytosine methylation and deamination into T. This mutational pattern was also observed in Bat RaTG13 and other coronaviruses, indicating rapid adaptation and evolution of the virus in the host (Matyasek & Kovarik, 2020; Simmonds, 2020). Among all known betacoronaviruses, SARS‐CoV‐2 represents the most extreme CpG deficiency, which contributes to evasion of host anti‐viral defence mechanisms (Xia, 2020).

SARS‐CoV‐2 mutational pattern in each region varies from each other with North American and European countries more stability and Asian countries more variability (Figure 3). In addition, we did not observe a consistent mutational pattern contributing to the degree of case mortality/morbidity rate although some countries such as France, Belgium and UK do have a much higher fatality rate while countries such as Singapore and Iceland have a much lower fatality rate (Figure S2). Multiple factors were reported to impact the course of COVID‐19 pandemic. Stringent measures such as quarantine, social distancing and isolation of infected patients have been implemented in China and result in successful containment of the epidemic (Anderson et al., 2020). Different social and economic factors among different countries also influence spread and outcomes of the disease (Qiu et al., 2020). In addition, according to WHO, the mortality is higher in people older than 65 years and those with underlying comorbidities, such as serious heart conditions, chronic lung disease, high blood pressure, obesity and diabetes (Lai et al., 2020; Ruan, 2020; Weiss & Murdoch, 2020).

SARS‐CoV‐2 strains from China demonstrate a high nucleotide substitution rate for C (C8782T) and M (T28144C) while the global strains feature substitutions on B (C3037T), E (C14408T) and J (A23403G), indicating rapid viral adaptation and evolution in other countries. The rapid spread to the world was reported to be a result from A23403G (D614G) mutation, which is responsible for increased viral infectivity, decreased neutralization sensitivity to individual convalescent serum and enhanced disease transmission thereafter (Daniloski et al., 2020; Hu et al., 2020; Korber et al., 2020; Ogawa et al., 2020; Yurkovetskiy et al., 2020; Zhang et al., 2020). Virus strains with D614G mutations represents the dominant strains globally (). Also, the recent outbreaks in China during June were due to transmission of viral strains with D614G from Europe (Hu et al., 2020). However, whether or not other critical mutations with highest counts affects viral replicative ability needs to be defined. Landscape of genome‐wide mutations globally and in different countries demonstrates high genetic diversity of SARS‐CoV‐2. Recombination events were reported in some studies (Gallaher, 2020; Korber et al., 2020; Paraskevis et al., 2020; Sashittal et al., 2020).

We also observed that N gene has 15 nucleotide positions mutated, then nsp2 and nsp13 (13), S gene (10), nsp14 (8), nsp7 and ORF3a (7), nsp13 (6) and nsp5 (5). This pattern is consistent with previous results claiming that ORF1a, ORF1b, S and N gene were detected at high frequency (Kim et al., 2020). N represents the most abundant protein expressed by viral genome and is able to induce high level of antibody response which ease serological diagnosis (Azkur et al., 2020; To et al., 2020). Non‐synonymous mutations on N gene (C28311T, C28854T, G28881A and G28883C), especially G28881A and G28883C with vast majority of counts that contribute to clade classification, may have impacts on antigenicity of N protein. Further studies are needed to determine the impacts. We also observed here that nsp2 and nsp3 possess high mutation frequency (Figure 2). SARS coronavirus nsp1 and nsp2 are the most variable protein (Graham et al., 2005). However, previous research found that nsp2 are dispensable for SARS viral replication, but attenuates viral growth and genome synthesis (Graham et al., 2005). Nsp3 possesses PLpro domain with protease‐cleavage activities and serves as a target for anti‐viral development (Rut et al., 2020). With high variability and high‐frequency mutations including G2891A, C3037T, C3177T and C6312A, cautions and considerations should be taken for anti‐viral therapeutic development. Multiple single nucleotide mutations lead to protein codon change to start/stop codons, which results in protein length change (Table 3). Mutations on TRS sites also may affect viral RNA transcription, thus affecting protein expression. Amino acids deletions and insertions were also observed (Table 2), and protein functions may get changed.

A detailed mutational profiling was performed for multiple key viral proteins including S, RdRp, 3CLpro and PLpro (Tables 4, 5, 6, 7 and Figure 5). S protein mediates virus binding and entry to host cells, and is able to elicit high level of neutralizing antibody response (BalcioGlu et al., 2020; P. Liu, Cai, et al., 2020; Schmidt et al., 2020). Utilizing monoclonal antibodies (mAbs) to target RBD region as therapeutics have gained promising results and are currently under clinical trials for COVID‐19 patients (Alsoussi et al., 2020; Chi et al., 2020; Shi et al., 2020). RdRp, 3CLpro and PLpro are conserved among all strains and play critical roles in viral genome replication and polyprotein cleavage to form functional viral proteins (Aftab et al., 2020; Chand et al., 2020; Chitranshi et al., 2020; Gao et al., 2020; Rut et al., 2020; Ul Qamar et al., 2020; Yin et al., 2020). Due to their critical feature of polymerase and protease, structures for RdRp, 3CLpro have been decoded (Gao et al., 2020; Ul Qamar et al., 2020; Yin et al., 2020). Anti‐viral drugs targeting these proteins are currently under development. Here, we described a detailed mutational profile of these four proteins. Critical mutations potentially impacting protein functions were observed and shown on their structures (Figure 5). Although counts for some of the mutations are not high, it provides insights that SARS‐CoV‐2 may adapt to environmental changes and gain replicative advantages/fitness to escape anti‐viral treatment and being drug‐resistant. Thus, further studies are needed to determine whether mutations on key sites affect viral replication and infectivity or not.

In summary, a detailed mutational profiling was described in this study. Landscape of genome‐wide mutations across the countries provides insights for SARS‐CoV‐2 transmission and adaptation as different regions have different mutational patterns. Mutations with high frequency contribute to clade classification of SARS‐CoV‐2 strains. This study provides more evidence for SARS‐CoV‐2 genomic diversity around the globe and rapid evolution/adaptation of the virus. Given the detailed mutational profiles of key viral proteins including S, RdRp, 3CLpro and PLpro, it also gives some guidance for better design of anti‐viral therapeutic to tackle the disease.

CONFLICT OF INTEREST

The authors declare that there is no competing interests.

ETHICAL APPROVAL

Ethical statement is not applicable since no human/animal sample handling and gathering were involved in this study.

Supporting information

[Correction added on 27 May 2021, after first online publication: A new supplementary table has been added to the online Supporting Information section.]

Supplementary Material

Click here for additional data file. (666.5KB, pdf)

Supplementary Material

Click here for additional data file. (31.4KB, xlsx)

Supplementary Material

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Supplementary Material

Click here for additional data file. (227.9KB, pdf)

ACKNOWLEDGEMENTS

The authors sincerely appreciate the researchers worldwide who sequenced and shared the complete genome data of SARS‐CoV‐2 from GISAID (https://www.gisaid.org/). Please see the Supplemental PDF file for the acknowledgement table regarding the Authors from the Originating laboratories responsible for obtaining the specimens, as well as the Submitting laboratories where the genome data were generated and shared Via GISAID, on which this research is based.

[Correction added on 27 May 2021, after first online publication: An Acknowledgments section has been included in this current version.]

Yuan F, Wang L, Fang Y, Wang L. Global SNP analysis of 11,183 SARS‐CoV‐2 strains reveals high genetic diversity. Transbound Emerg Dis.2021;68:3288–3304. 10.1111/tbed.13931

Contributor Information

Fangfeng Yuan, Email: fy8@illinois.edu.

Leyi Wang, Email: leyiwang@illinois.edu.

DATA AVAILABILITY STATEMENT

The data used to support the findings of the manuscript are included within the article.

REFERENCES

[Correction added on 27 May 2021, after first online publication: The full reference for “Shu & McCauley, 2017” has been included in the References list in this current version.]

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