|Year : 2022 | Volume
| Issue : 1 | Page : 3-10
Mutation analysis of severe acute respiratory syndrome coronavirus-2 genomic sequences in India and its geographical relations
Pradip Rameshbhai Chauhan1, Ashish J Rathva2, Kinjal Jethva3
1 Department of Anatomy, P.D.U. Government Medical College, Rajkot, Gujarat, India
2 Department of Anatomy, GMERS Medical College, Junagadh, Gujarat, India
3 Department of Anatomy, SKBS Medical College and Research Institute, Sumandeep Vidhyapeeth, Baroda, Gujarat, India
|Date of Submission||12-Jun-2020|
|Date of Acceptance||27-Oct-2021|
|Date of Web Publication||17-Mar-2022|
Dr. Pradip Rameshbhai Chauhan
Department of Anatomy, P.D.U. Government Medical College, Civil Hospital Campus, Jamanagar Road, Rajkot - 360 001, Gujarat
Source of Support: None, Conflict of Interest: None
Introduction: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has been spreading all over the world, including India; the virus has been classified in various clades (L, S, V, G, GH, GR, and others) on the base of mutations. India is vulnerable to the health and financial hazards of the SARS-CoV-2 infection. Even after four phases of lockdown, the number of SARS-CoV-2 infections has been increasing in India. Clinical trials for vaccine and ribonucleic acid (RNA)-dependent RNA polymerase inhibitor are going on. The study was conducted to analyze SARS-CoV-2 genomic sequences submitted from India to identify mutations and their geographical distribution. Material and Methods: Three hundred and sixty-three sequences submitted from India were archived (GISAID database), compared with reference sequence (Wuhan, China), and phylogenetic tree was prepared. Sequences with more than 1% nucleotide stretching were excluded for mutation analysis, and multiple sequence analysis for 317 sequences was done. Mutations were analyzed as per phases of lockdown and geographical distribution. Results: Clade “GH” appears in the second and third phases of lockdown; the clade “V” has not been reported after March 17, 2020, in India. Spike protein mutation D614G was found in 166 sequences, out of which 164 sequences show P323 L mutation of nonstructural protein 12 (nsp12). RNA-dependent RNA polymerase coding nsp12 shows 23 types of 364 amino acid mutations. Discussion and Conclusion: SARS-CoV-2 shows increasing mutations with the time and spread of the virus. The mutations in spike protein and nsp12 regions are critical for response to undergoing trials of vaccines and drugs.
Keywords: Genome, mutation, ribonucleic acid-dependent ribonucleic acid polymerase, severe acute respiratory syndrome coronavirus-2, spike protein
|How to cite this article:|
Chauhan PR, Rathva AJ, Jethva K. Mutation analysis of severe acute respiratory syndrome coronavirus-2 genomic sequences in India and its geographical relations. J Anat Soc India 2022;71:3-10
|How to cite this URL:|
Chauhan PR, Rathva AJ, Jethva K. Mutation analysis of severe acute respiratory syndrome coronavirus-2 genomic sequences in India and its geographical relations. J Anat Soc India [serial online] 2022 [cited 2022 Jul 3];71:3-10. Available from: https://www.jasi.org.in/text.asp?2022/71/1/3/339870
| Introduction|| |
The first case of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) disease (COVID-19) was reported on December 31, 2019, in Wuhan, China. The World Health Organization declared the emerging SARS-CoV-2 as a pandemic on March 11, 2020. As of June 2, 2020, reported to the WHO, there have been 6,194,533 confirmed cases of SARS-CoV-2 infection including 376,320 deaths globally and 5,598 deaths in India.
India implemented lockdown in four phases as cautionary measures to combat the spread of the SARS-CoV-2. First phase: March 25, 2020–April 14, 2020; second phase: April 15, 2020–May 3, 2020; and third phase May 4, 2020–May 17, 2020. From May 18, India started the fourth phase of lockdown with many relaxations that ended on May 31. The number of cases has been increasing in India even after four phases of lockdowns. India being a country with the second largest population in the world is vulnerable to the hazards of the SARS-CoV-2 infection.
Genomic structure of severe acute respiratory syndrome coronavirus-2
SARS-CoV-2 is from the SARS-CoV species of subgenus Sarbecovirus, genus Betacoronavirus, family Coronaviridae; the seventh member of the sphere-shaped enveloped nonsegmented positive-sense ribonucleic acid (RNA) β-coronavirus (SARS-CoV-2) is believed to be originated from the infected bat. Genome sequence of the SARS-CoV-2 is found 96.2% identical to the bat CoV RaTG13 collected in Yunnan province, China, and pangolin is believed as an intermediate host.
Coronavirus genome contains a variable number of open reading frame (ORF); the ORF encodes 16 nonstructural proteins (nsps). The remaining part of the viral genome encodes spike surface glycoprotein (S), a small envelope protein (E), matrix protein (M), and nucleocapsid protein (N), and other accessory proteins.
SARS-CoV-2 genome possesses 14 ORFs encoding 27 proteins. pp1ab and pp1a proteins are encoded by the orf1ab and orf1a genes located at the 5'-terminus of the genome, respectively. The pp1ab and pp1a proteins consist of 15 nsps that include nsp1 to nsp10 and nsp12 to nsp16. Four structural proteins (S, E, M, and N) and Five accessory proteins (ORF3a, ORF6, ORF7a, ORF7b, and ORF8) are encoded by the 3'-terminus of the SARS-CoV-2 genome.,
The envelope of the SARS-CoV-2 has glycoprotein spikes. The receptor-binding domain (RBD) of the SARS-CoV-2 is closer to GD pangolin-CoV. SARS-CoV-2 binds to angiotensin-converting enzyme-2 (ACE2) receptors through the receptor-binding domain of the spike glycoprotein. The spike glycoprotein contains S1 and S2 subunits with a furin-like cleavage site; S1 domain of the spike glycoprotein interacts with the ACE2 receptor and the S2 subunit allows membrane fusion.,
When the SARS-CoV-2 virus passes through the nasal and larynx mucosa, the patient shows early symptoms such as fever and cough. Around 5–10 days, the patient shows lower respiratory tract infection or pneumonia when the virus reaches the lung through the respiratory tract., The virus enters the vascular system through alveoli leading to viremia. SARS-CoV-2 affects the organs such as lungs, kidney, hearts, and gastrointestinal tract which expresses ACE2 receptors. Recent studies show that the virus lowers thrombin and prothrombin time deranging the blood coagulation., Clinical data reveal that patients with the SARS-CoV-2 infection show neurological symptoms also as impaired taste, smell, headache, disturbance of consciousness, and epilepsy.
SARS-CoV-2 clades and variants: GISAID database classified the SARS-CoV-2 in four major clades in the context of marker variants relative to WIV04 reference sequence. Clade “L” (Wuhan reference sequence), clade “S” (leucine replaced by serine at the 84th position [L84S mutation] in ns8), clade “V” (leucine replaced by phenylalanine at the 37th position [L37F mutation] in nsp6 and glycine replaced by valine at the 251st position [G251V mutation] in ns3), and clade G (aspartic acid replaced by glycine at the 614th position [D614G mutation] in spike glycoprotein). The clade “G” is further classified as clade “GH” (D614G mutation in spike glycoprotein and glutamine replaced by histidine at the 57th position [Q57H mutation] in ns3) and subclade “GR” (D614G mutation in spike glycoprotein and glycine replaced by arginine at the 204th position [G204R mutation] in nucleocapsid protein).
Because of high replication rate, SARS-CoV-2 is mutating and spreading rapidly. Clinical trials of RNA-dependent RNA polymerase (RdRp) inhibitor drugs are going on to combat the SARS-CoV-2 infection. Mutations of SARS-CoV-2 are critical spread of the virus, morbidity, mortality, vaccine development, and treatment of the infection.
This study was conducted to identify mutations present in SARS-CoV-2 genomic sequences of India and to find out their geographical location. One of the objectives was to find out the progressions of mutation with the phases of lockdown.
| Material and Methods|| |
SARS-Cov-2 genomic sequences submitted up to May 26, 2020, were retrieved from GSAID. Three hundred and sixty-three complete genome sequences from India were retrieved from the data source. The data contain information of various parameters such as viral strain name, data of sample collection, country, and state of origin of the sample along with the accession number of the sequence. The sequences were compared with the reference sequence (sequence id in GISAID: hCov-19/Wuhan/WIC04/2019 and access id in NICB database: NC_045512 sequence from the Wuhan, China). The study does not involve any living human or animal so does not require ethical committee approval.
Phylogenetic tree was constructed using maximum likelihood method and the Tamura–Nei model, applying neighbor-join and BIONJ algorithms to a matrix of pairwise distances estimated using the Tamura–Nei model, and then selecting the topology (1000 bootstrap replicates) with superior log-likelihood value. This analysis involved 364 nucleotide sequences. Evolutionary analyses were conducted in MEGA X.
Incomplete genomic sequences and with more than 1% nucleotide stretching were not considered for mutation identification and analysis. Finally, 317 genomic sequences were included for the identification of the mutation. Multiple sequence alignments for nucleotide sequences and the amino acid were done with MAFFT version 7 (Wellcome Genome Campus, Hinxton, Cambridgeshire). Amino acid mutations were distributed according to the geographical area of the sample collection. Demographic data and death rate of Indian SARS-CoV-2 cases according to states were accessed from the Indian COVID-19 dashboard on 9.52 A. M. on the May 31, 2020.
Statistical analysis was performed by the Epi Info 7™ software and R software. After checking the normality of distribution with the Shapiro–Wilk test, continuous variables were analyzed for median, mode, mean, and range. Categorical variables were analyzed for counts and frequency. Fisher's exact test of neutrality for sequence pairs was performed (P < 0.05). For the number of mutations per genome related to the states, we used Fisher's exact tests.
| Results|| |
Phylogenetic tree [Figure 1] of 364 nucleotide sequences (one of which was the reference sequence hCov-19/Wuhan/WIC04/2019 and NC_045512) was inferred using the maximum likelihood method and Tamura–Nei model. Number in bracket shows the branch number. The phylogenetic tree shows that the first two cases of India (access id EPI_ISL_413522 and EPI_ISL_413523) are closer to the reference sequence from Wuhan, China. A sequence from Telangana (access id EPI_ISL_447866) shows the maximum distance (99.87% similarity) from the reference sequence. A sequence from Madhya Pradesh (access id EPI_ISL_436453) shows the minimum distance (99.99% similarity) from the reference sequence.
|Figure 1: Phylogenetic tree of Indian severe acute respiratory syndrome coronavirus-2 genomic sequences (maximum likelihood and neighbor-joining model) (number in the bracket shows the branch number. Words “G,” “GH,” “GR,” “V,” “L,” “S,” and “others” indicate the clade of the severe acute respiratory syndrome coronavirus-2. Location has been mentioned along with the clade wherever it is necessary)|
Click here to view
Phylogenetic tree shows that SARS-CoV-2 mutates into clade “GH” in the second and third phases of lockdown. As shown at the branch no. 474, sequences marked with clade “others” (which shows more similarity to reference sequence) mutate into clade “G,” clade “V,” clade “S,” and clade “GR.” Clade “V” and clade “S” do not show further progression.
Three hundred and seventeen SARS-CoV-2 genomic sequences were aligned with the reference sequence (hCov-19/Wuhan/WIC04/2019 and NC_045512). Amino acid and nucleotide mutations were identified and analyzed.
Lockdown phase-wise analysis
Three hundred and seventeen SARS-CoV-2 genomic sequences were classified according to the date of collection in four groups [Figure 2]. The first group was before March 25, 2020 (before lockdown, n = 61); the second group was from March 25, 2020 to April 14, 2020 (the first phase of lockdown, n = 121); the third group was from April 15, 2020, to May 3, 2020 (the second phase of lockdown, n = 105); and the fourth group was May 4, 2020–May 17, 2020 (the third phase of lockdown, n = 30).
|Figure 2: Mutations frequency of severe acute respiratory syndrome coronavirus-2 genomic sequences as per phases of lockdown|
Click here to view
The difference in the means of the mutation among phases of lockdown was statistically significant. (ANOVA, a parametric test for inequality of population means, P = 0.0098 and Bartlett's test for inequality of population variances P = 0.0381); mutations increased significantly during the third phase of the lockdown, which shows that the frequency of mutations increases with the time and spread of the virus.
Lockdown phases and severe acute respiratory syndrome coronavirus-2 clades
In this study, SARS-CoV-2 genomic sequences were classified in major clade “L,” clade “S,” clade “V,” clade “G,” clade “GH,” clade “GR,” and “others” to identify their distribution during various phases of lockdown [Figure 3].
|Figure 3: Clades of severe acute respiratory syndrome coronavirus-2 genomic sequences as per phases of lockdown (words “G,” “GH,” “GR,” “V,” “L,” “S,” and “others” indicate the clade of the severe acute respiratory syndrome coronavirus-2. Dotted lines indicate the LogRhythm scale for the clades)|
Click here to view
Out of 317, only 2 sequences show clade “V”; the clade “V” has not been reported after March 17, 2020, in India. Both sequences were submitted from Delhi – one (access id: EPI_ISL_435109) was from the female of 18 years old and another (access id: EPI_ISL_435108) was of the female of 22 years old.
Clade “GH” appeared after the first phase of lockdown and increased during the second and third phases of lockdown.
Maximum sequences were available from Gujarat (n = 128), followed by Telangana (n = 59) and Delhi (n = 35). Sequences of Indian contact of Indian patients having travel history to Italy (n = 4), Indian citizens tested at Iran (n = 14), Italian tourists (n = 5), and Indian contact of Italian tourists (n = 1) were also analyzed [Figure 4] and [Table 1].
|Figure 4: Distribution of severe acute respiratory syndrome coronavirus-2 genomic sequences mutations according to locations (the color density indicates means of mutation, higher the density high means of mutations, states with more than 5 genomic sequences only are plotted on the map)|
Click here to view
|Table 1: Location-wise clade distribution of severe acute respiratory syndrome coronavirus-2 genomes|
Click here to view
Among 317 sequences studied, 1495 amino acid mutations were identified (95% confidence interval; mean = 4.7161, standard deviation = 1.823, median = 5, and mode = 4); Telangana shows a high number of mutations in comparison to the rest of India (mean = 5.508, median = 5, and mode = 5); the difference in frequency of mutation among Telangana and the rest of India was statistically significant (two-tailed Fisher's exact test, P = 0.023).
Out of 317 sequences, 95 sequences were of clade “G” and 56 of “GH” clade. Fifty-five out of 56 clade “GH” were from only Gujarat [[Table 1], two-tailed Fisher's exact test, P = 0.000001].
Spike protein mutation
SARS-CoV-2 clade with glycine (G) instead of aspartic acid (D) at the residue 614 in spike glycoprotein is identified as clade “G.” S1 subunit of the spike protein that contains the receptor-binding domain shows D614G mutation in 166 sequences. 88.28% (113 out of 128) genomic sequences submitted from Gujarat show the D614G mutation, while genomic sequences from the rest of India show D614G mutation in 28.19% (53 out of 189) of cases. The difference in the spike protein D624G mutation frequency between Gujarat and the rest of India is statistically significant (P < 0.00001, two-tailed Fisher's exact test).
Fifty-six sequences show Q57H mutation (glutamine replaced by histidine at the 57th position) in ns3 (orf3 protein) along with D614G mutation of spike protein. Fifteen sequences show G204R mutation (glycine replaced by arginine at the 204th position) in nucleocapsid protein along with D614G mutation of spike protein.
Nonstructural protein 2 mutation
Nineteen sequences show the replacement of valine (V) by isoleucine (I) at the 198th position (V198I mutation) of nsp2. Nine out of 19 sequences were from the Indian citizens sampled at Iran, three were from the Indian contact of Indian patients having travel history to Italy, one was in Italian tourist, and six were from the Ladakh. Seventeen sequences show the replacement of arginine by cysteine at the 27th position of nsp2. Arginine replaced cysteine at the 27th position of nsp2 in 17 sequences; this mutation evolves with the V198I mutation of nsp2.
Nonstructural protein 3 mutation
Lysine (K) instead of threonine (T) at the residue 1198 (T1198K mutation) was found in 121 genomic sequences. 93.22% (55 out of 59) genomic sequences submitted from Telangana show T1198K mutation, while genomic sequences from the rest of India show T1198K mutation in 25.58% (66 out 258) genomic sequences. The difference in the frequency of T1198K mutation between Telangana and the rest of India is statistically significant (P < 0.05, two-tailed Fisher's exact test).
Nonstructural protein 6 mutation
L37F mutation (leucine replaced by phenylalanine at the residue 37) was found in 141 genomic sequences. 93.22% (55 out of 59) genomic sequences submitted from Telangana show L37F mutation, while genomic sequences from the rest of India show L37F mutation in 33.33% (86 out 258) genomic sequences. The difference in the frequency of L37F mutation between Telangana and the rest of India is statistically significant (P = 0.00001, two-tailed Fisher's exact test).
Nonstructural protein 12 mutation
Total 363 amino acid mutations of 23 types were seen in nsp12 in the studied 317 genome sequences. One or more mutation of nsp12 was found in 296 out of 317 sequences; proline replaced by leucine at the residue 323 (P323 L mutation) being most frequent was present in 167 sequences. Valine replacing alanine at the residue 97 (A97V mutation) was present in 126 sequences. 87.5% (112 out of 128) genomic sequences submitted from Gujarat show the P323 L mutation, while genomic sequences from the rest of India show P323 L mutation in 29.10% (55 out of 189) sequences. The difference in the frequency of P323 L mutation between Gujarat and the rest of India is statistically significant (P < 0.05, two-tailed Fisher's exact test).
Both P323 L mutation of nsp12 and D614G mutation of spike glycoprotein were present in 164 sequences, which indicates that P323 L mutation evolves with the D614G mutation.
Nucleocapsid protein mutation
Forty types of 212 mutations in nucleocapsid protein were found in 317 studied sequences. Proline (P) replaced leucine (L) at the residue 13 (P13 L mutation) of nucleocapsid protein in 118 sequences. [Figure 5] shows the part of nucleocapsid protein sequence showing P13 L mutation. Fifty-seven out of 59 sequences of Telangana show the P13 L mutation in nucleocapsid protein. One hundred and nine sequences show both T1198K mutation in nsp3 and P13 L mutation in nucleocapsid protein.
|Figure 5: Nucleocapsid protein sequence alignment showing proline replaced by leucine at the 13th position|
Click here to view
Forty sequences show the replacement of leucine (L) by serine (S) at residue 194 in the nucleocapsid protein; 34 out of which were present from Gujarat.
| Discussion|| |
In the presented study, 364 sequences were studied for phylogenetic analysis; 317 sequences after deducting sequences with more than 1% nucleotide were considered for mutation analysis.
Replacement of aspartic acid (D) with the glycine (G) at the residue 614 in spike glycoprotein determines the clade “G” of the SARS-CoV-2 [Figure 6].,
|Figure 6: Receptor binding domain of spike glycoprotein of clade GH (D614G mutation in spike glycoprotein and glutamine replaced by histidine at the 57th position [Q57H mutation] in ns3). Blue dot indicates the affected receptor-binding area by the mutation|
Click here to view
Mutation of nsp12 at residue 323 (P to L) was seen in 164 sequences along with the D614G mutation of spike glycoprotein, which indicates that a P323 L mutation of nsp12 evolves with the D614G mutation of the spike glycoprotein. Previous studies have proved linkage disequilibrium between these two mutations in different populations.,
In the presented study, 88.28% (113 out of 128) genomic sequences of Gujarat show D614G mutation in the S glycoprotein at the RBD, S1 subunit, that is significantly high than the rest of India. The high number of clade “GH” in Gujarat indicates progressed mutation in Gujarat, and it is noticeable that Gujarat has a 6.15% death rate (1007 out of 16356) in the SARS-CoV-2-confirmed cases that are higher than the death rate of the rest of India (2.84%, 5185 out of 182275) as per 9.52 A. M. on May 31, 2020.
S glycoprotein plays an important role in viral entry and pathogenicity of coronavirus. S glycoprotein of the SARS-CoV-2 contains S1 and S2 subunits. S1 subunit is responsible for receptor binding and the S2 subunit allows membrane fusion with the host cell. S1 domain contains RBDs. B-cell epitope is present at the 614 positions of the S1 subunit; D614G mutation affects the conformation of the immunological determinant (amino acids 613-621) that may cause failure to act as a B-cell epitope in SARS-CoV-2. B-cell has an important role in adaptive immunity in virus infection by identifying the antigen. Elimination of B-cell epitope in D614G mutation of the spike glycoprotein reduces immunogenicity and may allow recurrent SARS-CoV-2 infection. It shows that SARS-CoV-2 strain with D614G mutation at the S1 subunit of glycoprotein may have higher mortality than the other clades.
L37F mutation in nsp6 was found in 53.20% (141 out of 317) genomic sequences. nsp6 being a transmembrane protein forms a double-membrane vesicle along with nsp3 and nsp4 protein. Although the 37th residue of nsp6 is a part of the unstructured coil segment, Phe residue at the position in L37F mutants can perform cation–n interaction which may affect the protein–protein interaction.
Twenty-three types of 318 amino acid mutations were seen in nsp12 of the SARS-CoV-2, out of which 126 sequences show the replacement of valine amino acid at residue at 97 with alanine in nsp12. The nsp12 plays an important role in transcription and translation of the viral genome. The nsp12 is the target of choice for RNA-dependent RNA polymerase inhibitors including undertrial drug remdesivir. Nucleoside analog inhibitor (e.g., remdesivir) acts on RNA-dependent RNA polymerase (RdRp); RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 consists of nsp12 (catalytic subunit) and two accessory subunits (nsp8 and nsp7)., Mutations in nsp12 and exonuclease site nsp14 are of concern in India as mutations in the nsp12 have been found responsible for resistance to RNA-dependent RNA polymerase inhibitors in other viruses.,
D614G mutation of spike glycoprotein has shown relation with the P323 L mutation of nsp12; combination of the mutation may affect the response of vaccine and drugs also.
In this study, we found 212 mutations in nucleocapsid protein that is an important site of T-cell epitope. P13 L residue in nucleocapsid protein was the most frequent (118 out of 317 sequences) in this study.
Mutation of the orf3 protein was found more frequently in Gujarat than the rest of India. orf3a along with orf1a, orf1b, and orf10 can dissociate the iron from the porphyrin by attacking the heme on hemoglobin 1-beta chain, leading to reduced hemoglobin to carry oxygen. As mutation of orf3 can affect the virulence and pathogenicity of the SARS-CoV-2 infection, high frequency of mutation of the residue Q57H along with D614G mutation of spike glycoprotein (that determines clade GH) in Gujarat may be one of the factors for high mortality in Gujarat. Although clade “GH” is restricted in Gujarat, after lockdown is relaxed, huge migration has been happened in May; the clade “GH” may spread to other parts of India also. That should be an important concern to combat the mortality and morbidity of SARS-CoV-2 infection.
The study shows that the mutations have been increasing with the spread of infection. Mutations and clades show differences among states. Borders of states are opened after the lockdown is withdrawn that may mix up the different clades in various states. Almost 12 lakh people migrated from Gujarat and 20 lakh people migrated from Maharashtra; such a large migration may spread mutations of Gujarat and Maharashtra other less affected areas.
Not enough number of sequences are available from less affected states (e.g. Kerala) that might have helped to identify the correlations of mutation in wider bases; we did not have status data of all patients in the study so could not correlate mutations with actual effect on morbidity and mortality.
| Conclusion|| |
SARS-CoV-2 mutations may progress and spread in less affected areas of India after the lockdown is withdrawn. As the mutations are crucial for response of SARS-CoV-2 to the various drugs and vaccines under clinical trials, it is recommended to identify the efficacy of various drugs according to the different mutations and clades of the virus.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Hui DS, Azhar E, Madani TA, Ntoumi F, Kock R, Dar O, et al.
The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health – The latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis 2020;91:264-6.
Rubino S, Kelvin N, Bermejo-Martin JF, Kelvin D. As COVID-19 cases, deaths and fatality rates surge in Italy, underlying causes require investigation. J Infect Dev Ctries 2020;14:265-7.
Yan Y, Shin WI, Pang YX, Meng Y, Lai J, You C, et al
. The first 75 days of novel coronavirus (SARS-CoV-2) outbreak: Recent advances, prevention, and treatment. Int J Environ Res Public Health 2020;17:2323.
Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, et al
. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 2020;579:270-3.
Song Z, Xu Y, Bao L, Zhang L, Yu P, Qu Y, et al.
From SARS to MERS, thrusting coronaviruses into the spotlight. Viruses 2019;11:59.
Wu A, Peng Y, Huang B, Ding X, Wang X, Niu P, et al.
Genome composition and divergence of the novel coronavirus (2019-nCoV) originating in China. Cell Host Microbe 2020;27:325-8.
Mousavizadeh L, Ghasemi S. Genotype and phenotype of COVID-19: Their roles in pathogenesis. J Microbiol Immunol Infect 2021;54:159-63.
Ye ZW, Yuan S, Yuen KS, Fung SY, Chan CP, Jin DY. Zoonotic origins of human coronaviruses. Int J Biol Sci 2020;16:1686-97.
Wu Y, Li C, Xia S, Tian X, Kong Y, Wang Z, et al.
Identification of human single-domain antibodies against SARS-CoV-2. Cell Host Microbe 2020;27:891-8.e5.
Tai W, He L, Zhang X, Pu J, Voronin D, Jiang S, et al.
Characterization of the receptor-binding domain (RBD) of 2019 novel coronavirus: Implication for development of RBD protein as a viral attachment inhibitor and vaccine. Cell Mol Immunol 2020;17:613-20.
Huang JT, Ran RX, Lv ZH, Feng LN, Ran CY, Tong YQ, et al.
Chronological changes of viral shedding in adult inpatients with COVID-19 in Wuhan, China. Clin Infect Dis 2020;71:2158-66.
Khan T, Agnihotri K, Tripathi A, Mukherjee S, Agnihotri N, Gupta G. COVID-19: A worldwide, zoonotic, pandemic outbreak. Altern Ther Health Med 2020;26:56-64.
Hu B, Qiu J, Chen H, Tao V, Wang J, Lin H. First, second and potential third generation spreads of the COVID-19 epidemic in mainland China: An early exploratory study incorporating location-based service data of mobile devices. Int J Infect Dis 2020;96:489-95.
Lin L, Lu L, Cao W, Li T. Hypothesis for potential pathogenesis of SARS-CoV-2 infection – A review of immune changes in patients with viral pneumonia. Emerg Microbes Infect 2020;9:727-32.
Wei XS, Wang X, Niu YR, Ye LL, Peng WB, Wang ZH, et al.
Diarrhoea is associated with prolonged symptoms and viral carriage in corona virus disease 2019. Clin Gastroenterol Hepatol 2020;18:1753-9.e2.
Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol 2020;92:552-5.
Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol 1993;10:512-26.
Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 2018;35:1547-9.
Madeira F, Park YM, Lee J, Buso N, Gur T, Madhusoodanan N, et al.
He EMBL-EBI search and sequence analysis tools APIs in 2019. Nucleic Acids Res 2019;47:W636-41.
Bartolini B, Rueca M, Gruber CE, Messina F, Carletti F, Giombini E, et al.
SARS-CoV-2 phylogenetic analysis, Lazio Region, Italy, February-March 2020. Emerg Infect Dis 2020;26:1842-1845. [Doi: 10.3201/eid2608.201525].
Kim SJ, Nguyen VG, Park YH, Park BK, Chung HC. A novel synonymous mutation of SARS-CoV-2: Is this possible to affect their antigenicity and immunogenicity? Vaccines (Basel) 2020;8:220.
Veeramachaneni GK, Thunuguntla VB, Bobbillapati J, Bondili JS. Structural and simulation analysis of hotspot residues interactions of SARS-CoV 2 with human ACE2 receptor. J Biomol Struct Dyn 2021;39:4015-25.
Cárdenas-Conejo Y, Liñan-Rico A, García-Rodríguez DA, Centeno-Leija S, Serrano-Posada H. An exclusive 42 amino acid signature in pp1ab protein provides insights into the evolutive history of the 2019 novel human-pathogenic coronavirus (SARS-CoV-2). J Med Virol 2020;92(6):688-692. [Doi: 10.1002/jmv. 25758].
Hillen HS, Kokic G, Farnung L, Dienemann C, Tegunov D, Cramer P. Structure of replicating SARS-CoV-2 polymerase. Nature 2020;584:154-6.
Ahn DG, Choi JK, Taylor DR, Oh JW. Biochemical characterization of a recombinant SARS coronavirus nsp12 RNA-dependent RNA polymerase capable of copying viral RNA templates. Arch Virol 2012;157:2095-104.
Shannon A, Le NT, Selisko B, Eydoux C, Alvarez K, Guillemot JC, et al.
Remdesivir and SARS-CoV-2: Structural requirements at both nsp12 RdRp and nsp14 exonuclease active-sites. Antiviral Res 2020;178:104793.
Jorgensen SC, Kebriaei R, Dresser LD. Remdesivir: Review of pharmacology, pre-clinical data, and emerging clinical experience for COVID-19. Pharmacotherapy 2020;40:659-71.
Ahmed SF, Quadeer AA, McKay MR. Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies. Viruses 2020;12:254.
Ahmadpour D, Ahmadpoor P. How the COVID-19 overcomes the battle? An approach to virus structure. Iran J Kidney Dis 2020;14:167-72.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]