The study of mutations and phylogenetics of the SARS-CoV-2 spike gene in population from Tehran province

Document Type : Original Articles

Authors

1 Razi vaccine and Sera institute

2 Department of Virology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran

3 Applied Biotechnology Research Center, Baqiyatallah University of Medical Science, Tehran, Iran

4 Department of Electrical and Computer Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON N2L Canada

5 Department of Microbiology, Faculty of Sciences, Islamic Azad University, Karaj Branch, Karaj, Iran

6 Razi vaccine and sera research institute

10.32592/ARI.2025.80.1.185

Abstract

In December 2019, an outbreak of pneumonia of unknown etiology was reported in Wuhan, China. The virus, known as SARS-CoV-2, is contagious and infects the lower respiratory tract. Since various coherent research needs to be conducted in Iran to detect mutations in the SARS-CoV-2 S gene, the present study was conducted to determine the sequence, mutation pattern, and phylogenetic evaluation of this gene. For this purpose, 120 positive samples were included to evaluate the complete S gene sequence by Reverse transcriptase-PCR. After sequencing, the gene assembly, blasting, mutation analysis, and phylogenetic analyzes were performed using MEGA-X. A total of 161 mutations were observed in the S gene sequences of Iran. The results of the phylogenetic tree showed that all the S gene sequences of Iranian samples were divergent from the Wuhan strain and had the most similarity to it and also alpha variants. 161 nonsynonymous variations were found along the complete coding S gene with a high frequency of A262T, D614G, and P863H, which were embedded in HVR1, HVR2, and HVR3, respectively. Most of Highly variable fragments have been identified in loop secondary structure of protein.
In the current study, the predominant variants (mostly alpha variants) and mutations were in parallel with the evolution of the virus and its fitness. We provided a wide picture of the genetic mutation of first three waves of SARS-CoV-2 in Iran which could be used to make big decisions and take effective decisions in the next pandemics to develop vaccines and kits and effective therapeutics.

Keywords

1. Introduction

At the conclusion of 2019, an outbreak of severe acute respiratory syndrome (SARS) was reported from Wuhan, China, which subsequently spread rapidly on a global scale. The causative agent was identified as a novel coronavirus (2019-nCov). Subsequently, the virus was designated severe acute respiratory syndrome coronavirus-2 (SARS-Cov2). The high transmissibility of SARS-CoV-2 resulted in the declaration of a pandemic by the World Health Organization (WHO) in March 2020 ( 1 ). As of now, the WHO has reported more than 251,788,329 confirmed cases and 5,077,907 deaths ( 2 ). The virus belongs to the Nidovirales order, coronaviridae family, coronavirinae subfamily and Betacoronavirus genus ( 3 ). It possesses a single-stranded positive-sense RNA genome of 29,891 bp in size, as demonstrated in Figure 1. The genome organisation is as follows: the spike protein, as a surface glycoprotein, is responsible for receptor binding, and the spike protein composes two subunits: S1 and S2, with the function of receptor binding and membrane fusion, respectively ( 4 ).The S1 subunit can bind to angiotensin-converting enzyme-2 (ACE-2) and other alternative receptors, such as CD147 and neuropilin, on the host cell and mediates the cell entry ( 4 , 5 ). It is well established that during the replication of coronaviruses, a multitude of mutations can occur, the majority of which are deleterious and neutral. However, it is noteworthy that certain mutations have the capacity to exacerbate the severity, infectivity and transmissibility of the virus ( 6 ). Indeed, mutations within the receptor-binding domain (RBD) of the S1 subunit have been shown to disrupt species barriers, thereby facilitating viral transmission between animals and humans ( 7 ). Evidence indicates that certain variations in the SARS-CoV-2 S gene can not only alter the viral antigenic phenotype, but also have a significant impact on viral infectivity, immune evasion, and pathogenicity ( 8 ). For instance, a nonsynonymous substitution at position 614 (D614G) has been observed to enhance viral replication and transmission, though there is no clear association with increased severity of infection ( 9 ). The Global Influenza Surveillance and Response System (GISRS) has identified 21 distinct clades for SARS-CoV-2 based on the mutations across the whole genome of the virus (https://nextstrain.org). Conversely, the WHO has recently adopted a novel nomenclature system for variants of concern, utilising the Greek alphabet. These variants are categorised as Alpha (lineage B.1.1.7), Beta (lineage B.1.3 51), Gamma (lineage P.1), Delta (lineage B.1.617.2), and Omicron (lineage B.1.1.529) (https://cov-lineages.org).From July to November 2021, Delta variants (21I and 21J) were the most prevalent circulating variants worldwide, causing concern even among fully vaccinated individuals. In late November 2021, a new variant designated Omicron was identified by the WHO, which was predicted to spread rapidly. Variations in the surface glycoprotein have the capacity to modify infectivity and immune responses. The present study therefore sought to investigate the complete coding sequence of the S gene in circulation among the Iranian population, with a view to ascertaining its genetic variations.

Figure 1. Shannon entropy of SARS-CoV-2 spike glycoprotein. The X and Y axes indicate amino acid positions and entropy, respectively. Bars near zero indicate the conserved sequences while bars greater than zero with greater height show amino acid positions with much variability, which show by arrows. Also, the S1, S2 subunits, and cleavage sites (positions 680-687) are displayed. HVR, hypervariable region; SHVR, Semi- hypervariable region.

2. Materials and Methods

2.1. Sample Collection

In the period between February and November 2020, a total of 120 nasal and/or oropharyngeal swabs were collected from patients referred to the Keyvan Virology Laboratory in Tehran. The samples that were positive for the SARS-CoV-2 test were included in the study.

2.2. Viral RNA Extraction and Complementary DNA (cDNA) Synthesis

The isolation of viral RNA from the samples was conducted in accordance with the stipulated instructions provided by the manufacturer of the LabPrep TM Viral DNA/RNA Mini Kit. The subsequent synthesis of cDNA was facilitated by the biotech rabbit GmbH kit (Berlin, Germany), utilizing a total reaction volume of 20 µl and the following components:

2 µl dNTP mix (10 mM for each), 0.5 µl RNase inhibitor, 0.5 µl oligo dT primer, 1 µl random hexamer primer, 4 µl 5x reverse transcriptase buffer biotech rabbit kit, 10 µl RNA template, 1 µl Moloney-Murine Leukemia Virus (MMuLV) reverse transcriptase, 1 µl RNase-free water. The RT-PCR reaction profile was set up at 30°C for 10 min, 55°C for 40 min, and 99°C for 5 min. The complete coding sequence of the S gene was amplified using primers and a PCR profile, the details of which can be found in Table 1. In addition, the β-globin gene was utilized to ensure the quality of the samples.

Primer name 5’- 3’ sequences PCR product Length Thermocycler program Ref
25-Forward CTTGGAGGTTCCGTGGCTAT 1077 bp Primary denaturation: 94 °C, 150 s ( 3 )
25-Reverse AAACCCTGAGGGAGATCACG Denaturation: 94 °C, 40 s
Annealing: 59 °C, 55 s x39
Extension: 72 °C, 128 s
Final extension: 72 °C, 600 s
26-Forward TATCTTGGCAAACCACGCGA 1057 bp Primary denaturation: 94 °C, 210 s ( 3 )
26-Reverse ACCAGCTGTCCAACCTGAAG Denaturation: 94 °C, 40 s
Annealing: 58 °C, 45 s x39
Extension: 72 °C, 120 s
Final extension: 72 °C, 420 s
27-Forward CCCTCAGGGTTTTTCGGCTT 1093 bp Primary denaturation: 94 °C, 180 s ( 3 )
27-Reverse CTGTGGATCACGGACAGCAT Denaturation: 94 °C, 40 s
Annealing: 60 °C, 48 s x39
Extension: 72 °C, 150 s
Final extension: 72 °C, 420 s
28-Forward CCAGCAACTGTTTGTGGACC 1027 bp Primary denaturation: 94 °C, 180 s ( 3 )
28-Reverse GTGGCAAAACAGTAAGGCCG Denaturation: 94 °C, 40 s
Annealing: 60 °C, 48 s x39
Extension: 72 °C, 135 s
Final extension: 72 °C, 480 s
29-Forward ACTTGCAGATGCTGGCTTCA 1084 bp Primary denaturation: 95 °C, 135 s ( 3 )
29-Reverse CTCATTGAGGCGGTCAATTTCT Denaturation: 94 °C, 40 s
Annealing: 57 °C, 58 s x39
Extension: 72 °C, 120 s
Final extension: 72 °C, 540 s
30-Forward TGATTTAGGTGACATCTCTGGCA 1106 bp Primary denaturation: 95 °C, 180 s ( 3 )
30-Reverse ACAACTCCGGATGAACCGTC Denaturation: 94 °C, 40 s
Annealing: 59 °C, 50 s x39
Extension: 72 °C, 135 s
Final extension: 72 °C, 420 s
 Table 1.Primers and thermal cycling profiles.

2.3. Bioinformatic Analysis

The amplified sequences were verified by 1% agarose gel electrophoresis and subsequently sent for Sanger sequencing. The amplicons that were successfully sequenced were analysed using BioEdit ( 10 ) and then subjected to blast searches using BLASTn, BLASTp and MEGA X ( 11 ) with reference sequences (NC_045512, MZ314997, MZ314998, MZ611965 and OK091006). The construction of the phylogenetic tree was performed using the neighbour-joining method with the Kimura 2-parameter model and a bootstrap value of 1000, implemented in MEGA X.To investigate the variations present in the understudied sequences, these were analysed as either being embedded in hypervariable regions (HVRs) or not. To this end, Shannon entropy analysis was employed, with a threshold of 0.3, thus revealing three regions: 1) HVRs exhibiting a higher degree than the threshold, 2) semi-HVRs situated near the threshold, and 3) variable regions falling beneath the threshold. The 3D structure of the spike glycoprotein model was modelled using the SWISS-MODEL online server (https://swissmodel.expasy.org/interactive), with energy minimisation conducted using SPDB viewer software. Visual analysis and editing was performed using Chimera UCSF software.

3. Results

3.1. Mutations

In the present study, the complete coding sequence of the S gene was successfully determined by means of sequencing and translation to amino acid sequences for 117 of the 120 samples enrolled. This was achieved using the online tool Basic Local Alignment Search Tool (BLASTx).A total of 161 nonsynonymous substitutions were observed in understudied amino acid sequences (Table 2). The most prevalent variations included V11I (n=17), T22I (n=11), K77N (n=12), D111N (n=15), A262T (n=42), D614G (n=45), and P863H (n=23). Furthermore, 3D structural analysis demonstrated that the majority of variations within this study, particularly those that were frequently substituted, such as A262T, D614G, and P863H, were located in SHVR1 (amino acid positions 13-25), HVR1 (amino acid positions 255-265), SHVR2 (amino acid positions 485-496), HVR2 (amino acid positions 613-620), and HVR3 (amino acid positions 857-865) (data not displayed).

2 9 11 13 14 18 21 22 30 34 37 40 42 44 47 59 65 74 77 78 95 97 106 111 115 123 136 141 149 151 156
Ref F P V S Q L R T N R Y D V R V F F N K R T K F D Q A C H N S E
Iranian samples L Q I N/R H P K I I H N E L/I K/I I I I H N K I N L N H T W R H G D
counts 2 1 17 2/6 5 2 3 11 2 2 3 1 2/4 7/2 7 2 2 2 12 2 1 2 2 15 4 2 2 2 1 1 5
158 159 161 162 169 173 181 185 187 190 191 193 194 198 199 200 206 207 210 211 212 213 215 216 220 222 224
Ref R V S S E Q G N K R E V F D G Y K H T N L V D L F A E
Iranian samples L I F I Q H R I N/Q S D L L E R N N L S Y/H S L/G H H V T/V/P K
counts 2 3 2 2 2 4 1 2 2/3 3 2 2 2 2 2 3 2 3 2 1/1 1 1/1 1 1 1 1/1/3 8
225 226 227 228 229 231 234 235 240 247 262 271 288 302 407 408 411 412 427 440 448 463 485 487 488 510 511 512
Ref P L V D L I N I T S A Q A T V R A P D N N P G N C V V V
Iranian samples S/R/T I I/M/A I/E/N/Y F L S V S N T H P A L T T S N H K L S I R E I I
counts 1 1 2/1/1 1/2/3/1 2 4 2 1 2 3 42 2 3 2 3 2 2 2 2 2 2 2 2 5 3 3 2 3
520 522 534 535 535 536 568 614 620 636 648 652 653 655 658 661 669 672 675 677 684 686 688 702 705 710 716 726
Ref A A V K N N D D V Y G G A H N E G A Q Q A S A E V N T I
Iranian samples S P G V/E E K H G F F R R P Y H D R P R H V T T/P K I/F T P F
counts 1 4 2 2/2 2 2 2 45 2 2 4 3 3 2 3 3 5 5 7 8 2 2 2 3 4/2 2 2 2
747 758 780 781 790 791 798 811 815 820 826 830 837 838 834 847 848 851 863 874 875 903 905 916 932 1019 1181
Ref T S E V K T G K R D V D Y G D R D C P T S A R L G R K
Iranian samples P I/T K F Q P A N K N G N N A/D G K N W H P F G S F A K Q
counts 2 3/2 2 3 3 2 2 2 3 5 3 3 2 2/2 3 4 4 4 23 3 3 2 2 3 2 2 2
Table 2.Mutations and their frequencies in the sequenced samples.

3.2. Shannon Entropy and 3D Structure Analysis

The Shannon entropy variation analysis indicates the presence of three HVRs in the spike glycoprotein of SARS-CoV-2, including HVR1 in the N-terminal domain at positions 255-265, HVR2 in the S1 subunit at positions 613-620, and HVR3 in the S2 subunit at positions 857-866. HVR2 was identified as the most variable region among understudied sequences. In addition, three semi-HVRs were identified: amino acids 13 to 25 in the N-terminal domain, 485-495 in the receptor binding domain, and 540-548 in the S1 subunit.As anticipated, the C-terminus of the spike glycoprotein and amino acids surrounding the cleavage site (positions 672 to 698) exhibited the lowest variability. The Shannon entropy map and the three-dimensional structure of the spike glycoprotein amino acid sequences with different variable regions related to Iranian samples are illustrated in Figures 1 and 2.

Figure 2. 3D structure of modeled Spike glycoprotein from Iran and mutation regions. Most of Highly variable fragments have been identified in loop secondary structure of protein.

3.3. Phylogenetic Analysis

The neighbour-joining method was employed to construct the tree, with the software Mega 10 utilised for this purpose. As illustrated in Figure 3, all understudied sequences diverged from the Wuhan isolate, with some sequences demonstrating clustering with alpha variants, such as MW090904 and MW040523. The isolates MW040527, MW09087 9, MW090877, MW136260, MW045462, MW090866, MW136350, and MW136262 depicted most divergency from the Wuhan isolate, suggesting the initiation of further changes.A deeper analysis of the tree, based on topology and branches, resulted in the division of the tree into five main groups. The largest of these groups, designated Group 1, is further subdivided into Group 2. The most divergent sequence, characterised by its greater distance from the common ancestor of the sequences and the presence of more mutations and divergence, is MW045461. This sequence belongs to the first wave of the disease.The reference sequence is located in the first cluster, which is the largest cluster in Iran and contains the majority of the sequences. Cluster 5 is the smallest cluster and the sequences in it are more divergent and different than the other sequences and are closer to the common ancestor of the sequence.These sequences are MW045462 and MW090877, which are related to the second wave of corona virus infection in Iran, and an interesting point.Note the difference between these and other sequences, especially the existing sequences from the first wave of the disease. It is conceivable that these sequences may be the ancestors of certain Iranian sequences, and that other sequences may have arisen from them.

Figure 3. Phylogenetic tree of S gene from Iranian samples. The tree was drawn by using the neighbor-joining method, Kimura 2-parameter model with 1000 bootstrap replicates through Mega 10. The numbers above branches with values lower than 70 are hidden. The reference genomes are displayed with name of “NC045612 Wuhan-Hu-1” and remained accession numbers are responsible for isolates from this study. The Genbank accession numbers of all isolates from this study are gathered in Table 3.

MT163712 MW032265 MW039449 MW039533 MW039576 MW039602
MW040510 MW040512 MW040514 MW040516 MW040519 MW040520
MW040521 MW040523 MW040524 MW040525 MW040527 MW045445
MW045452 MW045453 MW045454 MW045459 MW045461 MW045462
MW045463 MW045464 MW045467 MW045468 MW045470 MW045471
MW045474 MW045477 MW055255 MW055256 MW055257 MW055258
MW055259 MW055367 MW055425 MW055435 MW055436 MW055437
MW063474 MW063476 MW063479 MW063481 MW063482 MW090849
MW090851 MW090852 MW090853 MW090854 MW090856 MW090857
MW090858 MW090859 MW090862 MW090863 MW090867 MW090866
MW090871 MW090872 MW090877 MW090879 MW090900 MW090902
MW090904 MW090920 MW090921 MW093135 MW093139 MW093140
MW135333 MW136260 MW136261 MW136262 MW136267 MW136350
MW136351 MW136352 MW136445 MW136446 MW165491 MW165492
MW165493 MW165494 MW165495 MW165496 MW165497 MW426075
MW440431 MW440432 MW440435 MW440434 MW440436 MW440437
MW440438 MW440439 MW440440 MW440441 MW440442 MW548589
MW548595 MW548606 MW548607 MW548608 MW548609 MW548611
MW548612 MW548629 MW548631 MW548632 MW548633 MW548636
MW548637 MW548638 MW548639
Table 3.The accession numbers obtained from this study.

4. Discussion

The present study set out to determine the mutations and lineages of Iranian SARS-CoV-2 samples based on the S gene. Phylogenetic analysis showed that all understudied sequences were grouped with the Wuhan SARS-CoV-2 isolate and alpha variants, as had been expected. Indeed, until November 2020, alpha variants had been often circulating. 161 nonsynonymous substitutions were found in the understudied sequences. The most prevalent substitutions included V11I (n=17), T22I (n=11), K77N (n=12), D111N (n=15), and A262T (n=42) within the N-terminus domain, with V11I situated within the signal peptide. The most prevalent variants were found to be D614G (n=45), A262T (n=42), and P863H (n=23). The earliest documented samples of Delta variants were recorded in India in October 2020 ( 12 ), while the majority of our samples were collected in the mid-2020s, suggesting the emergence of this variant in Iran. A notable variation among the Delta variants was the D614G substitution, which was identified in 38.5% of understudied sequences. While this substitution increased the replication of SARS-CoV-2 in various cells that express the ACE-2 receptor on their surfaces, it did not affect the potency of neutralising antibodies. A total of six amino acid changes in and around the cleavage site S1/S2 were identified, including A672P, Q675R, Q677H, A684V, A686T, and A688T/P. The presence of basic amino acids, such as lysine and histidine, at cleavage sites, particularly at positions Q675R and Q677H, has been demonstrated to enhance transmissibility by facilitating viral entry through the pH-independent pathway ( 15 ). Consistent with the findings of this study, Eslami et al. reported that the P863H variation, located in the fusion peptide-heptad repeat 1 span region, was frequently observed in Iranian SARS-CoV-2 samples ( 16 ).

In Iran, various variants analogous to those observed in other regions emerged during the onset of the corona disease. These include alpha (B.1.17 and Q.1-Q.8), beta (B.1.351, B.1.351.2 and B.1.351.3), and gamma (P.1, P.1.1, P.1.2). 17.2, AY.3, AY.2 and AY.1), gamma (P.1, P.1.1, P.1.2), epsilon (B.1.427, B.1.429), Eta (B.1.525), Uta (B.1.526 ), Omicron (BA.2), Kappa (B.1.617.1), 1.617.3, Mu (B.1.621, B.1.621.1), Zeta (P.2) and Lambda (C.37) ( 17 , 18 ). Among these variants, the alpha, beta, delta and gamma variants appeared in several waves of the disease and had the ability to transmit and cause disease, and it was necessary to use a vaccine against them ( 17 , 18 ).Variations in the SARS-CoV-2 genome are natural and can interfere with the adaptation between host and virus. The mutations in the Delta and Omicron variants, for instance, have been shown to enhance viral fitness, thereby increasing replication and transmissibility ( 19 ). Consequently, further investigation into these mutations is essential for the development of effective prevention, control, and preparedness programs, along with suitable vaccines. A total of 161 nonsynonymous variations were identified along the entire coding S gene, with A262T, D614G and P863H exhibiting a high frequency. These variations were found within HVR1, HVR2 and HVR3, respectively. The present study revealed that the predominant variants (alpha variants) and mutations were in parallel with the evolution of the virus and its fitness.

Acknowledgment

It must be noted that acknowledgments are not applicable in the given context.

Authors' Contribution

HK designed the study. HK and AML provided the materials and equipment. ShS collected samples and performed the study. MMR supervised and analyzed the subjects. MMK, FK, and MM wrote the first draft. MMK GH K assisted in bioinformatics analysis. FK submitted the sequences. All authors read and approved the final manuscript.

Ethics

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

Conflict of Interest

None

Grant Support

None

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Kesheh MM, Hosseini P, Soltani S, Zandi M. An overview on the seven pathogenic human coronaviruses. Reviews in Medical Virology. 2021;e2282.
  2. Virus Z. Novel Coronavirus (2019-nCoV). 2020;1-5.
  3. Ren L-L, Wang Y-M, Wu Z-Q, Xiang Z-C, Guo L, Xu T, et al. Identification of a novel coronavirus causing severe pneumonia in human: a descriptive study. Chinese medical journal. 2020; 133(9):1015.
  4. Yang Y, Du L. SARS-CoV-2 spike protein: a key target for eliciting persistent neutralizing antibodies. Signal Transduction and Targeted Therapy. 2021; 6(1):95.
  5. Masre SF, Jufri NF, Ibrahim FW, Abdul Raub SH. Classical and alternative receptors for SARS-CoV-2 therapeutic strategy. Reviews in medical virology. 2021; 31(5):1-9.
  6. Hu B, Guo H, Zhou P, Shi Z-L. Characteristics of SARS-CoV-2 and COVID-19. Nature Reviews Microbiology. 2021; 19(3):141-54.
  7. Jelinek HF, Mousa M, Alefishat E, Osman W, Spence I, Bu D, et al. Evolution, Ecology, and Zoonotic Transmission of Betacoronaviruses: A Review. Frontiers in Veterinary Science. 2021; 8
  8. Harvey WT, Carabelli AM, Jackson B, Gupta RK, Thomson EC, Harrison EM, et al. SARS-CoV-2 variants, spike mutations and immune escape. Nature Reviews Microbiology. 2021; 19(7):409-24.
  9. Volz E, Hill V, McCrone JT, Price A, Jorgensen D, O’Toole Á, et al. Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity. Cell. 2021; 184(1):64-75.
  10. Hall TA. BioEdit : a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser. 1999; 41:95-8.
  11. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol Biol Evol. 2018; 35(6):1547-9.
  12. Tracking SARS-CoV-2 variants: World Health Organization (WHO); 2021.
  13. Yurkovetskiy L, Wang X, Pascal KE, Tomkins-Tinch C, Nyalile TP, Wang Y, et al. Structural and Functional Analysis of the D614G SARS-CoV-2 Spike Protein Variant. Cell. 2020; 183(3):739-51.e8.
  14. Hou YJ, Chiba S, Halfmann P, Ehre C, Kuroda M, Dinnon KH, et al. SARS-CoV-2 D614G variant exhibits efficient replication ex vivo and transmission in vivo. Science (New York, NY). 2020; 370(6523):1464-8.
  15. Winstone H, Lista Maria J, Reid Alisha C, Bouton C, Pickering S, Galao Rui P, et al. The Polybasic Cleavage Site in SARS-CoV-2 Spike Modulates Viral Sensitivity to Type I. Interferon and IFITM2. Journal of Virology. 95(9):e02422-20.
  16. Eslami S, Glassy MC, Ghafouri-Fard S. A comprehensive overview of identified mutations in SARS CoV-2 spike glycoprotein among Iranian patients. Gene. 2022; 813:146113.
  17. Aliabadi N, Jamaliduost M, Pouladfar G, Marandi NH, Ziyaeyan M. Characterization and phylogenetic analysis of Iranian SARS-CoV-2 genomes: A phylogenomic study. Health Sci Rep. 2023; 6(1):e1052.
  18. Yavarian J, Nejati A, Salimi V, Shafiei Jandaghi NZ, Sadeghi K, Abedi A, Sharifi Zarchi A, Gouya MM, Mokhtari-Azad T. Whole genome sequencing of SARS-CoV2 strains circulating in Iran during five waves of pandemic. PLoS One. 2022; 17(5):e0267847.
  19. Sofonea MT, Roquebert B, Foulongne V, Verdurme L, Trombert-Paolantoni S, Roussel M, et al. From Delta to Omicron: analysing the SARS-CoV-2 epidemic in France using variant-specific screening tests (September 1 to December 18, 2021). medRxiv. 2022;:12-. ;12.
Archives of Razi Institute
Volume 80, Issue 1
January and February 2025
Pages 185-192

Files

Share

How to cite

Statistics