Back

Surveillance of genetic diversity and evolution in locally transmitted SARS-CoV-2 in Pakistan during the first wave of the COVID-19 pandemic

Shakeel, M.; Irfan, M.; Nisa, Z.; Rashid, M.; Ansari, S. K.; Khan, I. A.

2021-01-14 genomics
10.1101/2021.01.13.426548 bioRxiv
Show abstract

Surveillance of genetic diversity in the SARS-CoV-2 is extremely important to detect the emergence of more infectious and deadly strains of the virus. In this study, we monitored mutational events in the SARS-CoV-2 genome through whole genome sequencing. The samples (n=48) were collected from the hot spot regions of the metropolitan city Karachi, Pakistan during the four months (May 2020 to August 2020) of first wave of the COVID-19 pandemic. The data analysis highlighted 122 mutations, including 120 single nucleotide variations (SNV), and 2 deletions. Among the 122 mutations, there were 71 singletons, and 51 recurrent mutations. A total of 16 mutations, including 5 nonsynonymous mutations, were detected in spike protein. Notably, the spike protein missense mutation D614G was observed in 31 genomes. The phylogenetic analysis revealed majority of the genomes (36) classified as B lineage, where 2 genomes were from B.6 lineage, 5 genomes from B.1 ancestral lineage and remaining from B.1 sub-lineages. It was noteworthy that three clusters of B.1 sub-lineages were observed, including B.1.36 lineage (10 genomes), B.1.160 lineage (11 genomes), and B.1.255 lineage (5 genomes), which represent independent events of SARS-CoV-2 transmission within the city. The sub-lineage B.1.36 had higher representation from the Asian countries and the UK, B.1.160 correspond to the European countries with highest representation from the UK, Denmark, and lesser representation from India, Saudi Arabia, France and Switzerland, and the third sub-lineage (B.1.255) correspond to the USA. Collectively, our study provides meaningful insight into the evolution of SARS-CoV-2 lineages in spatio-temporal local transmission during the first wave of the pandemic.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Virus Research
37 papers in training set
Top 0.1%
12.5%
2
Genomics
64 papers in training set
Top 0.1%
7.8%
3
Frontiers in Microbiology
427 papers in training set
Top 1%
6.7%
4
International Journal of Infectious Diseases
129 papers in training set
Top 0.2%
6.2%
5
Gene Reports
14 papers in training set
Top 0.1%
5.5%
6
Frontiers in Genetics
230 papers in training set
Top 0.5%
5.4%
7
Journal of Medical Virology
140 papers in training set
Top 0.6%
4.0%
8
Viruses
332 papers in training set
Top 1%
4.0%
50% of probability mass above
9
Infection, Genetics and Evolution
42 papers in training set
Top 0.2%
4.0%
10
Scientific Reports
3612 papers in training set
Top 38%
2.8%
11
Pathogens
56 papers in training set
Top 0.2%
2.6%
12
PLOS ONE
5266 papers in training set
Top 41%
2.6%
13
PeerJ
308 papers in training set
Top 4%
2.4%
14
Gene
46 papers in training set
Top 0.6%
2.1%
15
Frontiers in Cellular and Infection Microbiology
109 papers in training set
Top 1%
1.9%
16
Heliyon
152 papers in training set
Top 3%
1.7%
17
Frontiers in Public Health
148 papers in training set
Top 4%
1.7%
18
BMC Genomics
406 papers in training set
Top 5%
1.5%
19
Vaccines
198 papers in training set
Top 3%
1.1%
20
Archives of Virology
15 papers in training set
Top 0.2%
1.1%
21
Journal of Infection
78 papers in training set
Top 1%
1.0%
22
International Journal of Biological Macromolecules
76 papers in training set
Top 2%
1.0%
23
Antiviral Research
50 papers in training set
Top 0.6%
1.0%
24
Genes
144 papers in training set
Top 3%
1.0%
25
eLife
5828 papers in training set
Top 63%
0.9%
26
BMC Molecular and Cell Biology
16 papers in training set
Top 0.2%
0.8%
27
mSystems
394 papers in training set
Top 6%
0.8%
28
Transboundary and Emerging Diseases
37 papers in training set
Top 0.6%
0.8%
29
BMC Infectious Diseases
133 papers in training set
Top 5%
0.8%
30
Wellcome Open Research
67 papers in training set
Top 2%
0.6%