Phylogenomics and Phylodynamics of SARS-CoV-2 Genomes Retrieved From India

Farah, Sameera; Atkulwar, Ashwin; Praharaj, Manas Ranjan; Khan, Raja Ishaq Nabi; Gandham, Ravikumar; Baig, Mumtaz

doi:10.2217/fvl-2020-0243

Cited by 7 publications

(4 citation statements)

References 31 publications

(16 reference statements)

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“…To set the time scale prior for the dataset, we used a constrained evolution rate with a Log‐normal prior averaged at 10 −3 by substitution per site per year. We performed a phylogenetic Bayesian analysis using the Relaxed Clock Log‐Normal molecular clock model and selected the Coalescent Bayesian Skyline as the model of population size and growth according to the relevant studies 26–28 . The whole‐genome sequence and the sequence coding spike protein sequence (S gene) were separately analyzed by MCMC to calculate the mutation rate, with a length of 4 × 10 8 steps, sampling every 4 × 10 4 steps.…”

Section: Methodsmentioning

confidence: 99%

“…We performed a phylogenetic Bayesian analysis using the Relaxed Clock Log-Normal molecular clock model and selected the Coalescent Bayesian Skyline as the model of population size and growth according to the relevant studies. [26][27][28] The whole-genome sequence and the sequence coding spike protein sequence (S gene) were separately analyzed by MCMC to calculate the mutation rate, with a length of 4 × 10 8 steps, sampling every 4 × 10 4 steps. The convergence of all the parameters (ESS >200, burn-in 10%) was verified with Tracer v1.7.1.…”

Section: Sequence Alignment and Phylodynamics Analysismentioning

confidence: 99%

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Molecular evolutionary characteristics of SARS‐CoV‐2 emerging in the United States

Wang

Cai

et al. 2021

Journal of Medical Virology

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SARS-CoV-2 is a newly discovered beta coronavirus at the end of 2019, which is highly pathogenic and poses a serious threat to human health. In this paper, 1875 SARS-CoV-2 whole genome sequences and the sequence coding spike protein (S gene) sampled from the United States were used for bioinformatics analysis to study the molecular evolutionary characteristics of its genome and spike protein. The MCMC method was used to calculate the evolution rate of the whole genome sequence and the nucleotide mutation rate of the S gene. The results showed that the nucleotide mutation rate of the whole genome was 6.677 × 10 −4 substitution per site per year, and the nucleotide mutation rate of the S gene was 8.066 × 10 −4 substitution per site per year, which was at a medium level compared with other RNA viruses. Our findings confirmed the scientific hypothesis that the rate of evolution of the virus gradually decreases over time. We also found 13 statistically significant positive selection sites in the SARS-CoV-2 genome. In addition, the results showed that there were 101 nonsynonymous mutation sites in the amino acid sequence of S protein, including seven putative harmful mutation sites. This paper has preliminarily clarified the evolutionary characteristics of SARS-CoV-2 in the United States, providing a scientific basis for future surveillance and prevention of virus variants.

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Section: Methodsmentioning

confidence: 99%

Section: Sequence Alignment and Phylodynamics Analysismentioning

confidence: 99%

Molecular evolutionary characteristics of SARS‐CoV‐2 emerging in the United States

Wang

Cai

et al. 2021

Journal of Medical Virology

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“…We propose that the information obtained from such networks can be explored in contact tracing, filling gaps, and community transmission in India. When we compared this RM with the first phylogenetic network published by [20] Forster et al 2020 at the onset of the epidemic and with our own previously published MJ network [21], significant differences were observed. In comparison with our previously published MJ, RM exhibits a more distinct and faster evolution of variant in human hosts, evident in the emergence of more variants/haplogroups (colored circles) and the accumulation of large number of mutations across connecting lineages.…”

Section: Discussionmentioning

confidence: 99%

Analyses of Omicron genomes from India reveal BA.2 as a more transmissible variant

Atkulwar¹,

Rehman²,

Yashal

et al. 2022

Preprint

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This is the first study on omicron genomes from India to focus on phylodynamics and phylogenomics trait to provide an insight into the evolution of omicron variants. We analyzed 564 genomes deposited to GISAID database from various states of India. Pangolin COVID-19 Lineage Assigner tool was used to determine lineage assignment of all retrieved genomes. A Maximum likelihood (MLE) tree construction further confirms the separation of genomes into two distinct clades, BA. 1. and BA. 2. A very high reproduction number (R0) of 2.445 was estimated for the lineage BA.2. The highest R0 value in Telangana confirms the prevalence of lineage BA.2 in the state. Construction of the Reduced Median (RM) network shows evolution of some autochthonous haplogroups and haplotypes, which further supports the rapid evolution of omicron as compared to its previous variants. Phylogenomic analyses using maximum likelihood (ML) and RM show the potential for the emergence of sub-sublineages and novel haplogroups respectively. Due to the recombinant property and high transmissibility of omicron virus, we suggest continuous and more widespread genome sequencing in all states of India to track evolution of SARS-CoV-2 in real time.

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“…We have previously used and extended these well-established methods to estimating HIV transmission and unknown sources of infection in a population [ 14 ]. Moreover, these tools have been applied to infer the transmission of SARS-CoV-2 [ 15 – 17 ]. In this study, we fine-tuned these tools and extended the analyses to infer both transmission networks and infer the presence of unsampled sources of infection.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing SARS-CoV-2 infection dynamics through the phylogenetic inference of unsampled sources of infection

et al. 2021

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The COVID-19 pandemic has illustrated the importance of infection tracking. The role of asymptomatic, undiagnosed individuals in driving infections within this pandemic has become increasingly evident. Modern phylogenetic tools that take into account asymptomatic or undiagnosed individuals can help guide public health responses. We finetuned established phylogenetic pipelines using published SARS-CoV-2 genomic data to examine reasonable estimate transmission networks with the inference of unsampled infection sources. The system utilised Bayesian phylogenetics and TransPhylo to capture the evolutionary and infection dynamics of SARS-CoV-2. Our analyses gave insight into the transmissions within a population including unsampled sources of infection and the results aligned with epidemiological observations. We were able to observe the effects of preventive measures in Canada’s “Atlantic bubble” and in populations such as New York State. The tools also inferred the cross-species disease transmission of SARS-CoV-2 transmission from humans to lions and tigers in New York City’s Bronx Zoo. These phylogenetic tools offer a powerful approach in response to both the COVID-19 and other emerging infectious disease outbreaks.

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Phylogenomics and Phylodynamics of SARS-CoV-2 Genomes Retrieved From India

Cited by 7 publications

References 31 publications

Molecular evolutionary characteristics of SARS‐CoV‐2 emerging in the United States

Molecular evolutionary characteristics of SARS‐CoV‐2 emerging in the United States

Analyses of Omicron genomes from India reveal BA.2 as a more transmissible variant

Reconstructing SARS-CoV-2 infection dynamics through the phylogenetic inference of unsampled sources of infection

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