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1.
Viruses ; 13(11)2021 11 08.
Article in English | MEDLINE | ID: covidwho-1512695

ABSTRACT

The COVID-19 pandemic is a global challenge that impacted 200+ countries. India ranks in the second and third positions in terms of number of reported cases and deaths. Being a populous country with densely packed cities, SARS-CoV-2 spread exponentially. India sequenced ≈0.14% isolates from confirmed cases for pandemic surveillance and contributed ≈1.58% of complete genomes sequenced globally. This study was designed to map the circulating lineage diversity and to understand the evolution of SARS-CoV-2 in India using comparative genomics and population genetics approaches. Despite varied sequencing coverage across Indian States and Union Territories, isolates belonging to variants of concern (VoC) and variants of interest (VoI) circulated, persisted, and diversified during the first seventeen months of the pandemic. Delta and Kappa lineages emerged in India and spread globally. The phylogenetic tree shows lineage-wise monophyletic clusters of VoCs/VoIs and diversified tree topologies for non-VoC/VoI lineages designated as 'Others' in this study. Evolutionary dynamics analyses substantiate a lack of spatio-temporal clustering, which is indicative of multiple global and local introductions. Sites under positive selection and significant variations in spike protein corroborate with the constellation of mutations to be monitored for VoC/VoI as well as substitutions that are characteristic of functions with implications in virus-host interactions, differential glycosylation, immune evasion, and escape from neutralization.


Subject(s)
COVID-19/virology , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/genetics , COVID-19/epidemiology , Evolution, Molecular , Genome, Viral , Humans , India/epidemiology , Models, Molecular , Mutation , Phylogeny , Protein Conformation , Protein Domains , SARS-CoV-2/isolation & purification , Selection, Genetic , Spike Glycoprotein, Coronavirus/chemistry , Whole Genome Sequencing
2.
J Med Virol ; 92(10): 1932-1937, 2020 10.
Article in English | MEDLINE | ID: covidwho-935081

ABSTRACT

Coronavirus disease 2019 emerged as the first example of "Disease X", a hypothetical disease of humans caused by an unknown infectious agent that was named as novel coronavirus and subsequently designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The origin of the outbreak at the animal market in Wuhan, China implies it as a case of zoonotic spillover. The study was designed to understand evolution of Betacoronaviruses and in particular diversification of SARS-CoV-2 using RNA dependent RNA polymerase (RdRp) gene, a stable genetic marker. Phylogenetic and population stratification analyses were carried out using maximum likelihood and Bayesian methods, respectively. Molecular phylogeny using RdRp showed that SARS-CoV-2 isolates cluster together. Bat-CoV isolate RaTG13 and Pangolin-CoVs are observed to branch off prior to SARS-CoV-2 cluster. While SARS-CoV form a single cluster, Bat-CoVs form multiple clusters. Population-based analyses revealed that both SARS-CoV-2 and SARS-CoV form separate clusters with no admixture. Bat-CoVs were found to have single and mixed ancestry and clustered as four sub-populations. Population-based analyses of Betacoronaviruses using RdRp revealed that SARS-CoV-2 is a homogeneous population. SARS-CoV-2 appears to have evolved from Bat-CoV isolate RaTG13, which diversified from a common ancestor from which Pangolin-CoVs have also evolved. The admixed Bat-CoV sub-populations indicate that bats serve as reservoirs harboring virus ensembles that are responsible for zoonotic spillovers such as SARS-CoV and SARS-CoV-2. The extent of admixed isolates of Bat-CoVs observed in population diversification studies underline the need for periodic surveillance of bats and other animal reservoirs for potential spillovers as a measure towards preparedness for emergence of zoonosis.


Subject(s)
Coronavirus RNA-Dependent RNA Polymerase/genetics , Evolution, Molecular , SARS-CoV-2/genetics , Animals , Bayes Theorem , Chiroptera/virology , Genetics, Population , Humans , Likelihood Functions , Pangolins/virology , Phylogeny , Zoonoses/virology
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