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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21258076

RESUMO

Delhi, the national capital of India, has experienced multiple SARS-CoV-2 outbreaks in 2020 and reached a population seropositivity of over 50% by 2021. During April 2021, the city became overwhelmed by COVID-19 cases and fatalities, as a new variant B.1.617.2 (Delta) replaced B.1.1.7 (Alpha). A Bayesian model explains the growth advantage of Delta through a combination of increased transmissibility and partial reduction of immunity elicited by prior infection (median estimates; x1.5-fold, 20% reduction). Seropositivity of an employee and family cohort increased from 42% to 86% between March and July 2021, with 27% reinfections, as judged by increased antibody concentration after previous decline. The likely high transmissibility and partial evasion of immunity by the Delta variant contributed to an overwhelming surge in Delhi. One-Sentence SummaryDelhi experienced an overwhelming surge of COVID-19 cases and fatalities peaking in May 2021 as the highly transmissible and immune evasive Delta variant replaced the Alpha variant.

2.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-427775

RESUMO

Coronavirus disease (COVID-19) emerged from a city in China and has now spread as a global pandemic affecting millions of individuals. The causative agent, SARS-CoV-2 is being extensively studied in terms of its genetic epidemiology using genomic approaches. Andhra Pradesh is one of the major states of India with the third-largest number of COVID-19 cases with limited understanding of its genetic epidemiology. In this study, we have sequenced 293 SARS-CoV-2 genome isolates from Andhra Pradesh with a mean coverage of 13,324X. We identified 564 high-quality SARS-CoV-2 variants, out of which 15 are novel. A total of 18 variants mapped to RT-PCR primer/probe sites, and 4 variants are known to be associated with an increase in infectivity. Phylogenetic analysis of the genomes revealed the circulating SARS-CoV-2 in Andhra Pradesh majorly clustered under the clade A2a (94%), while 6% fall under the I/A3i clade, a clade previously defined to be present in large numbers in India. To the best of our knowledge, this is the most comprehensive genetic epidemiological analysis performed for the state of Andhra Pradesh.

3.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-424332

RESUMO

Many antibody and immune escape variants in SARS-CoV-2 are now documented in literature. The availability of SARS-CoV-2 genome sequences enabled us to investigate the occurrence and genetic epidemiology of the variants globally. Our analysis suggests that a number of genetic variants associated with immune escape have emerged in global populations.

4.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-417519

RESUMO

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying Variants Of Concern (VOC). Besides, viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host Single Nucleotide Variations (iSNVs). Analysing 1, 347 samples collected till June 2020, we recorded 18, 146 iSNV sites throughout the SARS-CoV-2 genome. Both, mutations in RdRp as well as APOBEC and ADAR mediated RNA editing seem to contribute to the differential prevalence of iSNVs in hosts. Noteworthy, 41% of all unique iSNVs were reported as SNVs by 30th September 2020 in samples submitted to GISAID, which increased to [~]80% by 30th June 2021. Following this, analysis of another set of 1, 798 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) variations appeared as iSNVs before getting fixed in the population. We also observe hyper-editing events at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC="FIGDIR/small/417519v3_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@12b6ac2org.highwire.dtl.DTLVardef@16df897org.highwire.dtl.DTLVardef@dbbec2org.highwire.dtl.DTLVardef@c8de14_HPS_FORMAT_FIGEXP M_FIG C_FIG

5.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-289892

RESUMO

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. Genomic approaches have been extensively used to understand the evolution and epidemiology of SARS-CoV-2 across the world. Kerala is a unique state in India well connected with the rest of the world through a large number of expatriates, trade, and tourism. The first case of COVID-19 in India was reported in Kerala in January 2020, during the initial days of the pandemic. The rapid increase in the COVID-19 cases in the state of Kerala has necessitated the understanding of the genetic epidemiology of circulating virus, evolution, and mutations in SARS-CoV-2. We sequenced a total of 200 samples from patients at a tertiary hospital in Kerala using COVIDSeq protocol at a mean coverage of 7,755X. The analysis identified 166 unique high-quality variants encompassing 4 novel variants and 89 new variants identified for the first time in SARS-CoV-2 samples isolated from India. Phylogenetic and haplotype analysis revealed that the circulating population of the virus was dominated (94.6% of genomes) by three distinct introductions followed by local spread, apart from identifying polytomies suggesting recent outbreaks. The genomes formed a monophyletic distribution exclusively mapping to the A2a clade. Further analysis of the functional variants revealed two variants in the S gene of the virus reportedly associated with increased infectivity and 5 variants that mapped to five primer/probe binding sites that could potentially compromise the efficacy of RT-PCR detection. To the best of our knowledge, this is the first and most comprehensive report of genetic epidemiology and evolution of SARS-CoV-2 isolates from Kerala.

6.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-242677

RESUMO

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.

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