After escaping relatively unscathed during the first wave of the COVID-19 pandemic, India witnessed a ferocious second COVID-19 wave, starting in March 2021 and accounting for about half of global cases by the first week of May. SARS-CoV-2 had spread widely throughout India in the first wave, with the third national serosurvey in January 2021 finding that 21.4% of adults and 25.3% of 10-to 17-year-old adolescents were seropositive (1). Delhi, the national capital, was not included in the national serosurvey but had undergone multiple periods of high transmission in 2020 (Fig. 1A). In a district-wise stratified serosurvey conducted by the Delhi Government in January 2021, overall seropositivity was reported to be 56.1% (95% CI, 55.5-56.8%), ranging from 49.1% to 62.2% across 11 districts (2). This was expected to confer some protection from future outbreaks.Despite high seropositivity, Delhi was amongst the most affected cities during the second wave. The rise in new cases was exceptionally rapid in April, going from approximately 2000 to 20,000 between 31 March and 16 April. This was accompanied by a rapid rise in hospitalizations and ICU admissions (Fig. 1B). In this emergency situation with saturated bed occupancy by 12 April, major private hospitals were declared by the state as full COVID care-only and senior medical students, including from alternative medicine branches, were pressed into service (3). Deaths rose proportionately (Fig. 1C) and the case-fatality ratio (CFR), estimated as the scaling factor between time-advanced cases and deaths (Fig. 1D), was stable (mean, SD; 1.9, 0.3%). Population spread of SARS-CoV-2 is underestimated by test positive cases alone (1, 2). To better understand the degree of spread and the factors leading to the unexpectedly severe outbreak, we used all available data including testing, sequencing, serosurveys, and serially followed cohorts.In the absence of finely resolved or serial data from national and state surveys, we focused on data for Delhi participants of a national serosurvey of Council of Scientific and

With the advent of next-generation sequencing, large-scale initiatives for mining whole genomes and exomes have been employed to better understand global or population-level genetic architecture. India encompasses more than 17% of the world population with extensive genetic diversity, but is under-represented in the global sequencing datasets. This gave us the impetus to perform and analyze the whole genome sequencing of 1029 healthy Indian individuals under the pilot phase of the ‘IndiGen’ program. We generated a compendium of 55,898,122 single allelic genetic variants from geographically distinct Indian genomes and calculated the allele frequency, allele count, allele number, along with the number of heterozygous or homozygous individuals. In the present study, these variants were systematically annotated using publicly available population databases and can be accessed through a browsable online database named as ‘IndiGenomes’ http://clingen.igib.res.in/indigen/. The IndiGenomes database will help clinicians and researchers in exploring the genetic component underlying medical conditions. Till date, this is the most comprehensive genetic variant resource for the Indian population and is made freely available for academic utility. The resource has also been accessed extensively by the worldwide community since it's launch.

In April 2021, after successfully enduring three waves of the SARS-CoV2 pandemic in 2020, and having reached population seropositivity of about 50%, Delhi, the national capital of India was overwhelmed by the fourth wave. Here, we trace viral, host, and social factors contributing to the scale and exponent of the fourth wave, when compared to preceding waves, in an epidemiological context. Genomic surveillance data from Delhi and surrounding states shows an early phase of the upsurge driven by the entry of the more transmissible B.1.1.7 variant of concern (VOC) into the region in January, with at least one B.1.1.7 super spreader event in February 2021, relatable to known mass gatherings over this period. This was followed by seeding of the B.1.617 VOC, which too is highly transmissible, with rapid expansion of B.1.617.2 sub-lineage outpacing all other lineages. This unprecedented growth of cases occurred in the background of high seropositivity, but with low median neutralizing antibody levels, in a serially sampled cohort. Vaccination breakthrough cases over this period were noted, disproportionately related to VOC in sequenced cases, but usually mild. We find that this surge of SARS-CoV2 infections in Delhi is best explained by the introduction of a new highly transmissible VOC, B.1.617.2, with likely immune-evasion properties; insufficient neutralizing immunity, despite high seropositivity; and social behavior that promoted transmission.

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This is the first and largest genetic map the DPYD variants associated with adverse drug reaction to 5-FU in south Asian population. Our study highlights ethnic differences in allelic frequencies.

Sequencing of SARS-CoV-2 genomes is crucial for understanding the genetic epidemiology of the COVID-19 pandemic. It is also critical for understanding the evolution of the virus and also for the rapid development of diagnostic tools. The present protocol is a modification of the Illumina COVIDSeq test. We describe an amplicon-based next-generation sequencing approach with short turnaround time, adapted for bench-top sequencers like MiSeq, iSeq and MiniSeq.

Emerging reports of SARS-CoV-2 breakthrough infections entail methodical genomic surveillance for determining the efficacy of vaccines. This study elaborates genomic analysis of isolates from breakthrough infections following vaccination with AZD1222/Covishield and BBV152/Covaxin. Variants of concern B.1.617.2 and B.1.1.7 responsible for cases surge in April-May 2021 in Delhi, were the predominant lineages among breakthrough infections.