The SARS-CoV-2 B.1.617.2 (Delta) variant was first identified in the state of Maharashtra in late 2020 and spread throughout India, outcompeting pre-existing lineages including B.1.617.1 (Kappa) and B.1.1.7 (Alpha) 1 . In vitro, B.1.617.2 is 6-fold less sensitive to serum neutralising antibodies from recovered individuals, and 8-fold less sensitive to vaccine-elicited antibodies as compared to wild type (WT) Wuhan-1 bearing D614G. Serum neutralising titres against B.1.617.2 were lower in ChAdOx-1 versus BNT162b2 vaccinees. B.1.617.2 spike pseudotyped viruses exhibited compromised sensitivity to monoclonal antibodies against the receptor binding domain (RBD) and N-terminal domain (NTD). B.1.617.2 demonstrated higher replication efficiency in both airway organoid and human airway epithelial systems compared to B.1.1.7, associated with B.1.617.2 spike in a predominantly cleaved state compared to B.1.1.7. The B.1.617.2 spike protein was able to mediate highly efficient syncytium formation that was less sensitive to inhibition by neutralising antibody as compared to WT spike. Additionally we observed that B.1.617.2 had higher replication and spike mediated entry as compared to B.1.617.1, potentially explaining B.1.617.2 dominance. In an analysis of over 130 SARS-CoV-2 infected healthcare workers across three centres in India during a period of mixed lineage circulation, we observed reduced ChAdOx-1 vaccine effectiveness against B.1.617.2 relative to non-B.1.617.2, with the caveat of possible residual confounding. Compromised vaccine efficacy against the highly fit and immune evasive B.1.617.2 Delta variant warrants continued infection control measures in the post-vaccination era. India's first wave of SARS-CoV-2 infections in mid-2020 was relatively mild and was controlled by a nationwide lockdown. Since easing of restrictions, India has seen expansion in cases of COVID-19 since March

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

Since its emergence as a pneumonia-like outbreak in the Chinese city of Wuhan in late 2019, the novel coronavirus disease COVID-19 has spread widely to become a global pandemic. The first case of COVID-19 in India was reported on 30 January 2020 and since then it has affected more than ten million people and resulted in around 150,000 deaths in the country. Over time, the viral genome has accumulated mutations as it passes through its human hosts, a common evolutionary mechanism found in all microorganisms. This has implications for disease surveillance and management, vaccines and therapeutics, and the emergence of reinfections. Sequencing the viral genome can help monitor these changes and provides an extraordinary opportunity to understand the genetic epidemiology and evolution of the virus as well as tracking its spread in a population. Here we review the past year in the context of the phylogenetic analysis of variants isolated over the course of the pandemic in India and highlight the importance of continued sequencing-based surveillance in the country.

Background Microsatellites, or Simple Sequence Repeats (SSRs), are short tandem repeats of 1–6 nt motifs present in all genomes. Emerging evidence points to their role in cellular processes and gene regulation. Despite the huge resource of genomic information currently available, SSRs have been studied in a limited context and compared across relatively few species. Results We have identified ~ 685 million eukaryotic microsatellites and analyzed their genomic trends across 15 taxonomic subgroups from protists to mammals. The distribution of SSRs reveals taxon-specific variations in their exonic, intronic and intergenic densities. Our analysis reveals the differences among non-related species and novel patterns uniquely demarcating closely related species. We document several repeats common across subgroups as well as rare SSRs that are excluded almost throughout evolution. We further identify species-specific signatures in pathogens like Leishmania as well as in cereal crops, Drosophila , birds and primates. We also find that distinct SSRs preferentially exist as long repeating units in different subgroups; most unicellular organisms show no length preference for any SSR class, while many SSR motifs accumulate as long repeats in complex organisms, especially in mammals. Conclusions We present a comprehensive analysis of SSRs across taxa at an unprecedented scale. Our analysis indicates that the SSR composition of organisms with heterogeneous cell types is highly constrained, while simpler organisms such as protists, green algae and fungi show greater diversity in motif abundance, density and GC content. The microsatellite dataset generated in this work provides a large number of candidates for functional analysis and for studying their roles across the evolutionary landscape. Electronic supplementary material The online version of this article (10.1186/s12864-019-5516-5) contains supplementary material, which is available to authorized users.

Motivation From an isolated epidemic, COVID-19 has now emerged as a global pandemic. The availability of genomes in the public domain following the epidemic provides a unique opportunity to understand the evolution and spread of the SARS-CoV-2 virus across the globe. Results We performed whole-genome sequencing of 303 Indian isolates, and analyzed them in the context of publicly available data from India. We describe a distinct phylogenetic cluster (Clade I/A3i) of SARS-CoV-2 genomes from India, which encompasses 22% of all genomes deposited in the public domain from India. Globally approximately 2% of genomes, which till date could not be mapped to any distinct known cluster fall in this clade. Conclusions The cluster is characterized by a core set of 4 genetic variants and has a nucleotide substitution rate of 1.1 x 10 -3 variants per site per year, lower than the prevalent A2a cluster. Epidemiological assessments suggest that the common ancestor emerged at the end of January 2020 and possibly resulted in an outbreak followed by countrywide spread. To the best of our knowledge, this is the first comprehensive study characterizing this cluster of SARS-CoV-2 in India.