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

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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In the last few months, there has been a global catastrophic outbreak of severe acute respiratory syndrome disease caused by the novel coronavirus SARS-CoV-2 affecting millions of people worldwide. Early diagnosis and isolation are key to contain the rapid spread of the virus. Towards this goal, we report a simple, sensitive and rapid method to detect the virus using a targeted mass spectrometric approach, which can directly detect the presence of virus from naso-oropharyngeal swabs. Using a multiple reaction monitoring we can detect the presence of two peptides specific to SARS-CoV-2 in a 2.3 min gradient run with 100% specificity and 90.5% sensitivity when compared to RT-PCR. Importantly, we further show that these peptides could be detected even in the patients who have recovered from the symptoms and have tested negative for the virus by RT-PCR highlighting the sensitivity of the technique. This method has the translational potential of in terms of the rapid diagnostics of symptomatic and asymptomatic COVID-19 and can augment current methods available for diagnosis of SARS-CoV-2.

Background: Association studies are an essential part of modern plant breeding, but are limited for polyploid crops. The increased number of possible genotype classes complicates the differentiation between them. Available methods are limited with respect to the ploidy level or data producing technologies. While genotype classification is an established noise reduction step in diploids, it gains complexity with increasing ploidy levels. Eventually, the errors produced by misclassifications exceed the benefits of genotype classes. Alternatively, continuous genotype values can be used for association analysis in higher polyploids. We associated continuous genotypes to three different traits and compared the results to the output of the genotype caller SuperMASSA. Linear, Bayesian and partial least squares regression were applied, to determine if the use of continuous genotypes is limited to a specific method. A disease, a flowering and a growth trait with h 2 of 0.51, 0.78 and 0.91 were associated with a hexaploid chrysanthemum genotypes. The data set consisted of 55,825 probes and 228 samples. Results: We were able to detect associating probes using continuous genotypes for multiple traits, using different regression methods. The identified probe sets were overlapping, but not identical between the methods. Baysian regression was the most restrictive method, resulting in ten probes for one trait and none for the others. Linear and partial least squares regression led to numerous associating probes. Association based on genotype classes resulted in similar values, but missed several significant probes. A simulation study was used to successfully validate the number of associating markers. Conclusions: Association of various phenotypic traits with continuous genotypes is successful with both uni-and multivariate regression methods. Genotype calling does not improve the association and shows no advantages in this study. Instead, use of continuous genotypes simplifies the analysis, saves computational time and results more potential markers.

Background: India first detected SARS-CoV-2, causal agent of COVID-19 in late January 2020, imported from Wuhan, China. From March 2020 onwards, the importation of cases from countries in the rest of the world followed by seeding of local transmission triggered further outbreaks in India. Methods: We used ARTIC protocol-based tiling amplicon sequencing of SARS-CoV-2 (n=104) from different states of India using a combination of MinION and MinIT sequencing from Oxford Nanopore Technology to understand how introduction and local transmission occurred. Results: The analyses revealed multiple introductions of SARS-CoV-2 genomes, including the A2a cluster from Europe and the USA, A3 cluster from Middle East and A4 cluster (haplotype redefined) from Southeast Asia (Indonesia, Thailand and Malaysia) and Central Asia (Kyrgyzstan). The local transmission and persistence of genomes A4, A2a and A3 was also observed in the studied locations. The most prevalent genomes with patterns of variance (confined in a cluster) remain unclassified, and are here proposed as A4-clade based on its divergence within the A cluster. Conclusions: The viral haplotypes may link their persistence to geo-climatic conditions and host response. Multipronged strategies including molecular surveillance based on real-time viral genomic data is of paramount importance for a timely management of the pandemic.

Independent outbreaks of dengue virus (DENV) infection and sporadic cases of chikungunya virus (CHIKV) have been recorded in the metropolitan city of Delhi on several occasions in the past. However, during a recent 2010 arboviral outbreak in Delhi many cases turned negative for DENV. This prompted us to use duplex reverse transcriptase-polymerase chain reaction (D-RT-PCR) to establish the aetiology of dengue/chikungunya through sequencing of CprM and E1 genes of dengue and chikungunya viruses. Interestingly, for the first time, both DENV and CHIKV co-circulated simultaneously and in equally dominant proportion during the post-monsoon period of 2010. DENV-1 genotype III and the East Central South African genotype of CHIKV were associated with post-monsoon spread of these viruses.