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). 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 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 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) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability 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.

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Since its zoonotic transmission in the human host, the SARS-CoV-2 virus has infected millions and has diversified extensively. A hallmark feature of viral system survival is their continuous evolution and adaptation within the host. RNA editing via APOBEC and ADAR family of enzymes has been recently implicated as the major driver of intra-host variability of the SARS-CoV-2 genomes. Analysis of the intra-host single-nucleotide variations (iSNVs) in SARS-CoV-2 genomes at spatio-temporal scales can provide insights on the consequence of RNA editing on the establishment, spread and functional outcomes of the virus. In this study, using 1,347 transcriptomes of COVID-19 infected patients across various populations, we find variable prevalence of iSNVs with distinctly higher levels in Indian population. Our results also suggest that iSNVs can likely establish variants in a population. These iSNVs may also contribute to key structural and functional changes in the Spike protein that confer antibody resistance.

Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed “Prakriti”. It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy Prakriti stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 (IFIT5) and rs941590 (SERPINA10) that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.

The recent release of SARS-CoV-2 genomic data from several countries has provided clues into the potential antigenic drift of the coronavirus population. In particular, the genomic instability observed in the spike protein necessitates immediate action and further exploration in the context of viral-host interactions. Here we dynamically track 3,11,795 genome sequences of spike protein, which comprises 2,584 protein mutations. We reveal mutational genomic ensemble at different timing and geographies, that evolves on four distinct residues. In addition to the well-established N501 mutational cluster, we detect the presence of three novel clusters, namely A222, N439, and S477. The robust examination of structural features from 44 known cryo-EM structures showed that the virus is deploying many mutations within these clusters on structurally heterogeneous regions. One such dominant variant D614G was also simulated using molecular dynamics simulations and, as compared to wild-type, we found higher stability with human ACE2 receptor. There is also a significant overlap of mutational clusters on known epitopes, indicating putative interference with antibody binding. Thus, we propose that the resulting coaxility of mutational clusters is the most efficient feature of SARS-CoV-2 evolution and provides precise mutant combinations that can enable future vaccine re-positioning.