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Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections.

Ke LiChrispin ChaguzaJulian StampYi Ting ChewNicholas F G ChenDavid FergusonSameer PandyaNick KerantzasWade Schulznull nullAnne M HahnC Brandon OgbunugaforVirginia E PitzerLorin CrawfordDaniel M WeinbergerNathan D Grubaugh
Published in: PLoS computational biology (2024)
Significant variations have been observed in viral copies generated during SARS-CoV-2 infections. However, the factors that impact viral copies and infection dynamics are not fully understood, and may be inherently dependent upon different viral and host factors. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the impact of virus genetic variation on changes in viral copies adjusted for host age and vaccination status. Using a genome-wide association study (GWAS) approach, we identified multiple single-nucleotide polymorphisms (SNPs) corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. We further applied a marginal epistasis test to detect interactions among SNPs and identified multiple pairs of substitutions located in the spike gene that have non-linear effects on viral copies. We also analyzed the temporal patterns and found that SNPs associated with increased viral copies were predominantly observed in Delta and Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were only observed in infections with Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes that are worth further exploration. We argue that this approach can be used more broadly across pathogens to characterize emerging variants and monitor therapeutic interventions.
Keyphrases
  • sars cov
  • respiratory syndrome coronavirus
  • genome wide association study
  • genome wide
  • gene expression
  • transcription factor
  • amino acid
  • molecular dynamics simulations
  • african american
  • single molecule
  • drug induced