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COVID-19 infection and transmission includes complex sequence diversity.

Ernest R Chan1,2, Lucas D Jones3, Marlin Linger4

  • 1Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America.

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SARS-CoV-2 infections are complex mixtures of diverse viral sequences, not just a single consensus. Monitoring this viral heterogeneity is crucial for understanding COVID-19 evolution and transmission dynamics.

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Area of Science:

  • Virology
  • Genomics
  • Epidemiology

Background:

  • Whole genome sequencing of SARS-CoV-2 tracks viral evolution and polymorphisms during the COVID-19 pandemic.
  • Previous studies often reported a single consensus sequence, potentially overlooking intra-host viral diversity.

Purpose of the Study:

  • To characterize the sequence diversity within individual SARS-CoV-2 infections.
  • To assess the transmission of viral sequence heterogeneity.
  • To evaluate the impact of reporting methods on understanding viral evolution.

Main Methods:

  • Whole genome sequencing of SARS-CoV-2 from over 360 patients across multiple variant surges (Alpha, Delta).
  • Analysis of sequence polymorphisms and intra-host diversity.
  • Comparison of consensus reporting versus comprehensive sequence variation reporting.

Main Results:

  • Significantly increasing SARS-CoV-2 sequence diversity observed throughout the pandemic.
  • Frequent occurrence of multiple biallelic sequence polymorphisms in all infections, indicating heterogeneous mixtures.
  • Majority consensus reporting under-reported sequence variation in all tested samples.
  • Efficient transmission of sequence heterogeneity from donors to recipients.
  • Minority alleles identified in earlier infections are now lineage-defining SNPs in Omicron variants (BA.1, BA.2).

Conclusions:

  • SARS-CoV-2 infections exhibit significant intra-host sequence heterogeneity.
  • Current consensus reporting methods underestimate viral diversity and its role in evolution.
  • Comprehensive monitoring and reporting of infection complexity are essential for understanding SARS-CoV-2 transmission and the emergence of new variants.