Intra-host site-specific polymorphisms of SARS-CoV-2 is consistent across multiple samples and methodologies

  1. Rebecca Rose
  2. David J. Nolan
  3. Samual Moot
  4. Amy Feehan
  5. Sissy Cross
  6. Julia Garcia-Diaz
  7. Susanna L. Lamers

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Abstract

Despite the potential relevance to clinical outcome, intra-host dynamics of SARS-CoV-2 are unclear. Here, we quantify and characterize intra-host variation in SARS-CoV-2 raw sequence data uploaded to SRA as of 14 April 2020, and compare results between two sequencing methods (amplicon and RNA-Seq). Raw fastq files were quality filtered and trimmed using Trimmomatic, mapped to the WuhanHu1 reference genome using Bowtie2, and variants called with bcftools mpileup . To ensure sufficient coverage, we only included samples with 10X coverage for >90% of the genome (n=406 samples), and only variants with a depth >=10. Derived (i.e. non-reference) alleles were found at 408 sites. The number of polymorphic sites (i.e. sites with multiple alleles) within samples ranged from 0-13, with 72% of samples (295/406) having at least one polymorphic site. Correlation between number of polymorphic sites and coverage was very low for both sequencing methods (R 2 < 0.1, p < 0.05). Polymorphisms were observed >1 sample at 66 sites (range: 2-38 samples). The minor allele frequency (MAF) at each shared polymorphic site was 0.03% - 48.5%. 33/66 sites occurred in ORF1a1b, and 37/66 changes were non-synonymous. At 10/66 sites, derived alleles were found in samples sequenced using both methods. Polymorphic amplicon samples were found at 10/10 positions, while polymorphic RNA-Seq samples were found at 7/10 positions. In conclusion, our results suggest that intra-host variation is prevalent among clinical samples. While mutations resulting from amplification and/or sequencing errors cannot be excluded, the observation of shared polymorphic sites with high MAF across multiple samples and sequencing methods is consistent with true underlying variation. Further investigation into intra-host evolutionary dynamics, particularly with longitudinal sampling, is critical for broader understanding of disease progression.

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    SciScore for 10.1101/2020.04.24.20078691: (What is this?)

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    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

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  2. Version published to 10.1101/2020.04.24.20078691v1 on medRxiv