Narrow transmission bottlenecks and limited within-host viral diversity during a SARS-CoV-2 outbreak on a fishing boat

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1. Version published to 10.1093/ve/veac052

   Jun 16, 2022
2. 

   ScreenIT

   Feb 12, 2022

   SciScore for 10.1101/2022.02.09.479546: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   Sequencing Data Processing: All data processing from the raw unaligned sequencing files onwards was handled by our Snakemake pipeline available on Github — https://github.com/jbloomlab/SARS-CoV-2_bottleneck [22].	Snakemake suggested: (Snakemake, RRID:SCR_003475)
   Fastp was also used to filter reads from the FASTQ file if they contained more than 50% unqualified bases (Phred < 15) or were less than 50 base pairs in length.	Phred suggested: (Phred, RRID:SCR_001017)
   Following quality filtering, SARS-CoV-2 specific reads were selected from the FASTQ files by matching 31 base long kmers to the …

   SciScore for 10.1101/2022.02.09.479546: (What is this?)

   Please note, not all rigor criteria are appropriate for all manuscripts.

   Table 1: Rigor

   NIH rigor criteria are not applicable to paper type.

   Table 2: Resources

   Software and Algorithms
   Sentences	Resources
   Sequencing Data Processing: All data processing from the raw unaligned sequencing files onwards was handled by our Snakemake pipeline available on Github — https://github.com/jbloomlab/SARS-CoV-2_bottleneck [22].	Snakemake suggested: (Snakemake, RRID:SCR_003475)
   Fastp was also used to filter reads from the FASTQ file if they contained more than 50% unqualified bases (Phred < 15) or were less than 50 base pairs in length.	Phred suggested: (Phred, RRID:SCR_001017)
   Following quality filtering, SARS-CoV-2 specific reads were selected from the FASTQ files by matching 31 base long kmers to the Wuhan-1/2019 reference genome (NC_045512.2) using BBDuk (https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbduk-guide/).	https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbduk-guide/ suggested: (Bestus Bioinformaticus Duk, RRID:SCR_016969)
   After quality filtering and selection of reads containing SARS-CoV-2 sequences, the FASTQ files were aligned to the Wuhan-1/2019 reference (NC_045512.2) with BWA mem [24].	BWA suggested: (BWA, RRID:SCR_010910)
   Libraries that were resequenced for greater depth were joined these libraries together after alignment with Samtools merge [24].	Samtools suggested: (SAMTOOLS, RRID:SCR_002105)
   The tree was rooted using midpoint rooting as implemented by the R package phytools and plotted with ggtree [28,29] (Fig.	phytools suggested: (phytools, RRID:SCR_015502)
   Additionally, to include genomes that were similar to those on the boat, we built a BLASTN database from all sequences collected in Washington state at and before the time of the outbreak (May 5th, 2020) that met the same quality standards described above.	BLASTN suggested: (BLASTN, RRID:SCR_001598)
   We aligned these sequences using MAFFT, however, we also aligned to the Wuhan-1/2019 (NC_045512.2) reference and standardized the length of each sequence.	MAFFT suggested: (MAFFT, RRID:SCR_011811)
   Variant Calling and Filtering: Variants were identified using a custom Python script (https://github.com/jbloomlab/SARS-CoV-2_bottleneck/blob/master/workflow/scripts/process_pysam_pil_eup.py).	Python suggested: (IPython, RRID:SCR_001658)
   We annotated the coding effect of each SNP using SnpEff [35].	SnpEff suggested: (SnpEff, RRID:SCR_005191)

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   Results from OddPub: Thank you for sharing your code and data.

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   Our study has several limitations. First, we were able to obtain high-quality sequencing for only some of the boat’s crew members. After accounting for samples that passed our quality controls, only 13 of the 122 crew members were available for analysis. Therefore, we might be missing instances where a variant rises to fixation over multiple transmission events. Another limitation of this study is that we cannot quantitatively estimate the transmission bottleneck because we do not know which passengers infected one another. However, we can still observe that the paucity of shared intra-host viral variants indicates generally narrow transmission bottlenecks. Overall, our study corroborates the finding of limited shared intra-host viral diversity that has been observed in studies of acute infections with SARS-CoV-2 in other settings. Therefore, even superspreading events in poorly ventilated, close-quarters environments appear insufficient to alter the dominant role of transmission bottlenecks in shaping the evolution of SARS-CoV-2.

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   Results from TrialIdentifier: No clinical trial numbers were referenced.

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   Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   Results from rtransparent:

   • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
   • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
   • No protocol registration statement was detected.

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   Results from scite Reference Check: We found no unreliable references.

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3. 

   Version published to 10.1101/2022.02.09.479546v1 on bioRxiv

   Feb 9, 2022