DOI: 10.6078/d1jq5c
title: Understanding shared variation in SARS-CoV-2 genomes

description: The project is a collaborative effort of investigators from the University
 of California, Berkeley’s Innovative Genomics Institute (IGI) and School
 of Public Health (SPH); Kaiser Permanente Northern California (KPNC); and
 the California Department of Public Health (CDPH), with administrative and
 programmatic support provided by Heluna Health. Over the project period,
 the collaborating investigators will analyze approximately 35,000 genomes
 of SARS-CoV-2 specimens obtained from KPNC members and sequenced by the
 CDPH through its COVIDNet activities. By combining results from the
 genomic analysis of low-frequency alleles with clinical and epidemiologic
 data available in patient records, including demographic variables,
 COVID-19 vaccination status (dates of vaccination; number of doses;
 manufacturer), COVID-19 disease severity, and underlying medical
 conditions, we assessed which shared genomic variations are associated
 with a greater risk of symptomatic infection and severe clinical outcomes;
 COVID-19 vaccine effectiveness; and transmission of SARS-CoV-2 in the
 household. The project and its results can serve as a model for
 community-based monitoring of the evolution and spread of SARS-CoV-2 and
 use of the data to inform decisions about the formulation and use of
 COVID-19 vaccines, including booster doses and next-generation vaccines.
description: <strong>Sample
 collection</strong> Our
 samples are from Kaiser Northern California patients testing positive for
 SARS-CoV-2 starting June 1, 2021, and through the present. The RNA is sent
 to the California Department of Public Health (CDPH) lab to be sequenced
 by COVIDNet–a consortium of primarily UC system labs helping CDPH with the
 overflow and backlog of samples. Once the genomes have been sequenced, the
 lineage information and unique deidentified PAUI number are returned to
 Kaiser where this information is recorded. Metadata from this list of
 PAUI’s is sent weekly to UC Berkeley. The KPNC sequencing data is returned
 to us through a third party that is processing all CDPH genomes and stored
 on a server at UC Berkeley and matched with metadata using
 PAUI’s. <strong>Sequence
 analysis</strong> The raw
 sequencing data is processed through a SARS-CoV-2 analysis pipeline that
 has been modified for this work as follows. Adapter removal and trimming
 are performed using <em>bbduk</em>. The reads are then aligned
 to the Wuhan reference genome using minimap2 followed by primer trimming
 using iVAR . We next create a pileup file using samtools and use that
 input to create a consensus file. This consensus file is created with iVAR
 using a minimum depth of 10 reads and majority rule for base calling. We
 next use iVAR to call variants from the pileup file where we set the
 threshold for calling a mutation to be 0.01. This will call mutations for
 any loci where at least one percent of the reads are non-reference. This
 very low threshold allows us to capture all variation that is seen in the
 sequencing data. The list of variants is then annotated with the gene and
 amino acid change (if there is one), and whether the mutation is
 considered defining in any SARS-CoV-2 variants and whether that mutation
 is seen in only one variant. This
 dataset includes the fasta consensus sequences and mutation calls for each
 genome.
description: These are fasta files and tab-delimited files and can be opened
 with any editor (fasta) or excel (mutation files).