ASSESSING THE IMPEDIMENTS ASSOCIATED WITH SARS-COV-2 WHOLE GENOME SEQUENCING

Abstract

Genomic surveillance can help track the emergence of SARS-COV-2 variants with novel mutations that can alert scientists and policymakers to ensure a proper response is implemented, such as updating vaccine formulations and public health policies. Due to logistics and costs, whole genome sequencing (WGS) cannot be conducted on all nasopharyngeal swabs (NPS). Further, there are regions of ambiguity in each sequence, which needs to be resolved. Therefore, the objective of this research is to enhance the WGS workflow for the submission of high-coverage SARS-CoV-2 sequences to global genomic databases. COVID-19-positive NPS were collected from clinical laboratories in Oahu and underwent a WGS workflow. During the workflow, different measurements that ascertain viral genomic levels were assessed to enhance the WGS workflow using statistical analysis to predict if a nucleotide sequence meets the criteria for submission to GenBank. Furthermore, if dropout regions were observed in the sequences, primers were designed to flank these regions for Sanger sequencing. This Sanger sequence was compared to an updated in-house developed novel bioinformatic workflow that fills in the ambiguous bases using an updated consensus reference sequence. These results demonstrate that utilizing a DNA cut-off of 1.096 ng/ µL increases the submission rate of SARS-CoV-2 sequences to the GenBank database by 15%. Additionally, the proposed updated bioinformatic workflow decreased ambiguous bases within a sequence and had a high coverage accuracy of 99.5-100% when compared to the Sanger sequencing. These data suggest that the updated bioinformatic workflow described in this thesis will enhance the quality of the WGS sequences submitted to various global genomic databases. These findings have the potential to be applied to other pathogens currently being monitored such as the influenza virus or antimicrobial-resistant bacteria.