A laboratory framework for ongoing optimization of amplification-based genomic surveillance programs

Abstract

ABSTRACT Constantly evolving viral populations affect the specificity of primers and the quality of genomic surveillance. This study presents a framework for the continuous optimization of sequencing efficiency for public health surveillance based on the ongoing evolution of the COVID-19 pandemic. SARS-CoV-2 genomic clustering capacity based on three amplification-based whole genome sequencing schemes was assessed using decreasing thresholds of genome coverage and measured against epidemiologically linked cases. The overall genome coverage depth and individual amplicon depth were used to calculate an amplification efficiency metric. Significant loss of genome coverage over time was documented, which was recovered by optimization of primer pooling or implementation of new primer sets. A minimum of 95% genome coverage was required to cluster 94% of epidemiologically defined SARS-CoV-2 transmission events. Clustering resolution fell to 70% when only 85% genome coverage was achieved. The framework presented in this study can provide public health genomic surveillance programs with a systematic process to ensure an agile and effective laboratory response during rapidly evolving viral outbreaks. IMPORTANCE This study provides a laboratory framework to ensure ongoing relevance and performance of amplification-based whole genome sequencing to strengthen public health surveillance during extended outbreaks or pandemics. The framework integrates regular reviews of the performance of a genomic surveillance system and highlights the importance of ongoing monitoring and the identification and implementation of improvements to whole genome sequencing methods to enhance public health responses to pathogen outbreaks.