A laboratory framework for ongoing optimisation of amplification based genomic surveillance programs
Lam, C.; Johnson-Mackinnon, J.; Basile, K.; Fong, W.; Suster, C. J. E.; Gall, M.; Aguis, J.; Chandra, S.; Draper, J.; Martinez, E.; Drew, A.; Wang, Q.; Chen, S.; Kok, J.; Dwyer, D. L.; Sintchenko, V.; Rockett, R. J.
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Constantly evolving viral populations affect the specificity of primers and quality of genomic surveillance. This study presents a framework for continuous optimisation 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. 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 optimisation 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% of genome coverage was achieved. The framework presented in this study can provide public health genomic surveillance programs a systematic process to ensure an agile and effective laboratory response during rapidly evolving viral outbreaks.
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