Genomic surveillance of SARS-CoV-2 in Ontario, Canada reveals biases in mutational patterns between successive epochs delimited by major public health events (Preprint)

Abstract

The emergence of SARS-CoV-2 variants with mutations associated with increased transmissibility and virulence is an ongoing public health concern in Ontario, Canada. Characterizing how the mutational patterns of the SARS-CoV-2 genome have changed over time can shed light on the driving factors, including selection for increased fitness and host immune response, that may contribute to the emergence of novel variants. Moreover, the study of SARS-CoV-2 in the microcosm of Ontario, Canada can reveal how different province-specific public health policies over time may be associated with observed mutational patterns as a model system.

This study is a comprehensive analysis of single base substitution types, counts, and genomic locations observed in SARS-CoV-2 genomic sequences sampled in Ontario, Canada. Comparisons of mutational patterns were conducted between sequences sampled during four different epochs delimited by major public health events to track the evolution of the SARS-CoV-2 mutational landscape over two years.

In total, 24,244 SARS-CoV-2 genomic sequences and associated metadata sampled in Ontario, Canada from January 1, 2020 to December 31, 2021 were retrieved from the GISAID database. Sequences were assigned to four epochs, delimited by major public health events based on the sampling date. Single base substitutions from each SARS-CoV-2 sequence were identified relative to the MN996528.1 reference genome. Catalogues of single base substitution types and counts were generated to estimate the impact of selection in each open reading frame, and identify mutation clusters. The estimation of mutational fitness over time was calculated using the Augur pipeline.

In total, 24,244 SARS-CoV-2 genomic sequences and associated metadata sampled in Ontario, Canada from January 1, 2020 to December 31, 2021 were retrieved from the GISAID database. Sequences were assigned to four epochs, delimited by major public health events based on the sampling date. Single base substitutions from each SARS-CoV-2 sequence were identified relative to the MN996528.1 reference genome. Catalogues of single base substitution types and counts were generated to estimate the impact of selection in each open reading frame, and identify mutation clusters. The estimation of mutational fitness over time was calculated using the Augur pipeline.

Quantitative analysis of mutational patterns of the SARS-CoV-2 genome in the microcosm of Ontario, Canada within early consecutive epochs of a pandemic tracks the mutational dynamics in a context of public health events that instigate significant shifts in selection and mutagenesis. We observed positive selection of ORF1A and S, highlighting the challenges in the rational design of effective pan-variant therapeutics targeting these regions. The differences in ORF selection, mutation clusters, and mutation diversity may be driven in part by viral evolution in a human population with different immune responses. Continued genomic surveillance of emergent variants will be useful for the design of public health policies in response to the evolving COVID-19 pandemic.