464 - Rapid whole genome sequence typing reveals multiple waves of SARS-CoV-2 spread

Background: As the pandemic SARS-CoV-2 virus has spread globally its genome has diversified and distinct clones can now be recognized, tracked, and traced. Identifying clonal groups allows for assessment of geographic spread, transmission events, and identification of more virulent or transmissible emerging strains.

Methods: All SARS-CoV-2 genomes (n=17,504) that are complete and high coverage were downloaded from GISAID on May 17^th 2020. We developed a GNU-based Virus IDentification (GNUVID) tool that implements a whole genome multilocus sequence typing (wgMLST) scheme composed of all ten ORFs in the SARS-CoV-2 genome. The 10,422 genomes that passed our quality check were fed to the GNUVID tool, which assigned a ST profile to each genome. Global optimum eBURST was then used to cluster the STs in clonal complexes (CCs).

Results: Our ST/CC analysis uncovered strong associations of ST/CCs with certain geographical regions but also dynamic local changes in ST/CC prevalence. We also identified several unexpected putative global transmission events (e.g., from the US to the Middle East and reintroduction to China later in the pandemic). We have made our tool (GNUVID) available so that new WG sequences can be rapidly assigned to an ST/CC (https://github.com/ahmedmagds/GNUVID).

Conclusion: Our sequence typing system uncovered previously unappreciated transmission events and waves of expansion and replacement of SARS-CoV-2 STs and CCs in different geographical locations, suggesting complex dynamics in viral populations that previously seemed monomorphic. Because, our tool can be rapidly updated with new sequencing data it can track emerging clones and identifying new hotspots.