(Internal) The evolution of SARS-CoV-2 (COVID-19) variants: analysis of large genomic datasets

Advisor: Ryan Gregory, Integrative Biology

Proposed computational advisor: Stefan Kremer, Justin Slater, Ayesha Ali, Rozita Dara, Lorna Deeth, Khurram Nadeem, Gurjit Randhawa, Yan Yan

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is unprecedented in human history in terms of both the number of hosts available, the degree of repeated infection, and the amount of global travel. At the same time, there has never before been such a detailed dataset of genome sequences that has allowed the evolution of the virus to be tracked in real-time. In particular, there are very large sequence datasets available from wastewater surveillance programs that have yet to be analyzed from the perspective of variant evolution. This includes identifying and tracking the evolution of rare and highly divergent variants that occur (for the time being) in only a single host with a persistent infection (“cryptic lineages”). 

This project will involve the use of bioinformatics tools to pose and answer empirical questions related to the evolution of SARS-CoV-2 variants. This may include tracking the effects and interactions of specific mutations, the role of within-host versus among-host evolution, the mechanisms that generate very divergent variants (e.g., long-term within-host infections, recombination among lineages, evolution in non-human host species), and the occurrence and evolution of variants arising within single hosts harbouring persistent infections.

This can be a one-semester or two-semester project. More than one student can work on a project involving this topic.
 

Knowledge/Skills

Familiarity with sequence analysis using bioinformatics tools, ability to work collaboratively, comfort working with large datasets, problem solving.