To facilitate real-time outbreak management and mitigation strategies, there is an urgent need to understand the spread of COVID-19. Researchers reconstruct the evolutionary and transmission history of the virus by applying algorithms to sequencing samples of COVID-19 patients. However, a key challenge is the presence of multiple strains of the virus within hosts, which is overlooked by current algorithms. This RAPID project will improve the nation’s COVID-19 response by developing algorithms to characterize the ongoing evolution and spread of the viral strains that coexist within patients. The developed algorithms will be applicable to future disease outbreaks.

This RAPID project seeks to understand the impact of within-host viral diversity on the current spread of COVID-19. The project will identify the viral strains coexisting in patients through the development of algorithms that deconvolve COVID-19 sequencing samples. Subsequently, the project will assess whether or not such coexisting strains are the result of multiple infection events. Finally, the project will quantify the severity of the identified viral strains through a protein functional analysis of their mutations. Results will be disseminated through an online portal that enable labs and hospitals to upload their sequencing reads and generate annotations and characterizations of COVID-19 viral strains.

In summary, the goal of this research is to understand SARS-CoV-2 by investigating the evolutionary origins of the virus and its genetic variation within host species in order to determine how molecular variation correlates with host range, and to evaluate risk of further disease emergence.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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University of Illinois Urbana-Champaign
United States
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