Development of Molecular and Bioinformatic Methods for Pan-Virome Analysis of SARS-COV-2 and Co-Circulating Viruses
Two major gaps in the understanding of COVID-19 are:
- how does COVID-19 evolve within and between hosts?
- how do co-infections impact COVID-19 transmission and clinical disease?
Currently, most COVID-19 genomic applications rely on PCR and subsequent sequencing. This approach has limitations, including biasing of the genome, failure to detect novel variants, and inability to detect co-circulating viruses.
Led by Noelle Noyes, DVM, PhD, assistant professor of veterinary population medicine, researchers in this study will develop a metagenomics approach that could address these limitations.
“There is a critical and unmet need for unbiased, multi-virus, full-length-genome detection in clinical samples,” said Noyes. “We hypothesize that rapid virome enrichment and real-time long-read sequencing can be combined with novel bioinformatics to quickly produce full-length, highly-resolved genomic data for all potential viruses in a clinical sample.”
This project is supported by the UMN Campus Public Health Officer's CO:VID (Collaborative Outcomes: Visionary Innovation & Discovery) grants program, which support University of Minnesota faculty to catalyze and energize small-scale research projects designed to address and mitigate the COVID-19 virus and its associated risks.