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Recent insights into SARS-CoV-2 intra-host population dynamics

C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Assistant Professor, Computer Science, Rice University, Co-Lead COVID-19 International Research Team (COV-IRT)
    Biography
      Todd J. Treangen, Ph.D. is an Assistant Professor in the Department of Computer Science at Rice University and co-lead of the COVID-19 International Research Team (COV-IRT, www.cov-irt.org). Prior to joining Rice, Dr. Treangen was an Assistant Research Professor at the University of Maryland College Park. He received his Ph.D. in Computer Science in 2008 from the Polytechnic University of Catalonia (Barcelona, Spain). His research group focuses on solving large-scale computational problems specific to computational biology, with a focus on developing robust software tools targeted towards biothreat screening, infectious disease monitoring, and microbial forensics. For more info: https://www.treangenlab.com

    Abstract

    The fast spread and deadliness of SARS-CoV-2 has sparked much interest in understanding the underlying genomics and evolutionary patterns of this 30,000bp Coronavirus. Since the first reported case on January 19th, 2020, over 200,000 genomes are now available. Within this large set of SARS-CoV-2 genomic data, thousands of mutations have been, including the D614G mutation that now is found in nearly all genomes and mink-associated variants. In this talk, I will take a deep dive into the intrahost and interhost diversity of the virus responsible for the COVID-19 pandemic. Specifically, I will discuss within-host minor variants and consensus-level variants that are found across hosts and describe population-wide structural variations that highlight this underexplored intrahost diversity. Implications of these findings include improved transmission cluster identification  and better understanding of how SARS-CoV-2 is changing over time.

    Learning Objectives:

    1. Differentiating consensus-level vs within-host variation of SARS-CoV-2

    2. Discovering the utility of genomic variants on tracking SARS-CoV-2 transmission

    3. Understanding of how SARS-CoV-2 is changing over time


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