Speaker: Kristina Moen, ISU Mathematics Department
Title: Tracking the Molecular Evolution of SARS-CoV-2: A Topological Approach
Abstract: COVID-19, the disease caused by the SARS-CoV-2 virus, has triggered an unprecedented global pandemic and caused an estimated 4.5 million deaths worldwide. As the virus spreads, it mutates and can become more infectious, virulent, and unpredictable. To better understand the evolution of SARS-CoV-2, we focus on its genetic code or RNA. A single SARS-CoV-2 RNA sequence is composed of approximately 30,000 nucleotide bases: one of Adenine (A), Cytosine (C), Guanine (G), or Uracil (U). We take SARS-CoV-2 RNA sequences and embed them as discrete points in a metric space. Using Topological Data Analysis, we examine hidden algebraic and topological structures to infer evolutionary events such as point mutations (where single nucleotides are changed, inserted, or deleted) and viral recombination (where two viruses co-infect the same host cell and exchange genetic material). We develop a hypothesis to help identify parental and recombinant strains of the virus using edge weights of the cycles that define the first homology group (H1) generators. This work was done with Dr. Javier Arsuaga and Dr. Mariel Vazquez (UC Davis).