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2nd APS COVID webinar - recording available

  • 1.  2nd APS COVID webinar - recording available

    Topical Group Officer
    Posted 16 days ago

    Hi everyone,

    Recording of the 2nd webinar is available in the CRRG library. Please check it out if you were not able to attend in person.

    Thanks everyone who completed the post-webinar survey! It is very useful and thanks for many valuable suggestions. Anyone, who has not filled out the survey, please do so! Your feedback really helps!

    Regards,

    Robert



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    Robert Jeraj
    University of Wisconsin - Madison
    Madison WI
    rjeraj@wisc.edu
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  • 2.  RE: 2nd APS COVID webinar - recording available

    EARLY CAREER MEMBER
    Posted 8 days ago
    Hi everyone,

    Dr. Rabadan's webinar was excellent. It was very dense with insights and methodological detail. Most of this was new to me personally, so I'm sure that people can expand on the notes I took (below). Feel free to comment with any insights I missed or expand the discussion on any of these concepts as I'd love to learn more. Thanks!

    Raul Rabadan, director of the Program for Mathematical Genomics and director of the Center for Topology of Cancer Evolution and Heterogeneity at Columbia University

    PART 1: Evolution of Coronaviruses

    • COVID-19 is the disease caused by the SARS-CoV-2 virus in humans
      • So in order to understand evolution of the disease, we need information about both the virus and the human (i.e genomic info) – this talk is about the virus information
    • How do coronaviruses evolve?
      • Mutations
        • SARS is an RNA virus
        • Smaller genome size (bp) leads to faster mutation rate
          • Thus viruses mutate at a much higher rate than eukaryotes and bacteria
        • Use phylogenetic trees to represent the evolution/history of how the virus evolves
        • Mutation tracking:
          • 100,000 genomes of this virus that have been collected around the world since December
          • Branches show the relationship between measured genomes
          • Tells us that most of the viruses are very similar, which tell us that this virus is new in the population (the Wu-Han outbreak is very close to the origin of the virus); has not been circulating in humans for very long
          • Can see by the clusters where the virus branched from
            • Example: US cluster in Washington came from one branch from China
            • Suggests that international travel played a very instrumental role in early spread
          • Recombination
            • Can create highly non-local jumps in the branches
            • One branch can quickly acquire traits of different branches
          • Where is SARS-CoV-2 coming from?
            • Is a sarbecovirus (subset of beta-coronaviruses)
            • SARS is a subtype of coronavirus called beta-coronaviruses
              • We know of 4 of these in humans:
                • SARS-CoV-1 in 2002-2003
                  • Coronaviruses in bats are very similar to what we saw in humans for SARS-CoV-1 and current SARS-CoV-2
                • MERS-CoV
                  • Come from other animals (pangolins)
                • OC43 and HKU1 have been circulating for long time
                  • Usually kids and usually asymptomatic
                  • Distantly related to current virus
                • Recombination is pervasive in beta-coronaviruses (extremely frequent)
                  • Showed plots that show a jump in recombination events in a particular region
                  • Looking more closely at the phylogenetic structure of this particular region…
                    • When looking at whole genome see relation to virus in pangolins
                    • When looking at specific region, see more similarity to SARS-CoV-1 and virus in bats
                  • This region appears to be highly important because of receptor-binding domain (RBD)
                • Topological inconsistencies in SARS-CoV-2
                  • Seems that at some point there was an exchange of information between a close ancestor of SARS-CoV-1 and 2 (recombination event)
                  • Studied Rosetta binding energy for each branch of the sarbecoviruses
                    • Shows difference in binding affinity for various branches of the virus
                  • Receptor-binding domain (RBD) recombination events study suggest that many events that happened ~2007 and ~2010 mutated to create SARS-CoV-2
                • SUMMARY:
                  • Coronavirus mostly evolve through point mutations and recombinations
                  • Recombinations are extremely frequent in beta-coronaviruses
                  • Reconstruction of ancestral states to CoV-2 suggest a two hit scenario model:
                    • Recombination picks up SARS-like RBD - > enables binding to human ACE2 receptor
                    • Further mutations refine the interactions between RBD and receptor
                  • Ancestral reconstruction analysis indicates active circulation of potentially human infecting sarbecoviruses for the last 20 years

    PART 2: Tools and Methods

    • Are phylogenetic trees a good way of thinking about viral data?
      • Standard method, but have shown that looking as specific regions of the genome can be very impactful (looking at subsections of the trees is important)
    • Practical problem: Given a set of genomes and a way of comparing them, how do we represent their relationship without any assumptions about species or non-vertical genetic exchange?
      • 3 important features to consider:
        • Type of evolution
        • Frequency
        • Scale of exchange
      • Could topological analysis be a better method?
      • Topological data analysis
        • Homology groups capture global properties about shapes of spaces
          • Count the number of n dim objects that are not a boundary of an n+1 object
          • Ranks are called Betti numbers (b0: connected, b1: holes, b2: voids/cavities)
        • How do we uncover underlying topological invariants with real (noisy) samples?
          • Examine the persistent homology
            • Calculate the number of connected components across different scales
          • What is the topology of space sampled by genomes?
            • Represent evolutionary relationships of a large set of genomes by persistence complex
              • Simulation without recombination only gives 0-dim connections
              • With recombination then results in 0 and 1 dimensional connections
            • Genomic data -> set of evolutionary complexes -> properties of the evolution process
            • 3 examples:
              • Influenza A: reassortments
                • Several are circulating, every ~30 years we get a pandemic due to a recombination jump from a branch that has been circulating in animals
                • H1N1: Trying to explore the origin of the reassortments of the swine, human, and avian versions of the virus
                  • Found no recombination (all b0 connections) within one segment of the virus
                  • Found higher dimension connections when looking at combinations of segments
                  • Explored whether particular segments like to travel together
                • Sarbecoviruses
                  • Find many recombination events in a particular region
                • HIV
                  • Show many voids
                • SUMMARY:
                  • Evolution occurs in a high dimensional space (genomics sample this space)
                  • Want to understand the structure of this space from sample points
                  • Algebraic topology (TDA) provides a way to capture properties about the shapes of the evolutionary spaces
                    • Type: including complex exchange of genomic material keeping track of the scale of the process
                    • Scale: keeps track of the evolutionary scale
                    • Numbers: statistics of shapes (how many objects and at what scale)

     

    QUESTIONS:

    • How can you find shared ancestry using topological data?
      • Topology has no time direction, so we have to impose additional restrictions to incorporate these dynamic concepts
    • How do you examine functional impact of mutations and recombinations?
      • Still needs much study
    • How much evidence do we have to find the exact mutations and their locations?
    • Transmission of virus between humans
    • Does the virus evolve more or less in humans who are more affected by the virus (more symptoms)?
      • No evidence to show this. Yet? Only small amount of data
    • Would SARS-CoV-1 cause illness if reintroduced to the population now? Or do we have vaccinations?
      • Evidence that it was more confined to the hospital environment than this one
    • Comparing to SARS-CoV-1, very few people didn't have symptoms… can we find a location in the genome that explains why this is different in CoV-2?
      • Need more experimental testing to understand this better
    • Noise in the data… how much does the noise really affect your studies? There is a lot of sampling
      • Noise in this technology is very low. Noise is a minor contribution in the technology
      • Noise discussion earlier was about biological noise, not technological
    • Is there a way to extrapolate to future predictions of mutations?
      • Can see that the number of mutations will continue to increase with time
      • Can predict that recombinations will certainly happen – don't know how frequent, likely very rare


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    Alison Deatsch
    Postdoctoral Research Associate
    University of Wisconsin - Madison
    Madison IL
    deatsch@wisc.edu
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