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Join us at 12 PM EDT on Thursday, April 25, for the next installment in the ISCBacademy Webinar Series:
Reconstructing the horizontal movement of genes using Bayesian phylogenetic network inference
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Reconstructing the horizontal movement of genes using Bayesian phylogenetic network inference
by Nicola F. Müller
The horizontal movement of genes is a crucial driver in the evolution of viral and bacterial pathogens. It enables pathogens to, for example, make large jumps in fitness space, adapt to new host species, or gain novel genes, such as acquiring plasmids carrying determinants for antibiotic resistance. Phylogenetic methods are often used to reconstruct evolutionary events but mostly assume that a phylogenetic tree can describe the shared evolutionary history of pathogens. This assumption—that phylogenetic trees accurately represent that history—is challenged when genes move horizontally, necessitating the use of phylogenetic networks instead.
In this talk, I will first present recent work on inferring phylogenetic networks using a Markov chain Monte Carlo approach. This approach models the horizontal movement of genes using coalescent models, allowing us to quantify reassortment, recombination, or plasmid transfer rates. I will then showcase multiple applications of phylogenetic network inference. First, I will demonstrate how we can use the coalescent with reassortment to infer reassortment rates across different influenza viruses. Next, I will discuss how phylogenetic network inference allows us to infer the complex evolutionary history of human coronaviruses, including MERS and SARS-like viruses such as SARS-CoV-1 and 2. Lastly, I will present work on reconstructing the gain and loss of small plasmids and the recent dissemination of a multidrug-resistance plasmid between Shigella sonnei and Shigella flexneri lineages. This includes multiple independent events and steady growth in prevalence since 2010 and quantifies the rates at which different plasmids move between bacterial lineages.
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