Frontiers in Genomics: Oana Carja
A theory of evolutionary dynamics on any complex population structure

Resumen de la plática
At a big picture level, my group at CMU is focused on studying the adaptive properties of spatial structure, across different biological systems. Spatially-resolved datasets are revolutionizing knowledge across many areas in biology, yet are under-utilized for questions in evolutionary biology. When it comes to understanding the role that population structure plays in shaping rates of evolution, it is commonly accepted that interference between evolutionary innovations is more prevalent in structured populations compared to well-mixed, and that population structure reduces the rate of evolution, while simultaneously promoting maintenance of genetic variation. Prior models usually represent population structure using two or more connected demes or lattices with periodic boundary conditions. Fundamentally, the observed spatial evolutionary slow-down is rooted in the fact that these types of structures increase the time it takes for a selective sweep and therefore, increase the probability that multiple beneficial mutations will coexist and interfere. I will present a new modeling framework that allows us to introduce more complexity in the types of population structures we can study and show that this can reshape prior conclusions and lead to a much wider range of observed evolutionary outcome. At a big picture level, our results showcase that knowing how the effects of population structure depend on the properties of the topology considered is crucial for making meaningful comparisons across different topologies and for developing an intuition for when and why the well-mixed approximations, or approximations done using models with a high degree of symmetry, might not apply. This is requisite for forming sensible null expectations about experimental or observational data.

Oana Carja. Carnegie Mellon University, US

https://cbd.cmu.edu/people/carja.html

Frontiers in Genomics