I study theoretical population genetics using mathematical analysis of stochastic processes (diffusion approximation and coalescent theory) and evolutionary simulations. My recent research topics include local adaptation, sex chromosome evolution, and the evolution of gene regulation. I am also broadly interested in various topics in evolutionary biology. For a list of my publications, please visit Google Scholar and ORCiD.
Assistant Professor @ Evolutionary Genetics Lab., Department of Biology, Kyushu University
744 Moto-oka, Nishi-ku, Fukuoka 819-0395, Japan
Email: sakamoto.takahiro.292 (at) m.kyushu-u.ac.jp
2023-2026: Postdoc @ National Institute of Genetics, Japan (PI: Dr. Hiroshi Akashi)
2023-2025: Visiting Postdoc @ University of Calgary, Canada (PI: Dr. Sam Yeaman)
2018-2023: Ph. D student @ SOKENDAI, Japan (Supervisor: Dr. Hideki Innan)
Analyzing structured populations is challenging due to multidimensional stochastic processes. Exploiting the fact that strong migration allows an entire population to behave as a single unit, we developed a method to determine when this approximation is valid and derive the corresponding one-dimensional diffusion process.
Local adaptation in polygenic traits can arise through divergence at a few large-effect loci or many small-effect loci. Using mathematical analysis and simulations, we examined how the stability of divergence at large-effect loci depends on migration rates, background mutation rates, and other evolutionary parameters.
Web-based Population Genetics Simulators
As a hobby, I'm developing interactive simulators to help beginners learn the basics of population genetics. They should also work on smartphones, so I hope they might be useful in classes or other settings. Send Feedback (Google Form) .