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KISHINO Hirohisa

  • Graduate School of Agricultural and Life Sciences, University of Tokyo, Tokyo, Japan
  • Ecology, Evolutionary Biology, Genetics and population Genetics, Probability and statistics
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Educational and work
Education 1971.4 - 1974.3 Tokyo Metropolitan Fuji High School 1974.4 - 1976.3 Faculty of Liberal Arts and Sciences, University of Tokyo 1976.4 - 1978.3 B. S. Mathematics, Department of Mathematics, University of Tokyo 1978.4 - 1980.3 M. S. Mathematics, Department of Mathematics, University of Tokyo 1989.3 Dissertation PhD. Department of Biology, Kyushu University Professional Experience 1980.4 - 1990.11 Assistant Professor, Institute of Statistical Mathematics 1990.12- 1993.6 Associate Professor, Ocean Research Institute, University of Tokyo 1993.7 - 1999.3 Associate Professor, Graduate School of Arts and Sciences, University of Tokyo 1999.4 - present Professor, Graduate School of Agriculture and Life Sciences, University of Tokyo

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07 Dec 2021
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The emergence of a birth-dependent mutation rate in asexuals: causes and consequences

A new perspective in modeling mutation rate for phenotypically structured populations

Recommended by based on reviews by Hirohisa Kishino and 1 anonymous reviewer

In standard mutation-selection models for describing the dynamics of phenotypically structured populations, it is often assumed that the mutation rate is constant across the phenotypes. In particular, this assumption leads to a constant diffusion coefficient for diffusion approximation models (Perthame, 2007 and references therein).   

Patout et al (2021) study the dependence of the mutation rate on the birth rate, by introducing some diffusion approximations at the population level, derived from the large population limit of a stochastic, individual-based model. The reaction-diffusion model in this article is of the “cross-diffusion” type: The form of “cross-diffusion” also appeared in ecological literature as a type of biased movement behaviors for organisms (Shigesada et al., 1979). The key underlying assumption for “cross-diffusion” is that the transition probability at the individual level depends solely upon the condition at the departure point. Patout et al (2021) envision that a higher birth rate yields more mutations per unit of time. One of their motivations is that during cancer development, the mutation rates of cancer cells at the population level could be correlated with reproduction success.   

The reaction-diffusion approximation model derived in this article illustrates several interesting phenomena: For the time evolution situation, their model predicts different solution trajectories under various assumptions on the fitness function, e.g. the trajectory could initially move towards the birth optimum but eventually end up at the survival optimum. Their model also predicts that the mean fitness could be flat for some period of time, which might provide another alternative to explain observed data. At the steady-state level, their model suggests that the populations are more concentrated around the survival optimum, which agrees with the evolution of the time-dependent solution trajectories.   

Perhaps one of the most interesting contributions of the study of Patout et al (2021) is to give us a new perspective to model the mutation rate in phenotypically structured populations and subsequently, and to help us better understand the connection between mutation and selection. More broadly, this article offers some new insights into the evolutionary dynamics of phenotypically structured populations, along with potential implications in empirical studies.   

References

Perthame B (2007) Transport Equations in Biology Frontiers in Mathematics. Birkhäuser, Basel. https://doi.org/10.1007/978-3-7643-7842-4_2

Patout F, Forien R, Alfaro M, Papaïx J, Roques L (2021) The emergence of a birth-dependent mutation rate in asexuals: causes and consequences. bioRxiv, 2021.06.11.448026, ver. 3 peer-reviewed and recommended by Peer Community in Mathematical and Computational Biology. https://doi.org/10.1101/2021.06.11.448026

Shigesada N, Kawasaki K, Teramoto E (1979) Spatial segregation of interacting species. Journal of Theoretical Biology, 79, 83–99. https://doi.org/10.1016/0022-5193(79)90258-3

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KISHINO Hirohisa

  • Graduate School of Agricultural and Life Sciences, University of Tokyo, Tokyo, Japan
  • Ecology, Evolutionary Biology, Genetics and population Genetics, Probability and statistics
  • recommender, manager

Recommendations:  0

Review:  1

Educational and work
Education 1971.4 - 1974.3 Tokyo Metropolitan Fuji High School 1974.4 - 1976.3 Faculty of Liberal Arts and Sciences, University of Tokyo 1976.4 - 1978.3 B. S. Mathematics, Department of Mathematics, University of Tokyo 1978.4 - 1980.3 M. S. Mathematics, Department of Mathematics, University of Tokyo 1989.3 Dissertation PhD. Department of Biology, Kyushu University Professional Experience 1980.4 - 1990.11 Assistant Professor, Institute of Statistical Mathematics 1990.12- 1993.6 Associate Professor, Ocean Research Institute, University of Tokyo 1993.7 - 1999.3 Associate Professor, Graduate School of Arts and Sciences, University of Tokyo 1999.4 - present Professor, Graduate School of Agriculture and Life Sciences, University of Tokyo