Abstract
The vast majority of multi-cellular organisms are anisogamous, meaning that male and female sex cells differ in size. It remains an open question how this asymmetric state evolved, presumably from the symmetric isogamous state where all gametes are roughly the same size (drawn from the same distribution). Here, we use tools from the study of nonlinear dynamical systems to develop a simple mathematical model for this phenomenon. Unlike some prior work, we do not assume the existence of mating types. We also model frequency dependent selection via “mean-field coupling,” whereby the likelihood that a gamete survives is an increasing function of its size relative to the population's mean gamete size. Using theoretical analysis and numerical simulation, we demonstrate that this mean-referenced competition will almost inevitably result in a stable anisogamous equilibrium, and thus isogamy may naturally lead to anisogamy.
Original language | English (US) |
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Article number | 110669 |
Journal | Journal of Theoretical Biology |
Volume | 521 |
DOIs | |
State | Published - Jul 21 2021 |
Funding
The authors gratefully acknowledge support of the National Science Foundation through the program on Research Training Groups in the Mathematical Sciences, grant 1547394. We also thank Northwestern University's Office of Undergraduate Research for support through URP 758SUMMER1915627 and URP 758SUMMER1915476. We also thank Christina Goss for help with translation of reference (Kalmus, 1932). The authors gratefully acknowledge support of the National Science Foundation through the program on Research Training Groups in the Mathematical Sciences, grant 1547394. We also thank Northwestern University’s Office of Undergraduate Research for support through URP 758SUMMER1915627 and URP 758SUMMER1915476. We also thank Christina Goss for help with translation of reference ( Kalmus, 1932 ).
Keywords
- Anisogamy
- Evolution
- Evolutionary game theory
- Isogamy
- Natural selection
ASJC Scopus subject areas
- General Agricultural and Biological Sciences
- Applied Mathematics
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology
- Statistics and Probability
- Modeling and Simulation