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Journal Articles Bulletin of Mathematical Biology Year : 2022

Ancestral Lineages in Mutation Selection Equilibria with Moving Optimum

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Many populations can somehow adapt to rapid environmental changes. To understand this fast evolution, we investigate the genealogy of individuals inside those populations. More precisely, we use a deterministic model to describe the phenotypic density of a population under selection when the fitness optimum moves at constant speed. We study the inside dynamics of this population using the neutral fractions approach. We then define a Markov process characterizing the distribution of ancestral phenotypic lineages inside the equilibrium. This construction yields qualitative as well as quantitative properties on the phenotype of typical ancestors. In particular, we show that in asexual populations typical ancestors of present individuals carried traits much closer to the fitness optimum than most individuals alive at the same time. We also investigate more deeply the asymptotic regime of small mutation effects. In this regime, we obtain an explicit formula for the typical ancestral lineage using the description of the solutions of the Hamilton Jacobi equation as a minimizer of an optimization problem. In addition, we compare our deterministic results on lineages with the lineages of stochastic models.

Dates and versions

hal-03843702 , version 1 (08-11-2022)



Raphaël Forien, Jimmy Garnier, Florian Patout. Ancestral Lineages in Mutation Selection Equilibria with Moving Optimum. Bulletin of Mathematical Biology, 2022, 84 (9), pp.93. ⟨10.1007/s11538-022-01048-w⟩. ⟨hal-03843702⟩
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