Two-locus clines maintained by diffusion and recombination in a heterogeneous environment
Linlin Su, King-Yeung Lam, Reinhard B\"urger

TL;DR
This paper investigates the existence and stability of two-locus clines in a spatially structured population, revealing how recombination strength influences genetic diversity and equilibrium stability in heterogeneous environments.
Contribution
It provides new conditions for the existence and stability of two-locus clines, including cases of weak and strong recombination, and analyzes stability of monomorphic equilibria.
Findings
Strong recombination leads to unique, globally stable clines.
Weak recombination allows for stable internal clines under certain conditions.
Monomorphic equilibria stability depends on recombination and selection.
Abstract
We study existence and stability of stationary solutions of a system of semilinear parabolic partial differential equations that occurs in population genetics. It describes the evolution of gamete frequencies in a geographically structured population of migrating individuals in a bounded habitat. Fitness of individuals is determined additively by two recombining, diallelic genetic loci that are subject to spatially varying selection. Migration is modeled by diffusion. Of most interest are spatially non-constant stationary solutions, so-called clines. In a two-locus cline all four gametes are present in the population, i.e., it is an internal stationary solution. We provide conditions for existence and linear stability of a two-locus cline if recombination is either sufficiently weak or sufficiently strong relative to selection and diffusion. For strong recombination, we also prove…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMathematical and Theoretical Epidemiology and Ecology Models · Evolution and Genetic Dynamics · Mathematical Biology Tumor Growth
