# How does geographical distance translate into genetic distance?

## TL;DR

This paper models how geographic structure influences genetic differentiation by representing populations as a graph and analyzing genetic distances through random walk hitting times, revealing the importance of overall metapopulation structure.

## Contribution

It introduces a graph-based model linking genetic distances to metapopulation structure using random walk hitting times under specific regimes.

## Key findings

- Genetic distance converges to a deterministic value in large populations.
- Distance depends on the entire metapopulation structure, not just direct migration.
- Model simplifies to a population-based model under rare mutation and migration regimes.

## Abstract

Geographic structure can affect patterns of genetic differentiation and speciation rates. In this article, we investigate the dynamics of genetic distances in a geographically structured metapopulation. We model the metapopulation as a weighted directed graph, with d vertices corresponding to d subpopulations that evolve according to an individual based model. The dynamics of the genetic distances is then controlled by two types of transitions -mutation and migration events. We show that, under a rare mutation - rare migration regime, intra subpopulation diversity can be neglected and our model can be approximated by a population based model. We show that under a large population - large number of loci limit, the genetic distance between two subpopulations converges to a deterministic quantity that can asymptotically be expressed in terms of the hitting time between two random walks in the metapopulation graph. Our result shows that the genetic distance between two subpopulations does not only depend on the direct migration rates between them but on the whole metapopulation structure.