Abstract

In humans and many other species, recombination events cluster in narrow and short-lived hot spots distributed across the genome, whose location is determined by the Zn-finger protein PRDM9. To explain these fast evolutionary dynamics, an intra-genomic Red Queen model has been proposed, based on the interplay between two antagonistic forces: biased gene conversion, mediated by double-strand breaks, resulting in hot-spot extinction, followed by positive selection favouring new PRDM9 alleles recognizing new sequence motifs. Thus far, however, this Red Queen model has not been formalized as a quantitative population-genetic model, fully accounting for the intricate interplay between biased gene conversion, mutation, selection, demography and genetic diversity at the PRDM9 locus. Here, we explore the population genetics of the Red Queen model of recombination. A Wright–Fisher simulator was implemented, allowing exploration of the behaviour of the model (mean equilibrium recombination rate, diversity at the PRDM9 locus or turnover rate) as a function of the parameters (effective population size, mutation and erosion rates). In a second step, analytical results based on self-consistent mean-field approximations were derived, reproducing the scaling relations observed in the simulations. Empirical fit of the model to current data from the mouse suggests both a high mutation rate at PRDM9 and strong biased gene conversion on its targets.This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’.

Highlights

  • In mammals, as in many other species, meiotic recombination events are not uniformly distributed along chromosomes

  • Hot spots are not conserved between humans and chimps [5,6,7], nor between mouse subspecies [8], suggesting that recombination landscapes are highly dynamic

  • We provide a general overview of the behaviour of the Red Queen model in different parameter regimes

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Summary

Introduction

As in many other species, meiotic recombination events are not uniformly distributed along chromosomes. EÀac dc: In addition, as we assume that conversion strength and recombination rates are proportional, the rate of erosion for the fraction of hot spots recombining at rate c decays at a rate proportional to c, i.e. Altogether, the model effectively depends on four parameters: the effective population size Ne, the erosion rate vg, the mutation rate u at the PRDM9 locus and the parameter of the fitness function (or fitness parameter), which is either a (under the powerlaw fitness function) or b (when using the exponential fitness function). To explore the behaviour of the model as a function of the parameters, several summary statistics were considered These statistics are meant to capture key features of the Red Queen dynamics: the diversity at the PRDM9 locus, the mean recombination rate over the population at stationarity and the time of turnover of the genetic diversity at the PRDM9 locus (or, equivalently, the time of turnover of recombination landscapes).

Results
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Comparing analytical approximations with simulation results
Scaling of the model allowing for variation in hot-spot strength
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Discussion
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