Erratum: Rybnikov et al. Selection for Plastic, Pathogen-Inducible Recombination in a Red Queen Model with Diploid Antagonists. Pathogens 2021, 10, 898

In the original article, there was a mistake published in Figure 3 [...]

Selection for Plastic, Pathogen-Inducible Recombination in a Red Queen Model with Diploid Antagonists

Antagonistic interactions and co-evolution between a host and its parasite are known to cause oscillations in the population genetic structure of both species (Red Queen dynamics). Potentially, such oscillations may select for increased sex and recombination in the host, although theoretical models suggest that this happens under rather restricted values of selection intensity, epistasis, and other parameters. Here, we explore a model in which the diploid parasite succeeds to infect the diploid host only if their phenotypes at the interaction-mediating loci match. Whenever regular oscillations emerge in this system, we test whether plastic, pathogen-inducible recombination in the host can be favored over the optimal constant recombination. Two forms of the host recombination dependence on the parasite pressure were considered: either proportionally to the risk of infection (prevention strategy) or upon the fact of infection (remediation strategy). We show that both forms of plastic recombination can be favored, although relatively infrequently (up to 11% of all regimes with regular oscillations, and up to 20% of regimes with obligate parasitism). This happens under either strong overall selection and high recombination rate in the host, or weak overall selection and low recombination rate in the host. In the latter case, the system’s dynamics are considerably more complex. The prevention strategy is favored more often than the remediation one. It is noteworthy that plastic recombination can be favored even when any constant recombination is rejected, making plasticity an evolutionary mechanism for the rescue of host recombination.

The evolutionary advantage of condition-dependent recombination in a Red Queen model with diploid antagonists

Antagonistic interaction, like those between a host and its parasite, are known to cause oscillations in genetic structure of both species, usually referred to as Red Queen dynamics (RQD). The RQD is believed to be a plausible explanation for the evolution of sex/recombination, although numerous theoretical models showed that this may happen only under rather restricted parameter values (selection intensity, epistasis, etc.). Here, we consider two diploid antagonists, each with either two or three selected loci; the interaction is based on matching phenotypes model. We use the RQD, whenever it emerges in this system, as a substrate to examine the evolution of one recombination feature, condition dependence in diploids, which still remains an underexplored question. We consider several forms of condition-dependent recombination, with recombination rates in the host being sensitive either to the parasite’s mean fitness, or to the host’s infection status, or to the host’s genotype fitness. We show that all form of condition-dependent recombination can be favored over the corresponding optimal constant recombination rate, even including situations in which the optimal constant recombination rate is zero.

The Red Queen model of recombination hot-spot evolution: a theoretical investigation

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’.