Matching-allele Model Research Articles

The maintenance of genetic diversity under host-parasite coevolution in finite, structured populations.

As a corollary to the Red Queen hypothesis, host-parasite coevolution has been hypothesized to maintain genetic variation in both species. Recent theoretical work, however, suggests that reciprocal natural selection alone is insufficient to maintain variation at individual loci. As highlighted by our brief review of the theoretical literature, models of host-parasite coevolution often vary along multiple axes (e.g. inclusion of ecological feedbacks or abiotic selection mosaics), complicating a comprehensive understanding of the effects of interacting evolutionary processes on diversity. Here we develop a series of comparable models to explore the effect of interactions between spatial structures and antagonistic coevolution on genetic diversity. Using a matching alleles model in finite populations connected by migration, we find that, in contrast to panmictic populations, coevolution in a spatially structured environment can maintain genetic variation relative to neutral expectations with migration alone. These results demonstrate that geographic structure is essential for understanding the effect of coevolution on biological diversity.

Human and pathogen genotype-by-genotype interactions in the light of coevolution theory.

Antagonistic coevolution (i.e., reciprocal adaptation and counter-adaptation) between hosts and pathogens has long been considered an important driver of genetic variation. However, direct evidence for this is still scarce, especially in vertebrates. The wealth of data on genetics of susceptibility to infectious disease in humans provides an important resource for understanding host-pathogen coevolution, but studies of humans are rarely framed in coevolutionary theory. Here, I review data from human host-pathogen systems to critically assess the evidence for a key assumption of models of host-pathogen coevolution-the presence of host genotype-by-pathogen genotype interactions (G×G). I also attempt to infer whether observed G×G fit best with "gene-for-gene" or "matching allele" models of coevolution. I find that there are several examples of G×G in humans (involving, e.g., ABO, HBB, FUT2, SLC11A1, and HLA genes) that fit assumptions of either gene-for-gene or matching allele models. This means that there is potential for coevolution to drive polymorphism also in humans (and presumably other vertebrates), but further studies are required to investigate how widespread this process is.

Multi-strain compatibility polymorphism between a parasite and its snail host, a neglected vector of schistosomiasis in Africa

Interactions between Schistosoma mansoni and its snail host are understood primarily through experimental work with one South American vector species, Biomphalaria glabrata. However, 90% of schistosomiasis transmission occurs in Africa, where a diversity of Biomphalaria species may serve as vectors. With the long-term goal of determining the genetic and ecological determinants of infection in African snail hosts, we developed genetic models of Biomphalaria sudanica, a principal vector in the African Great Lakes. We determined laboratory infection dynamics of two S. mansoni lines in four B. sudanica lines. We measured the effects of the following variables on infection success and the number of cercariae produced (infection intensity): (i) the combination of parasite and snail line; (ii) the dose of parasites; and (iii) the size of snail at time of exposure. We found one snail line to be almost completely incompatible with both parasite lines, while other snail lines showed a polymorphism in compatibility: compatible with one parasite line while incompatible with another. Interestingly, these patterns were opposite in some of the snail lines. The parasite-snail combination had no significant effect on the number of cercariae produced in a successful infection. Miracidia dose had a strong effect on infection status, in that higher doses led to a greater proportion of infected snails, but had no effect on infection intensity. In one of the snail-schistosome combinations, snail size at the time of exposure affected both infection status and cercarial production in that the smallest size class of snails (1.5–2.9 mm) had the highest infection rates, and produced the greatest number of cercariae, suggesting that immunity increases with age and development. The strongest predictor of the infection intensity was the size of snail at the time of shedding: 1 ​mm of snail growth equated to a 19% increase in cercarial production. These results strongly suggest that infection status is determined in part by the interaction between snail and schistosome genetic lines, consistent with a gene-for-gene or matching allele model. This foundational work provides rationale for determining the genetic interactions between African snails and schistosomes, which may be applied to control strategies.

Coevolution fails to maintain genetic variation in a host–parasite model with constant finite population size

Coevolutionary negative frequency-dependent selection has been hypothesized to maintain genetic variation in host and parasites. Despite the extensive literature pertaining to host–parasite coevolution, the temporal dynamics of genetic variation have not been examined in a matching-alleles model (MAM) with a finite population size relative to the expectation under neutral genetic drift alone. The dynamics of the MA coevolution in an infinite population, in fact, suggests that genetic variation in these coevolving populations behaves neutrally. By comparing host heterozygosity to the expectation in a single-species model of neutral genetic drift we find that while this is also largely true in finite populations two additional phenomena arise. First, reciprocal natural selection acting on stochastic perturbations in host and pathogen allele frequencies results in a slight increase or decrease in genetic variation depending on the parameter conditions. Second, following the fixation of an allele in the parasite, selection in the MAM becomes directional, which then rapidly erodes genetic variation in the host. Hence, rather than maintain it, we find that, on average, matching-alleles coevolution depletes genetic variation.

An alternative route of bacterial infection associated with a novel resistance locus in the Daphnia\u2013Pasteuria host\u2013parasite system

To understand the mechanisms of antagonistic coevolution, it is crucial to identify the genetics of parasite resistance. In the Daphnia magna–Pasteuria ramosa host–parasite system, the most important step of the infection process is the one in which P. ramosa spores attach to the host’s foregut. A matching-allele model (MAM) describes the host–parasite genetic interactions underlying attachment success. Here we describe a new P. ramosa genotype, P15, which, unlike previously studied genotypes, attaches to the host’s hindgut, not to its foregut. Host resistance to P15 attachment shows great diversity across natural populations. In contrast to P. ramosa genotypes that use foregut attachment, P15 shows some quantitative variation in attachment success and does not always lead to successful infections, suggesting that hindgut attachment represents a less-efficient infection mechanism than foregut attachment. Using a Quantitative Trait Locus (QTL) approach, we detect two significant QTLs in the host genome: one that co-localizes with the previously described D. magna PR locus of resistance to foregut attachment, and a second, major QTL located in an unlinked genomic region. We find no evidence of epistasis. Fine mapping reveals a genomic region, the D locus, of ~13 kb. The discovery of a second P. ramosa attachment site and of a novel host-resistance locus increases the complexity of this system, with implications for both for the coevolutionary dynamics (e.g., Red Queen and the role of recombination), and for the evolution and epidemiology of the infection process.

Joint coevolutionary–epidemiological models dampen Red Queen cycles and alter conditions for epidemics

Host–parasite interactions in the form of infectious diseases are a topic of interest in both evolutionary biology and public health. Both fields have relied on mathematical models to predict and understand the dynamics and consequences of these interactions. Yet few models explicitly incorporate both epidemiological and coevolutionary dynamics, allowing for genetic variation in both hosts and parasites. By comparing a matching-alleles model of coevolution, a susceptible–infected–recovered–susceptible compartmental model from epidemiology, and a combined coevolutionary–epidemiology model we assess the effect of the coevolutionary feedback on the epidemiological dynamics and vice versa. We find that Red-Queen cycles are not robust in an epidemiological framework and that coevolutionary interactions can alter the conditions under which epidemic cycles arise. Incorporating both explicit epidemiology and genetic diversity may have important implications for the maintenance of sexual reproduction as well as disease management.

Spatially induced nestedness in a neutral model of phage-bacteria networks.

Ecological networks, both displaying mutualistic or antagonistic interactions, seem to share common structural traits: the presence of nestedness and modularity. A variety of model approaches and hypothesis have been formulated concerning the significance and implications of these properties. In phage-bacteria bipartite infection networks, nestedness seems to be the rule in many different contexts. Modeling the coevolution of a diverse virus–host ensemble is a difficult task, given the dimensionality and multi parametric nature of a standard continuous approximation. Here, we take a different approach, by using a neutral, toy model of host–phage interactions on a spatial lattice. Each individual is represented by a bit string (a digital genome) but all strings in each class (i.e. hosts or phages) share the same sets of parameters. A matching allele model of phage-virus recognition rule is enough to generate a complex, diverse ecosystem with heterogeneous patterns of interaction and nestedness, provided that interactions take place under a spatially constrained setting. It is found that nestedness seems to be an emergent property of the co-evolutionary dynamics. Our results indicate that the enhanced diversity resulting from localized interactions strongly promotes the presence of nested infection matrices.

Human Management of a Wild Plant Modulates the Evolutionary Dynamics of a Gene Determining Recessive Resistance to Virus Infection.

This work analyses the genetic variation and evolutionary patterns of recessive resistance loci involved in matching-allele (MA) host-pathogen interactions, focusing on the pvr2 resistance gene to potyviruses of the wild pepper Capsicum annuum glabriusculum (chiltepin). Chiltepin grows in a variety of wild habitats in Mexico, and its cultivation in home gardens started about 25 years ago. Potyvirus infection of Capsicum plants requires the physical interaction of the viral VPg with the pvr2 product, the translation initiation factor eIF4E1. Mutations impairing this interaction result in resistance, according to the MA model. The diversity of pvr2/eIF4E1 in wild and cultivated chiltepin populations from six biogeographical provinces in Mexico was analysed in 109 full-length coding sequences from 97 plants. Eleven alleles were found, and their interaction with potyvirus VPg in yeast-two-hybrid assays, plus infection assays of plants, identified six resistance alleles. Mapping resistance mutations on a pvr2/eIF4E1 model structure showed that most were around the cap-binding pocket and strongly altered its surface electrostatic potential, suggesting resistance-associated costs due to functional constraints. The pvr2/eIF4E1 phylogeny established that susceptibility was ancestral and resistance was derived. The spatial structure of pvr2/eIF4E1 diversity differed from that of neutral markers, but no evidence of selection for resistance was found in wild populations. In contrast, the resistance alleles were much more frequent, and positive selection stronger, in cultivated chiltepin populations, where diversification of pvr2/eIF4E1 was higher. This analysis of the genetic variation of a recessive resistance gene involved in MA host-pathogen interactions in populations of a wild plant show that evolutionary patterns differ according to the plant habitat, wild or cultivated. It also demonstrates that human management of the plant population has profound effects on the diversity and the evolution of the resistance gene, resulting in the selection of resistance alleles.

Coevolutionary Epidemiology: Disease Spread, Local Adaptation, and Sex.

How does evolution in parasite populations affect the rate of disease spread? In the present study, I derived the mean reproductive rate ([Formula: see text]) for a genetically diverse parasite population that is evolving with a similarly diverse host population. Assuming a matching-alleles model, I found that [Formula: see text] is a positive function of the covariance between the frequencies of "matching" host and parasite genotypes. Computer simulations further showed that evolution in the parasite population tends to increase the covariance, which can lead to epidemiological feedbacks. However, the covariances can also become negative during counteradaptation by the host, leading to oscillatory dynamics in host and parasite fitness. Nonetheless, when parasite-mediated selection is strong, the covariance is positive on average, which facilitates the spread of disease. Positive covariances may also underlie patterns of local adaptation in parasite populations and increase the selective advantage of cross-fertilization in host populations.

Epidemiological and Evolutionary Outcomes in Gene-for-Gene and Matching Allele Models.

Gene-for-gene (GFG) and matching-allele (MA) models are qualitatively different paradigms for describing the outcome of genetic interactions between hosts and pathogens. The GFG paradigm was largely built on the foundations of Flor’s early work on the flax–flax rust interaction and is based on the concept of genetic recognition leading to incompatible disease outcomes, typical of host immune recognition. In contrast, the MA model is based on the assumption that genetic recognition leads to compatible interactions, which can result when pathogens require specific host factors to cause infection. Results from classical MA and GFG models have led to important predictions regarding various coevolutionary phenomena, including the role of fitness costs associated with resistance and infectivity, the distribution of resistance genes in wild populations, patterns of local adaptation and the evolution and maintenance of sexual reproduction. Empirical evidence (which we review briefly here), particularly from recent molecular advances in understanding of the mechanisms that determine the outcome of host–pathogen encounters, suggests considerable variation in specific details of the functioning of interactions between hosts and pathogens, which may contain elements of both models. In this regard, GFG and MA scenarios likely represent endpoints of a continuum of potentially more complex interactions that occur in nature. Increasingly, this has been recognized in theoretical studies of coevolutionary processes in plant host–pathogen and animal host-parasite associations (e.g., departures from strict GFG/MA assumptions, diploid genetics, multi-step infection processes). However, few studies have explored how different genetic assumptions about host resistance and pathogen infectivity might impact on disease epidemiology or pathogen persistence within and among populations. Here, we use spatially explicit simulations of the basic MA and GFG scenarios to highlight qualitative differences between these scenarios with regard to patterns of disease and impacts on host demography. Given that such impacts drive evolutionary trajectories, future theoretical advances that aim to capture more complex genetic scenarios should explicitly address the interaction between epidemiology and different models of host–pathogen interaction genetics.

Host-parasite coevolution in populations of constant and variable size.

BackgroundThe matching-allele and gene-for-gene models are widely used in mathematical approaches that study the dynamics of host-parasite interactions. Agrawal and Lively (Evolutionary Ecology Research 4:79–90, 2002) captured these two models in a single framework and numerically explored the associated time discrete dynamics of allele frequencies.ResultsHere, we present a detailed analytical investigation of this unifying framework in continuous time and provide a generalization. We extend the model to take into account changing population sizes, which result from the antagonistic nature of the interaction and follow the Lotka-Volterra equations. Under this extension, the population dynamics become most complex as the model moves away from pure matching-allele and becomes more gene-for-gene-like. While the population densities oscillate with a single oscillation frequency in the pure matching-allele model, a second oscillation frequency arises under gene-for-gene-like conditions. These observations hold for general interaction parameters and allow to infer generic patterns of the dynamics.ConclusionOur results suggest that experimentally inferred dynamical patterns of host-parasite coevolution should typically be much more complex than the popular illustrations of Red Queen dynamics. A single parasite that infects more than one host can substantially alter the cyclic dynamics.

Host-parasite coevolutionary dynamics with generalized success/failure infection genetics.

Host-parasite infection genetics can be more complex than envisioned by classic models such as the gene-for-gene or matching-allele models. By means of a mathematical model, I investigate the coevolutionary dynamics arising from a large set of generalized models of infection genetics in which hosts are either fully resistant or fully susceptible to a parasite, depending on the genotype of both individuals. With a single diploid interaction locus in the hosts, many of the infection genetic models produce stable or neutrally stable genotype polymorphisms. However, only a few models, which are all different versions of the matching-allele model, lead to sustained cycles of genotype frequency fluctuations in both interacting species ("Red Queen" dynamics). By contrast, with two diploid interaction loci in the hosts, many infection genetics models that cannot be classified as one of the standard infection genetics models produce Red Queen dynamics. Sexual versus asexual reproduction and, in the former case, the rate of recombination between the interaction loci have a large impact on whether Red Queen dynamics arise from a given infection genetics model. This may have interesting but as yet unexplored implications with respect to the Red Queen hypothesis for the evolution of sex.

Host-parasite evolution in male-haploid hosts: an individual based network model

Host-parasite co-evolution is a key component of the Red Queen Hypothesis (RQH). The RQH currently being one of the main hypotheses describing the evolution of sex and recombination. However, most analyses in this area have either ignored parasite transmission or included it either with mean field or simple frequency based models. Moreover models have rarely addressed the issue of male haploid species. We here use agent based models to qualify the interactions between host- and parasite-based transmission parameters and virulence comparing diploid with male-haploid species. We found diploid hosts to have a higher fitness under the inverse matching allele mode compared to male haplodiploid hosts which in turn have a higher fitness under the matching allele model . Selection for recombination was rare but whenever selection for recombination was evident (<6.6 %), the resulting recombination rates were both consistently higher and more frequent in male haploids.

Interaction patterns between potato virus Y and eIF4E-mediated recessive resistance in the Solanaceae.

The structural pattern of infectivity matrices, which contains infection data resulting from inoculations of a set of hosts by a set of parasites, is a key parameter for our understanding of biological interactions and their evolution. This pattern determines the evolution of parasite pathogenicity and host resistance, the spatiotemporal distribution of host and parasite genotypes, and the efficiency of disease control strategies. Two major patterns have been proposed for plant-virus genotype infectivity matrices. In the gene-for-gene model, infectivity matrices show a nested pattern, where the host ranges of specialist virus genotypes are subsets of the host ranges of less specialized viruses. In contrast, in the matching-allele (MA) model, each virus genotype is specialized to infect one (or a small set of) host genotype(s). The corresponding infectivity matrix shows a modular pattern where infection is frequent for plants and viruses belonging to the same module but rare for those belonging to different modules. We analyzed the structure of infectivity matrices between Potato virus Y (PVY) and plant genotypes in the family Solanaceae carrying different eukaryotic initiation factor 4E (eIF4E)-coding alleles conferring recessive resistance. Whereas this system corresponds mechanistically to an MA model, the expected modular pattern was rejected based on our experimental data. This was mostly because PVY mutations involved in adaptation to a particular plant genotype displayed frequent pleiotropic effects, conferring simultaneously an adaptation to additional plant genotypes with different eIF4E alleles. Such effects should be taken into account for the design of strategies of sustainable control of PVY through plant varietal mixtures or rotations. The interaction pattern between host and virus genotypes has important consequences on their respective evolution and on issues regarding the application of disease control strategies. We found that the structure of the interaction between Potato virus Y (PVY) variants and host plants in the family Solanaceae departs significantly from the current model of interaction considered for these organisms because of frequent pleiotropic effects of virus mutations. These mutational effects allow the virus to expand rapidly its range of host plant genotypes, make it very difficult to predict the effects of mutations in PVY infectivity factors, and raise concerns about strategies of sustainable management of plant genetic resistance to viruses.

How specificity and epidemiology drive the coevolution of static trait diversity in hosts and parasites.

There is typically considerable variation in the level of infectivity of parasites and the degree of resistance of hosts within populations. This trait variation is critical not only to the evolutionary dynamics but also to the epidemiology, and potentially the control of infectious disease. However, we lack an understanding of the processes that generate and maintain this trait diversity. We examine theoretically how epidemiological feedbacks and the characteristics of the interaction between host types and parasites strains determine the coevolution of host–parasite diversity. The interactions include continuous characterizations of the key phenotypic features of classic gene-for-gene and matching allele models. We show that when there are costs to resistance in the hosts and infectivity in the parasite, epidemiological feedbacks may generate diversity but this is limited to dimorphism, often of extreme types, in a broad range of realistic infection scenarios. For trait polymorphism, there needs to be both specificity of infection between host types and parasite strains as well as incompatibility between particular strains and types. We emphasize that although the high specificity is well known to promote temporal “Red Queen” diversity, it is costs and combinations of hosts and parasites that cannot infect that will promote static trait diversity.

Allopolyploidy and the evolution of plant virus resistance.

BackgroundThe relationship between allopolyploidy and plant virus resistance is poorly understood. To determine the relationship of plant evolutionary history and basal virus resistance, a panel of Nicotiana species from diverse geographic regions and ploidy levels was assessed for resistance to non-coevolved viruses from the genus Nepovirus, family Secoviridae. The heritability of resistance was tested in a panel of synthetic allopolyploids. Leaves of different positions on each inoculated plant were tested for virus presence and a subset of plants was re-inoculated and assessed for systemic recovery.ResultsDepending on the host-virus combination, plants displayed immunity, susceptibility or intermediate levels of resistance. Synthetic allopolyploids showed an incompletely dominant resistance phenotype and manifested systemic recovery. Plant ploidy was weakly negatively correlated with virus resistance in Nicotiana species, but this trend did not hold when synthetic allopolyploids were taken into account. Furthermore, a relationship between resistance and geographical origin was observed.ConclusionThe gradients of resistance and virulence corresponded to a modified matching allele model of resistance. Intermediate resistance responses of allopolyploids corresponded with a model of multi-allelic additive resistance. The variable virus resistance of extant allopolyploids suggested that selection-based mechanisms surpass ploidy with respect to evolution of basal resistance to viruses.

A Matching-Allele Model Explains Host Resistance to Parasites

The maintenance of genetic variation and sex despite its costs has long puzzled biologists. A popular idea, the Red Queen Theory, is that under rapid antagonistic coevolution between hosts and their parasites, the formation of new rare host genotypes through sex can be advantageous as it creates host genotypes to which the prevailing parasite is not adapted. For host-parasite coevolution to lead to an ongoing advantage for rare genotypes, parasites should infect specific host genotypes and hosts should resist specific parasite genotypes. The most prominent genetics capturing such specificity are matching-allele models (MAMs), which have the key feature that resistance for two parasite genotypes can reverse by switching one allele at one host locus. Despite the lack of empirical support, MAMs have played a central role in the theoretical development of antagonistic coevolution, local adaptation, speciation, and sexual selection. Using genetic crosses, we show that resistance of the crustacean Daphnia magna against the parasitic bacterium Pasteuria ramosa follows a MAM. Simulation results show that the observed genetics can explain the maintenance of genetic variation and contribute to the maintenance of sex in the facultatively sexual host as predicted by the Red Queen Theory.

The Red Queen Process does not Select for High Recombination Rates in Haplodiploid Hosts

One of the main competing theories to describe the evolution of recombination is the Red Queen hypothesis (RQH). Presently, many theoretical analyses of the RQH typically examine fitness interactions in host-parasite frameworks. Less emphasis has been placed on understanding the impact of host ploidy in these systems. In this study, we look to investigate the high observed rates of recombination observed in two common haplodiploid species (Apis mellifera and Bombus terrestris). We compared haplodiploid to diploid host populations under infection with haploid asexual parasites, using a matching allele model. Results from a simulation analysis showed that the Red Queen does not run in haplodiploid hosts and is therefore, probably not responsible for the high recombination rates observed so far in haplodiploid hosts.

What Can Phages Tell Us about Host-Pathogen Coevolution?

The outcomes of host-parasite interactions depend on the coevolutionary forces acting upon them, but because every host-parasite relation is enmeshed in a web of biotic and abiotic interactions across a heterogeneous landscape, host-parasite coevolution has proven difficult to study. Simple laboratory phage-bacteria microcosms can ameliorate this difficulty by allowing controlled, well-replicated experiments with a limited number of interactors. Genetic, population, and life history data obtained from these studies permit a closer examination of the fundamental correlates of host-parasite coevolution. In this paper, I describe the results of phage-bacteria coevolutionary studies and their implications for the study of host-parasite coevolution. Recent experimental studies have confirmed phage-host coevolutionary dynamics in the laboratory and have shown that coevolution can increase parasite virulence, specialization, adaptation, and diversity. Genetically, coevolution frequently proceeds in a manner best described by the Gene for Gene model, typified by arms race dynamics, but certain contexts can result in Red Queen dynamics according to the Matching Alleles model. Although some features appear to apply only to phage-bacteria systems, other results are broadly generalizable and apply to all instances of antagonistic coevolution. With laboratory host-parasite coevolutionary studies, we can better understand the perplexing array of interactions that characterize organismal diversity in the wild.

Tunisian Potato virus Y isolates with unnecessary pathogenicity towards pepper: support for the matching allele model in eIF4E resistance–potyvirus interactions

The pathogenic properties of Potato virus Y (PVY; genus Potyvirus, family Potyviridae) isolates collected in naturally infected pepper (Capsicum annuum) fields in Tunisia were evaluated against recessive resistance alleles at the pvr2 locus of pepper. Two pathotypes were observed. Pathotype (0,1,3) isolates were able to infect plants carrying the susceptibility allele pvr2+, together with pvr21/pvr21 and pvr23/pvr23 plants, but not pvr22/pvr22 plants. Pathotype (0) isolates were only able to infect pvr2+/pvr2+ plants. On the other hand, sequence data and phylogenetic analyses revealed three major groups of isolates, each characterized by particular amino acid residues in the central part of the VPg, the pathogenicity factor towards pvr2. Correspondence between pathogenic properties and phylogeny suggested a single evolutionary step for pathogenicity towards the pvr21 and pvr23 resistances, possibly under the selective pressure of pvr21. Indeed, 23% of the pepper plants in this area were shown to carry the pvr21 resistance, while pvr23 was not detected. The data suggested that pathogenicity towards pvr21 and pvr23 were not costly for PVY to infect susceptible pepper genotypes and supported the matching allele model for pepper–PVY interactions.