Stability of genetic polymorphism in host-parasite interactions

Inference of Host-Pathogen Interaction Matrices from Genome-Wide Polymorphism Data

Host-pathogen coevolution is defined as the reciprocal evolutionary changes in both species due to genotype × genotype (G×G) interactions at the genetic level determining the outcome and severity of infection. While co-analyses of hosts and pathogen genomes (co-genome-wide association studies) allow us to pinpoint the interacting genes, these do not reveal which host genotype(s) is/are resistant to which pathogen genotype(s). The knowledge of this so-called infection matrix is important for agriculture and medicine. Building on established theories of host-pathogen interactions, we here derive four novel indices capturing the characteristics of the infection matrix. These indices can be computed from full genome polymorphism data of randomly sampled uninfected hosts, as well as infected hosts and their pathogen strains. We use these indices in an approximate Bayesian computation method to pinpoint loci with relevant G×G interactions and to infer their underlying interaction matrix. In a combined single nucleotide polymorphism dataset of 451 European humans and their infecting hepatitis C virus (HCV) strains and 503 uninfected individuals, we reveal a new human candidate gene for resistance to HCV and new virus mutations matching human genes. For two groups of significant human-HCV (G×G) associations, we infer a gene-for-gene infection matrix, which is commonly assumed to be typical of plant-pathogen interactions. Our model-based inference framework bridges theoretical models of G×G interactions with host and pathogen genomic data. It, therefore, paves the way for understanding the evolution of key G×G interactions underpinning HCV adaptation to the European human population after a recent expansion.

The impact of sterility-mortality tolerance and recovery-transmission trade-offs on host-parasite coevolution

Understanding the coevolutionary dynamics of hosts and their parasites remains a major focus of much theoretical literature. Despite empirical evidence supporting the presence of sterility-mortality tolerance trade-offs in hosts and recovery-transmission trade-offs in parasites, none of the current models have explored the potential outcomes when both trade-offs are considered within a coevolutionary framework. In this study, we consider a model where the host evolves sterility tolerance at the cost of increased mortality and the parasite evolves higher transmission rate at the cost of increased recovery rate (reduced infection duration), and use adaptive dynamics to predict the coevolutionary outcomes under such trade-off assumptions. We particularly aim to understand how our coevolutionary dynamics compare with single species evolutionary models. We find that evolutionary branching in the host can drive the parasite population to branch, but that cycles in the population dynamics can prevent the coexisting strains from reaching their extremes. We also find that varying crowding does not impact the recovery rate when only the parasite evolves, yet coevolution reduces recovery as crowding intensifies. We conclude by discussing how different host and parasite trade-offs shape coevolutionary outcomes, underscoring the pivotal role of trade-offs in coevolution.

How do fluctuating ecological dynamics impact the evolution of hosts and parasites?

Theoretical models of the evolution of parasites and their hosts have shaped our understanding of infectious disease dynamics for over 40 years. Many theoretical models assume that the underlying ecological dynamics are at equilibrium or constant, yet we know that in a great many systems there are fluctuations in the ecological dynamics owing to a variety of intrinsic or extrinsic factors. Here, we discuss the challenges presented when modelling evolution in systems with fluctuating ecological dynamics and summarize the main approaches that have been developed to study host-parasite evolution in such systems. We provide an in-depth guide to one of the methods by applying it to two worked examples of host evolution that have not previously been studied in the literature: when cycles occur owing to seasonal forcing in competition, and when the presence of a free-living parasite causes cycles, with accompanying interactive Python code provided. We review the findings of studies that have explored host-parasite evolution when ecological dynamics fluctuate, and point to areas of future research. Throughout we stress the importance of feedbacks between the ecological and evolutionary dynamics in driving the outcomes of infectious disease systems. This article is part of the theme issue 'Infectious disease ecology and evolution in a changing world'.

Studying Wild Plant Pathosystems to Understand Crop Plant Pathosystems: Status, Gaps, Challenges, and Perspectives

Phytopathology is a highly complex scientific discipline. Initially, its focus was on the study of plant-pathogen interactions in agricultural and forestry production systems. Host-pathogen interactions in natural plant communities were generally overlooked until the 1970s when plant pathologists and evolutionary biologists started to take an interest in these interactions, and their dynamics in natural plant populations, communities, and ecosystems. This article introduces the general principles of plant pathosystems, provides a basic critical overview of current knowledge of host-pathogen interactions in natural plant pathosystems, and shows how this knowledge is important for future developments in plant pathology especially as it applies in cropping systems, ecology, and evolutionary biology. Plant pathosystems can be further divided according to the structure and origin of control, as autonomous (wild plant pathosystems, WPPs) or deterministic (crop plant pathosystems, CPPs). WPPs are characterized by the disease triangle and closed-loop (feedback) controls, and CPPs are characterized by the disease tetrahedron and open-loop (non-feedback) controls. Basic general, ecological, genetic, and population structural and functional differences between WPPs and CPPs are described. It is evident that we lack a focus on long-term observations and research of diseases and their dynamics in natural plant populations, metapopulations, communities, ecosystems, and biomes, as well as their direct or indirect relationships to CPPs. Differences and connections between WPPs and CPPs, and why, and how, these are important for agriculture varies. WPP and CPP may be linked by strong biological interactions, especially where the pathogen is in common. This is demonstrated through a case study of lettuce (Lactuca spp., L. serriola and L. sativa) and lettuce downy mildew (Bremia lactucae). In other cases where there is no such direct biological linkage, the study of WPPs can provide a deeper understanding of how ecology and genetics interacts to drive disease through time. These studies provide insights into ways in which farming practices may be changed to limit disease development. Research on interactions between pathosystems, the "cross-talk" of WPPs and CPPs, is still very limited and, as shown in interactions between wild and cultivated Lactuca spp.-B. lactucae associations, can be highly complex. The implications and applications of this knowledge in plant breeding, crop management, and disease control measures are considered. This review concludes with a discussion of theoretical, general and specific aspects, challenges and limits of future WPP research, and application of their results in agriculture.

How the epidemiology of disease-resistant and disease-tolerant varieties affects grower behaviour

Population-scale effects of resistant or tolerant crop varieties have received little consideration from epidemiologists. When growers deploy tolerant crop, population-scale disease pressures are often unaffected. This only benefits growers using tolerant varieties, selfishly decreasing yields for others. However, resistant crop can reduce disease pressure for all. We coupled an epidemiological model with game theory to understand how this affects uptake of control. Each time a grower plants a new crop, they must decide whether to use an improved (i.e. tolerant/resistant) or unimproved variety. This decision is based on strategic-adaptive expectations in our model, with growers comparing last season's profit with an estimate of what is expected from the alternative crop. Despite the positive feedback loop promoting use of a tolerant variety whenever it is available, a mixed unimproved- and tolerant-crop equilibrium can persist. Tolerant crop can also induce bistability between a scenario in which all growers use tolerant crop and the disease-free equilibrium, where no growers do. However, due to 'free-riding' by growers of unimproved crop, resistant crop nearly always exists in a mixed equilibrium. This work highlights how growers respond to contrasting incentives caused by tolerant and resistant varieties, and the distinct effects on yields and population-scale deployment.

Host mixtures for plant disease control: Benefits from pathogen selection and immune priming

Multiline and cultivar mixtures are highly effective methods for agroecological plant disease control. Priming-induced cross protection, occurring when plants are challenged by avirulent pathogen genotypes and resulting in increased resistance to subsequent infection by virulent ones, is one critical key to their lasting performance against polymorphic pathogen populations. Strikingly, this mechanism was until recently absent from mathematical models aiming at designing optimal host mixtures. We developed an epidemiological model to explore the effect of host mixtures composed of variable numbers of single-resistance cultivars on the equilibrium prevalence of the disease caused by pathogen populations polymorphic for virulence complexity. This model shows that a relatively large amount of resistance genes must be deployed to achieve low disease prevalence, as pathogen competition in mixtures tends to select for intermediate virulence complexity. By contrast, priming significantly reduces the number of plant genotypes needed to drop disease prevalence below an acceptable threshold. Given the limited availability of resistance genes in cultivars, this mechanism of plant immunity should be assessed when designing host mixtures.

Genetic diversity and disease: The past, present, and future of an old idea

Why do infectious diseases erupt in some host populations and not others? This question has spawned independent fields of research in evolution, ecology, public health, agriculture, and conservation. In the search for environmental and genetic factors that predict variation in parasitism, one hypothesis stands out for its generality and longevity: genetically homogeneous host populations are more likely to experience severe parasitism than genetically diverse populations. In this perspective piece, I draw on overlapping ideas from evolutionary biology, agriculture, and conservation to capture the far-reaching implications of the link between genetic diversity and disease. I first summarize the development of this hypothesis and the results of experimental tests. Given the convincing support for the protective effect of genetic diversity, I then address the following questions: (1) Where has this idea been put to use, in a basic and applied sense, and how can we better use genetic diversity to limit disease spread? (2) What new hypotheses does the established disease-diversity relationship compel us to test? I conclude that monitoring, preserving, and augmenting genetic diversity is one of our most promising evolutionarily informed strategies for buffering wild, domesticated, and human populations against future outbreaks.

Coevolutionary theory of hosts and parasites

Host and parasite evolution are closely intertwined, with selection for adaptations and counter-adaptations forming a coevolutionary feedback loop. Coevolutionary dynamics are often difficult to intuit due to these feedbacks and are hard to demonstrate empirically in most systems. Theoretical models have therefore played a crucial role in shaping our understanding of host-parasite coevolution. Theoretical models vary widely in their assumptions, approaches and aims, and such variety makes it difficult, especially for non-theoreticians and those new to the field, to: (1) understand how model approaches relate to one another; (2) identify key modelling assumptions; (3) determine how model assumptions relate to biological systems; and (4) reconcile the results of different models with contrasting assumptions. In this review, we identify important model features, highlight key results and predictions and describe how these pertain to model assumptions. We carry out a literature survey of theoretical studies published since the 1950s (n = 219 papers) to support our analysis. We identify two particularly important features of models that tend to have a significant qualitative impact on the outcome of host-parasite coevolution: population dynamics and the genetic basis of infection. We also highlight the importance of other modelling features, such as stochasticity and whether time proceeds continuously or in discrete steps, that have received less attention but can drastically alter coevolutionary dynamics. We finish by summarizing recent developments in the field, specifically the trend towards greater model complexity, and discuss likely future directions for research.

Major QTL confer race-nonspecific resistance in the co-evolved Cronartium quercuum f. sp. fusiforme-Pinus taeda pathosystem

Fusiform rust disease, caused by the endemic fungus Cronartium quercuum f. sp. fusiforme, is the most damaging disease affecting economically important pine species in the southeast United States. Unlike the major epidemics of agricultural crops, the co-evolved pine-rust pathosystem is characterized by steady-state dynamics and high levels of genetic diversity within environments. This poses a unique challenge and opportunity for the deployment of large-effect resistance genes. We used trait dissection to study the genetic architecture of disease resistance in two P. taeda parents that showed high resistance across multiple environments. Two mapping populations (full-sib families), each with ~1000 progeny, were challenged with a complex inoculum consisting of 150 pathogen isolates. High-density linkage mapping revealed three major-effect QTL distributed on two linkage groups. All three QTL were validated using a population of 2057 cloned pine genotypes in a 6-year-old multi-environmental field trial. As a complement to the QTL mapping approach, bulked segregant RNAseq analysis revealed a small number of candidate nucleotide binding leucine-rich repeat genes harboring SNP associated with disease resistance. The results of this study show that in P. taeda, a small number of major QTL can provide effective resistance against genetically diverse mixtures of an endemic pathogen. These QTL vary in their impact on disease liability and exhibit additivity in combination.

Genetic identity and genotype × genotype interactions between symbionts outweigh species level effects in an insect microbiome

Microbial symbionts often alter the phenotype of their host. Benefits and costs to hosts depend on many factors, including host genotype, symbiont species and genotype, and environmental conditions. Here, we present a study demonstrating genotype-by-genotype (G×G) interactions between multiple species of endosymbionts harboured by an insect, and the first to quantify the relative importance of G×G interactions compared with species interactions in such systems. In the most extensive study to date, we microinjected all possible combinations of five Hamiltonella defensa and five Fukatsuia symbiotica (X-type; PAXS) isolates into the pea aphid, Acyrthosiphon pisum. We applied several ecological challenges: a parasitoid wasp, a fungal pathogen, heat shock, and performance on different host plants. Surprisingly, genetic identity and genotype × genotype interactions explained far more of the phenotypic variation (on average 22% and 31% respectively) than species identity or species interactions (on average 12% and 0.4%, respectively). We determined the costs and benefits associated with co-infection, and how these compared to corresponding single infections. All phenotypes were highly reliant on individual isolates or interactions between isolates of the co-infecting partners. Our findings highlight the importance of exploring the eco-evolutionary consequences of these highly specific interactions in communities of co-inherited species.

Novel genomic approaches to study antagonistic coevolution between hosts and parasites

Host-parasite coevolution is ubiquitous, shaping genetic and phenotypic diversity and the evolutionary trajectory of interacting species. With the advances of high throughput sequencing technologies applicable to model and non-model organisms alike, it is now feasible to study in greater detail (a) the genetic underpinnings of coevolution, (b) the speed and type of dynamics at coevolving loci, and (c) the genomic consequences of coevolution. This review focuses on three recently developed approaches that leverage information from host and parasite full genome data simultaneously to pinpoint coevolving loci and draw inference on the coevolutionary history. First, co-genome-wide association study (co-GWAS) methods allow pinpointing the loci underlying host-parasite interactions. These methods focus on detecting associations between genetic variants and the outcome of experimental infection tests or on correlations between genomes of naturally infected hosts and their infecting parasites. Second, extensions to population genomics methods can detect genes under coevolution and infer the coevolutionary history, such as fitness costs. Third, correlations between host and parasite population size in time are indicative of coevolution, and polymorphism levels across independent spatially distributed populations of hosts and parasites can reveal coevolutionary loci and infer coevolutionary history. We describe the principles of these three approaches and discuss their advantages and limitations based on coevolutionary theory. We present recommendations for their application to various host (prokaryotes, fungi, plants, and animals) and parasite (viruses, bacteria, fungi, and macroparasites) species. We conclude by pointing out methodological and theoretical gaps to be filled to extract maximum information from full genome data and thereby to shed light on the molecular underpinnings of coevolution.

When Does Spatial Diversification Usefully Maximize the Durability of Crop Disease Resistance?

Maximizing the durability of crop disease resistance genes in the face of pathogen evolution is a major challenge in modern agricultural epidemiology. Spatial diversification in the deployment of resistance genes, where susceptible and resistant fields are more closely intermixed, is predicted to drive lower epidemic intensities over evolutionary timescales. This is due to an increase in the strength of dilution effects, caused by pathogen inoculum challenging host tissue to which it is not well-specialized. The factors that interact with and determine the magnitude of this spatial suppressive effect are not currently well understood, however, leading to uncertainty over the pathosystems where such a strategy is most likely to be cost-effective. We model the effect on landscape scale disease dynamics of spatial heterogeneity in the arrangement of fields planted with either susceptible or resistant cultivars, and the way in which this effect depends on the parameters governing the pathosystem of interest. Our multiseason semidiscrete epidemiological model tracks spatial spread of wild-type and resistance-breaking pathogen strains, and incorporates a localized reservoir of inoculum, as well as the effects of within and between field transmission. The pathogen dispersal characteristics, any fitness cost(s) of the resistance-breaking trait, the efficacy of host resistance, and the length of the timeframe of interest all influence the strength of the spatial diversification effect. A key result is that spatial diversification has the strongest beneficial effect at intermediate fitness costs of the resistance-breaking trait, an effect driven by a complex set of nonlinear interactions. On the other hand, however, if the resistance-breaking strain is not fit enough to invade the landscape, then a partially effective resistance gene can result in spatial diversification actually worsening the epidemic. These results allow us to make general predictions of the types of system for which spatial diversification is most likely to be cost-effective, paving the way for potential economic modeling and pathosystem specific evaluation. These results highlight the importance of studying the effect of genetics on landscape scale spatial dynamics within host-pathogen disease systems.[Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Inference of coevolutionary dynamics and parameters from host and parasite polymorphism data of repeated experiments

There is a long-standing interest in understanding host-parasite coevolutionary dynamics and associated fitness effects. Increasing amounts of genomic data for both interacting species offer a promising source to identify candidate loci and to infer the main parameters of the past coevolutionary history. However, so far no method exists to perform the latter. By coupling a gene-for-gene model with coalescent simulations, we first show that three types of biological costs, namely, resistance, infectivity and infection, define the allele frequencies at the internal equilibrium point of the coevolution model. These in return determine the strength of selective signatures at the coevolving host and parasite loci. We apply an Approximate Bayesian Computation (ABC) approach on simulated datasets to infer these costs by jointly integrating host and parasite polymorphism data at the coevolving loci. To control for the effect of genetic drift on coevolutionary dynamics, we assume that 10 or 30 repetitions are available from controlled experiments or several natural populations. We study two scenarios: 1) the cost of infection and population sizes (host and parasite) are unknown while costs of infectivity and resistance are known, and 2) all three costs are unknown while populations sizes are known. Using the ABC model choice procedure, we show that for both scenarios, we can distinguish with high accuracy pairs of coevolving host and parasite loci from pairs of neutrally evolving loci, though the statistical power decreases with higher cost of infection. The accuracy of parameter inference is high under both scenarios especially when using both host and parasite data because parasite polymorphism data do inform on costs applying to the host and vice-versa. As the false positive rate to detect pairs of genes under coevolution is small, we suggest that our method complements recently developed methods to identify host and parasite candidate loci for functional studies.

Neutral genomic signatures of host-parasite coevolution

Background

Coevolution is a selective process of reciprocal adaptation in hosts and parasites or in mutualistic symbionts. Classic population genetics theory predicts the signatures of selection at the interacting loci of both species, but not the neutral genome-wide polymorphism patterns. To bridge this gap, we build an eco-evolutionary model, where neutral genomic changes over time are driven by a single selected locus in hosts and parasites via a simple biallelic gene-for-gene or matching-allele interaction. This coevolutionary process may lead to cyclic changes in the sizes of the interacting populations.

Results

We investigate if and when these changes can be observed in the site frequency spectrum of neutral polymorphisms from host and parasite full genome data. We show that changes of the host population size are too smooth to be observable in its polymorphism pattern over the course of time. Conversely, the parasite population may undergo a series of strong bottlenecks occurring on a slower relative time scale, which may lead to observable changes in a time series sample. We also extend our results to cases with 1) several parasites per host accelerating relative time, and 2) multiple parasite generations per host generation slowing down rescaled time.

Conclusions

Our results show that time series sampling of host and parasite populations with full genome data are crucial to understand if and how coevolution occurs. This model provides therefore a framework to interpret and draw inference from genome-wide polymorphism data of interacting species.

Durability of Quantitative Resistance in Crops: Greater Than We Know?

Quantitative resistance (QR) to crop diseases has usually been much more durable than major-gene, effector-triggered resistance. It has been observed that the effectiveness of some QR has eroded as pathogens adapt to it, especially when deployment is extensive and epidemics occur regularly, but it generally declines more slowly than effector-triggered resistance. Changes in aggressiveness and specificity of diverse pathogens on cultivars with QR have been recorded, along with experimental data on fitness costs of pathogen adaptation to QR, but there is little information about molecular mechanisms of adaptation. Some QR has correlated or antagonistic effects on multiple diseases. Longitudinal data on cultivars' disease ratings in trials over several years can be used to assess the significance of QR for durable resistance in crops. It is argued that published data likely underreport the durability of QR, owing to publication bias. The implications of research on QR for plant breeding are discussed.

Immunogenetic response of the bananaquit in the face of malarial parasites

BACKGROUND

In the arms race between hosts and parasites, genes involved in the immune response are targets for natural selection. Toll-Like Receptor (TLR) genes play a role in parasite detection as part of the innate immune system whereas Major Histocompatibility Complex (MHC) genes encode proteins that display antigens as part of the vertebrate adaptive immune system. Thus, both gene families are under selection pressure from pathogens. The bananaquit (Coereba flaveola) is a passerine bird that is a common host of avian malarial parasites (Plasmodium sp. and Haemoproteus sp.). We assessed molecular variation of TLR and MHC genes in a wild population of bananaquits and identified allelic associations with resistance/susceptibility to parasitic infection to address hypotheses of avian immune response to haemosporidian parasites.

RESULTS

We found that allele frequencies are associated with infection status at the immune loci studied. A consistent general trend showed the infected groups possessed more alleles at lower frequencies, and exhibited unique alleles, compared to the uninfected group.

CONCLUSIONS

Our results support the theory of natural selection favoring particular alleles for resistance while maintaining overall genetic diversity in the population, a mechanism which has been demonstrated in some systems in MHC previously but understudied in TLRs.

Arms races with mitochondrial genome soft sweeps in a gynodioecious plant, Plantago lanceolata

Biological situations involving conflict can create arms race situations with repeated fixations of different functional variants, producing selective sweeps and lowering neutral diversity in genome regions linked to the functional locus. However, they can sometimes lead to balancing selection, potentially creating long coalescent times for sites with functionally different variants, and, if recombination occurs rarely, for extended haplotypes carrying such variants. We tested between these possibilities in a gynodioecious plant, Plantago lanceolata, in which cytoplasmic male-sterility factors conflict with nuclear restorers of male fertility. We find low mitochondrial diversity, which does not support very long-term coexistence of highly diverged mitochondrial haplotypes. Interestingly, however, we found a derived haplotype that is associated with male fertility in a restricted geographic region, and that has fixed differences from the ancestral sequence in several genes, suggesting that it did not arise very recently. Taken together, the results suggest arms race events that involved "soft" selective sweeps involving a moderately old-established haplotype, consistent with the frequency fluctuations predicted by theoretical models of gynodioecy.

Exploring the causes of small effective population sizes in cyst nematodes using artificial Globodera pallida populations

The effective size of a population is the size of an ideal population which would undergo genetic drift at the same rate as the real population. The balance between selection and genetic drift depends on the effective population size ( Ne), rather than the real numbers of individuals in the population ( N). The objectives of the present study were to estimate Ne in the potato cyst nematode Globodera pallida and to explore the causes of a low Ne/ N ratio in cyst nematodes using artificial populations. Using a temporal analysis of 24 independent populations, the median Ne was 58 individuals (min Ne = 25 and max Ne = 228). Ne is commonly lower than N but in the case of cyst nematodes, the Ne/ N ratio was extremely low. Using artificial populations showed that this low ratio did not result from migration, selection and overlapping generations, but could be explain by the fact that G. pallida populations deviate in structure from the assumptions of the ideal population by having unequal sex ratios, high levels of inbreeding and a high variance in family sizes. The consequences of a low Ne, resulting in a strong intensity of genetic drift, could be important for their control because G. pallida populations will have a low capacity to adapt to changing environments.

Intersexual conflict over seed size is stronger in more outcrossed populations of a mixed-mating plant

In polyandrous species, fathers benefit from attracting greater maternal investment toward their offspring at the expense of the offspring of other males, while mothers should usually allocate resources equally among offspring. This conflict can lead to an evolutionary arms race between the sexes, manifested through antagonistic genes whose expression in offspring depends upon the parent of origin. The arms race may involve an increase in the strength of maternally versus paternally derived alleles engaged in a "tug of war" over maternal provisioning or repeated "recognition-avoidance" coevolution where growth-enhancing paternally derived alleles evolve to escape recognition by maternal genes targeted to suppress their effect. Here, we develop predictions to distinguish between these two mechanisms when considering crosses among populations that have reached different equilibria in this intersexual arms race. We test these predictions using crosses within and among populations of Dalechampia scandens (Euphorbiaceae) that presumably have experienced different intensities of intersexual conflict, as inferred from their historical differences in mating system. In crosses where the paternal population was more outcrossed than the maternal population, hybrid seeds were larger than those normally produced in the maternal population, whereas when the maternal population was more outcrossed, hybrid seeds were smaller than normal. These results confirm the importance of mating systems in determining the intensity of intersexual conflict over maternal investment and provide strong support for a tug-of-war mechanism operating in this conflict. They also yield clear predictions for the fitness consequences of gene flow among populations with different mating histories.

Population genomics of bacterial host adaptation

Some bacteria can transfer to new host species, and this poses a risk to human health. Indeed, an estimated 60% of all human pathogens have originated from other animal species. Similarly, human-to-animal transitions are recognized as a major threat to sustainable livestock production, and emerging pathogens impose an increasing burden on crop yield and global food security. Recent advances in high-throughput sequencing technologies have enabled comparative genomic analyses of bacterial populations from multiple hosts. Such studies are providing new insights into the evolutionary processes that underpin the establishment of bacteria in new host niches. A better understanding of the genetic and mechanistic basis for bacterial host adaptation may reveal novel targets for controlling infection or inform the design of approaches to limit the emergence of new pathogens.

The Genome Biology of Effector Gene Evolution in Filamentous Plant Pathogens

Filamentous pathogens, including fungi and oomycetes, pose major threats to global food security. Crop pathogens cause damage by secreting effectors that manipulate the host to the pathogen's advantage. Genes encoding such effectors are among the most rapidly evolving genes in pathogen genomes. Here, we review how the major characteristics of the emergence, function, and regulation of effector genes are tightly linked to the genomic compartments where these genes are located in pathogen genomes. The presence of repetitive elements in these compartments is associated with elevated rates of point mutations and sequence rearrangements with a major impact on effector diversification. The expression of many effectors converges on an epigenetic control mediated by the presence of repetitive elements. Population genomics analyses showed that rapidly evolving pathogens show high rates of turnover at effector loci and display a mosaic in effector presence-absence polymorphism among strains. We conclude that effective pathogen containment strategies require a thorough understanding of the effector genome biology and the pathogen's potential for rapid adaptation.

Host-pathogen coevolution in the presence of predators: fluctuating selection and ecological feedbacks

Host-pathogen coevolution is central to shaping natural communities and is the focus of much experimental and theoretical study. For tractability, the vast majority of studies assume the host and pathogen interact in isolation, yet in reality, they will form one part of complex communities, with predation likely to be a particularly key interaction. Here, I present, to my knowledge, the first theoretical study to assess the impact of predation on the coevolution of costly host resistance and pathogen transmission. I show that fluctuating selection is most likely when predators selectively prey upon infected hosts, but that saturating predation, owing to large handling times, dramatically restricts the potential for fluctuations. I also show how host evolution may drive either enemy to extinction, and demonstrate that while predation selects for low host resistance and high pathogen infectivity, ecological feedbacks mean this results in lower infection rates when predators are present. I emphasize the importance of accounting for varying population sizes, and place the models in the context of recent experimental studies.

Host-parasite fluctuating selection in the absence of specificity

Fluctuating selection driven by coevolution between hosts and parasites is important for the generation of host and parasite diversity across space and time. Theory has focused primarily on infection genetics, with highly specific ‘matching-allele’ frameworks more likely to generate fluctuating selection dynamics (FSD) than ‘gene-for-gene’ (generalist–specialist) frameworks. However, the environment, ecological feedbacks and life-history characteristics may all play a role in determining when FSD occurs. Here, we develop eco-evolutionary models with explicit ecological dynamics to explore the ecological, epidemiological and host life-history drivers of FSD. Our key result is to demonstrate for the first time, to our knowledge, that specificity between hosts and parasites is not required to generate FSD. Furthermore, highly specific host–parasite interactions produce unstable, less robust stochastic fluctuations in contrast to interactions that lack specificity altogether or those that vary from generalist to specialist, which produce predictable limit cycles. Given the ubiquity of ecological feedbacks and the variation in the nature of specificity in host–parasite interactions, our work emphasizes the underestimated potential for host–parasite coevolution to generate fluctuating selection.

The ash dieback invasion of Europe was founded by two genetically divergent individuals

Accelerating international trade and climate change make pathogen spread an increasing concern. Hymenoscyphus fraxineus, the causal agent of ash dieback, is a fungal pathogen that has been moving across continents and hosts from Asian to European ash. Most European common ash trees (Fraxinus excelsior) are highly susceptible to H. fraxineus, although a minority (~5%) have partial resistance to dieback. Here, we assemble and annotate a H. fraxineus draft genome which approaches chromosome scale. Pathogen genetic diversity across Europe and in Japan, reveals a strong bottleneck in Europe, though a signal of adaptive diversity remains in key host interaction genes. We find that the European population was founded by two divergent haploid individuals. Divergence between these haplotypes represents the ancestral polymorphism within a large source population. Subsequent introduction from this source would greatly increase adaptive potential of the pathogen. Thus, further introgression of H. fraxineus into Europe represents a potential threat and Europe-wide biological security measures are needed to manage this disease.

Host-parasite coevolution can promote the evolution of seed banking as a bet-hedging strategy

Seed (egg) banking is a common bet-hedging strategy maximizing the fitness of organisms facing environmental unpredictability by the delayed emergence of offspring. Yet, this condition often requires fast and drastic stochastic shifts between good and bad years. We hypothesize that the host seed banking strategy can evolve in response to coevolution with parasites because the coevolutionary cycles promote a gradually changing environment over longer times than seed persistence. We study the evolution of host germination fraction as a quantitative trait using both pairwise competition and multiple mutant competition methods, while the germination locus can be genetically linked or unlinked with the host locus under coevolution. In a gene-for-gene model of coevolution, hosts evolve a seed bank strategy under unstable coevolutionary cycles promoted by moderate to high costs of resistance or strong disease severity. Moreover, when assuming genetic linkage between coevolving and germination loci, the resistant genotype always evolves seed banking in contrast to susceptible hosts. Under a matching-allele interaction, both hosts' genotypes exhibit the same seed banking strategy irrespective of the genetic linkage between loci. We suggest host-parasite coevolution as an additional hypothesis for the evolution of seed banking as a temporal bet-hedging strategy.

Species-specific genes under selection characterize the co-evolution of slavemaker and host lifestyles

BACKGROUND

The transition to a parasitic lifestyle entails comprehensive changes to the selective regime. In parasites, genes encoding for traits that facilitate host detection, exploitation and transmission should be under selection. Slavemaking ants are social parasites that exploit the altruistic behaviour of their hosts by stealing heterospecific host brood during raids, which afterwards serve as slaves in slavemaker nests. Here we search for evidence of selection in the transcriptomes of three slavemaker species and three closely related hosts. We expected selection on genes underlying recognition and raiding or defense behaviour. Analyses of selective forces in species with a slavemaker or host lifestyle allowed investigation into whether or not repeated instances of slavemaker evolution share the same genetic basis. To investigate the genetic basis of host-slavemaker co-evolution, we created orthologous clusters from transcriptome sequences of six Temnothorax ant species - three slavemakers and three hosts - to identify genes with signatures of selection. We further tested for functional enrichment in selected genes from slavemakers and hosts respectively and investigated which pathways the according genes belong to.

RESULTS

Our phylogenetic analysis, based on more than 5000 ortholog sequences, revealed sister species status for two slavemakers as well as two hosts, contradicting a previous phylogeny based on mtDNA. We identified 309 genes with signs of positive selection on branches leading to slavemakers and 161 leading to hosts. Among these were genes potentially involved in cuticular hydrocarbon synthesis, thus species recognition, and circadian clock functionality possibly explaining the different activity patterns of slavemakers and hosts. There was little overlap of genes with signatures of positive selection among species, which are involved in numerous different functions and different pathways.

CONCLUSIONS

We identified different genes, functions and pathways under positive selection in each species. These results point to species-specific adaptations rather than convergent trajectories during the evolution of the slavemaker and host lifestyles suggesting that the evolution of parasitism, even in closely related species, may be achieved in diverse ways.

Modification of meiotic recombination by natural variation in plants

Meiosis is a specialized cell division that produces haploid gametes required for sexual reproduction. During the first meiotic division, homologous chromosomes pair and undergo reciprocal crossing over, which recombines linked sequence variation. Meiotic recombination frequency varies extensively both within and between species. In this review, we will examine the molecular basis of meiotic recombination rate variation, with an emphasis on plant genomes. We first consider cis modification caused by polymorphisms at the site of recombination, or elsewhere on the same chromosome. We review cis effects caused by mismatches within recombining joint molecules, the effect of structural hemizygosity, and the role of specific DNA sequence motifs. In contrast, trans modification of recombination is exerted by polymorphic loci encoding diffusible molecules, which are able to modulate recombination on the same and/or other chromosomes. We consider trans modifiers that act to change total recombination levels, hotspot locations, or interactions between homologous and homeologous chromosomes in polyploid species. Finally, we consider the significance of genetic variation that modifies meiotic recombination for adaptation and evolution of plant species.

Evolutionary dynamics of interactions between plants and their enemies: comparison of herbivorous insects and pathogens

Plants colonized land over 400 million years ago. Shortly thereafter, organisms began to consume terrestrial plant tissue as a nutritional resource. Most plant enemies are plant pathogens or herbivores, and they impose natural selection for plants to evolve defenses. These traits generate selection pressures on enemies. Coevolution between terrestrial plants and their enemies is an important element of the evolutionary history of both groups. However, coevolutionary studies of plant-pathogen interactions have tended to focus on different research topics than plant-herbivore interactions. Specifically, studies of plant-pathogen interactions often adopt a "gene-for-gene" conceptual framework. In contrast, studies of plants and herbivores often investigate escalation or elaboration of plant defense and herbivore adaptations to overcome it. The main exceptions to the general pattern are studies that focus on small, sessile herbivores that share many features with plant pathogens, studies that incorporate both herbivores and pathogens into a single investigation, and studies that test aspects of Thompson's geographic mosaic theory for coevolution. We discuss the implications of these findings for future research.

Evidence for Adaptive Introgression of Disease Resistance Genes Among Closely Related Arabidopsis Species

The generation and maintenance of functional variation in the pathogen defense system of plants is central to the constant evolutionary battle between hosts and parasites. If a species is susceptible to a given pathogen, hybridization and subsequent introgression of a resistance allele from a related species can potentially be an important source of new immunity and is therefore expected to be selected for in a process referred to as adaptive introgression. Here, we survey sequence variation in 10 resistance (R-) genes and compare them with 37 reference genes in natural populations of the two closely related and interfertile species: Arabidopsis lyrata and A. halleri. The R-genes are highly polymorphic in both species and show clear signs of trans-species polymorphisms. We show that A. lyrata and A. halleri have had a history of limited introgression for the reference genes. For the R-genes, the introgression rate has been significantly higher than for the reference genes, resulting in fewer fixed differences between species and a higher sharing of identical haplotypes. We conclude that R-genes likely cross the species boundaries at a higher rate than reference genes and therefore also that some of the increased diversity and trans-specific polymorphisms in R-genes is due to adaptive introgression.

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.

The escalatory Red Queen: Population extinction and replacement following arms race dynamics in poplar rust

Host-parasite systems provide convincing examples of Red Queen co-evolutionary dynamics. Yet, a key process underscored in Van Valen's theory - that arms race dynamics can result in extinction - has never been documented. One reason for this may be that most sampling designs lack the breadth needed to illuminate the rapid pace of adaptation by pathogen populations. In this study, we used a 25-year temporal sampling to decipher the demographic history of a plant pathogen: the poplar rust fungus, Melampsora larici-populina. A major adaptive event occurred in 1994 with the breakdown of R7 resistance carried by several poplar cultivars widely planted in Western Europe since 1982. The corresponding virulence rapidly spread in M. larici-populina populations and nearly reached fixation in northern France, even on susceptible hosts. Using both temporal records of virulence profiles and temporal population genetic data, our analyses revealed that (i) R7 resistance breakdown resulted in the emergence of a unique and homogeneous genetic group, the so-called cultivated population, which predominated in northern France for about 20 years, (ii) selection for Vir7 individuals brought with it multiple other virulence types via hitchhiking, resulting in an overall increase in the population-wide number of virulence types and (iii) - above all - the emergence of the cultivated population superseded the initial population which predominated at the same place before R7 resistance breakdown. Our temporal analysis illustrates how antagonistic co-evolution can lead to population extinction and replacement, hence providing direct evidence for the escalation process which is at the core of Red Queen dynamics.

The wild tomato species Solanum chilense shows variation in pathogen resistance between geographically distinct populations

Wild tomatoes are a valuable source of disease resistance germplasm for tomato (Solanum lycopersicum) breeders. Many species are known to possess a certain degree of resistance against certain pathogens; however, evolution of resistance traits is yet poorly understood. For some species, like Solanum chilense, both differences in habitat and within species genetic diversity are very large. Here we aim to investigate the occurrence of spatially heterogeneous coevolutionary pressures between populations of S. chilense. We investigate the phenotypic differences in disease resistance within S. chilense against three common tomato pathogens (Alternaria solani, Phytophthora infestans and a Fusarium sp.) and confirm high degrees of variability in resistance properties between selected populations. Using generalised linear mixed models, we show that disease resistance does not follow the known demographic patterns of the species. Models with up to five available climatic and geographic variables are required to best describe resistance differences, confirming the complexity of factors involved in local resistance variation. We confirm that within S. chilense, resistance properties against various pathogens show a mosaic pattern and do not follow environmental patterns, indicating the strength of local pathogen pressures. Our study can form the basis for further investigations of the genetic traits involved.

Odor diversity decreases with inbreeding in the ant Hypoponera opacior

Reduction in heterozygosity can lead to inbreeding depression. This loss of genetic variability especially affects diverse loci, such as immune genes or those encoding recognition cues. In social insects, nestmates are recognized by their odor, that is their cuticular hydrocarbon profile. Genes underlying hydrocarbon production are thought to be under balancing selection. If so, inbreeding should result in a loss of chemical diversity. We show here that cuticular hydrocarbon diversity decreases with inbreeding. Studying an ant with a facultative inbreeding lifestyle, we found inbred workers to exhibit both a lower number of hydrocarbons and less diverse, that is less evenly proportioned profiles. The association with inbreeding was strong for methyl-branched alkanes, which play a major role in nestmate recognition, and for n-alkanes, whereas unsaturated compounds were unaffected. Shifts in allocation strategies with inbreeding in our focal species indicate that these ants can detect their inbreeding level and use this information to adjust their reproductive strategy. Our study is the first to demonstrate that odor profiles can encode information on inbreeding, with broad implications not only for social insects, but for sexual selection and mate choice in general. Odor profiles may constitute an honest signal of inbreeding, a fitness-relevant trait in many species.

Genotype-by-genotype interactions between an insect and its pathogen

Genotype-by-genotype (G×G) interactions are an essential requirement for the coevolution of hosts and parasites, but have only been documented in a small number of animal model systems. G×G effects arise from interactions between host and pathogen genotypes, such that some pathogen strains are more infectious in certain hosts and some hosts are more susceptible to certain pathogen strains. We tested for G×G interactions in the gypsy moth (Lymantria dispar) and its baculovirus. We infected 21 full-sib families of gypsy moths with each of 16 isolates of baculovirus and measured the between-isolate correlations of infection rate across host families for all pairwise combinations of isolates. Mean infectiousness varied among isolates and disease susceptibility varied among host families. Between-isolate correlations of infection rate were generally less than one, indicating nonadditive effects of host and pathogen type consistent with G×G interactions. Our results support the presence of G×G effects in the gypsy moth-baculovirus interaction and provide empirical evidence that correlations in infection rates between field-collected isolates are consistent with values that mathematical models have previously shown to increase the likelihood of pathogen polymorphism.

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.

Recombination Rate Heterogeneity within Arabidopsis Disease Resistance Genes

Meiotic crossover frequency varies extensively along chromosomes and is typically concentrated in hotspots. As recombination increases genetic diversity, hotspots are predicted to occur at immunity genes, where variation may be beneficial. A major component of plant immunity is recognition of pathogen Avirulence (Avr) effectors by resistance (R) genes that encode NBS-LRR domain proteins. Therefore, we sought to test whether NBS-LRR genes would overlap with meiotic crossover hotspots using experimental genetics in Arabidopsis thaliana. NBS-LRR genes tend to physically cluster in plant genomes; for example, in Arabidopsis most are located in large clusters on the south arms of chromosomes 1 and 5. We experimentally mapped 1,439 crossovers within these clusters and observed NBS-LRR gene associated hotspots, which were also detected as historical hotspots via analysis of linkage disequilibrium. However, we also observed NBS-LRR gene coldspots, which in some cases correlate with structural heterozygosity. To study recombination at the fine-scale we used high-throughput sequencing to analyze ~1,000 crossovers within the RESISTANCE TO ALBUGO CANDIDA1 (RAC1) R gene hotspot. This revealed elevated intragenic crossovers, overlapping nucleosome-occupied exons that encode the TIR, NBS and LRR domains. The highest RAC1 recombination frequency was promoter-proximal and overlapped CTT-repeat DNA sequence motifs, which have previously been associated with plant crossover hotspots. Additionally, we show a significant influence of natural genetic variation on NBS-LRR cluster recombination rates, using crosses between Arabidopsis ecotypes. In conclusion, we show that a subset of NBS-LRR genes are strong hotspots, whereas others are coldspots. This reveals a complex recombination landscape in Arabidopsis NBS-LRR genes, which we propose results from varying coevolutionary pressures exerted by host-pathogen relationships, and is influenced by structural heterozygosity.

Pooled Enrichment Sequencing Identifies Diversity and Evolutionary Pressures at NLR Resistance Genes within a Wild Tomato Population

Nod-like receptors (NLRs) are nucleotide-binding domain and leucine-rich repeats containing proteins that are important in plant resistance signaling. Many of the known pathogen resistance (R) genes in plants are NLRs and they can recognize pathogen molecules directly or indirectly. As such, divergence and copy number variants at these genes are found to be high between species. Within populations, positive and balancing selection are to be expected if plants coevolve with their pathogens. In order to understand the complexity of R-gene coevolution in wild nonmodel species, it is necessary to identify the full range of NLRs and infer their evolutionary history. Here we investigate and reveal polymorphism occurring at 220 NLR genes within one population of the partially selfing wild tomato species Solanum pennellii. We use a combination of enrichment sequencing and pooling ten individuals, to specifically sequence NLR genes in a resource and cost-effective manner. We focus on the effects which different mapping and single nucleotide polymorphism calling software and settings have on calling polymorphisms in customized pooled samples. Our results are accurately verified using Sanger sequencing of polymorphic gene fragments. Our results indicate that some NLRs, namely 13 out of 220, have maintained polymorphism within our S. pennellii population. These genes show a wide range of πN/πS ratios and differing site frequency spectra. We compare our observed rate of heterozygosity with expectations for this selfing and bottlenecked population. We conclude that our method enables us to pinpoint NLR genes which have experienced natural selection in their habitat.

Adaptation to resistant hosts increases fitness on susceptible hosts in the plant parasitic nematode Globodera pallida

Trade-offs between virulence (defined as the ability to infect a resistant host) and life-history traits are of particular interest in plant pathogens for durable management of plant resistances. Adaptation to plant resistances (i.e., virulence acquisition) is indeed expected to be associated with a fitness cost on susceptible hosts. Here, we investigated whether life-history traits involved in the fitness of the potato cyst nematode Globodera pallida are affected in a virulent lineage compared to an avirulent one. Both lineages were obtained from the same natural population through experimental evolution on resistant and susceptible hosts, respectively. Unexpectedly, we found that virulent lineages were more fit than avirulent lineages on susceptible hosts: they produced bigger cysts, containing more larvae and hatching faster. We thus discuss possible reasons explaining why virulence did not spread into natural G. pallida populations.

Host-parasite coevolution: why changing population size matters

Host-parasite coevolution is widely assumed to have a major influence on biological evolution, especially as these interactions impose high selective pressure on the reciprocally interacting antagonists. The exact nature of the underlying dynamics is yet under debate and may be determined by recurrent selective sweeps (i.e., arms race dynamics), negative frequency-dependent selection (i.e., Red Queen dynamics), or a combination thereof. These interactions are often associated with reciprocally induced changes in population size, which, in turn, should have a strong impact on co-adaptation processes, yet are neglected in most current work on the topic. Here, we discuss potential consequences of temporal variations in population size on host-parasite coevolution. The limited empirical data available and the current theoretical literature in this field highlight that the consideration of such interaction-dependent population size changes is likely key for the full understanding of the coevolutionary dynamics, and, thus, a more realistic view on the complex nature of species interactions.

Host-parasite coevolution in populations of constant and variable size

BACKGROUND

The 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.

RESULTS

Here, 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.

CONCLUSION

Our 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.

Emergence of long-term balanced polymorphism under cyclic selection of spatially variable magnitude

A fundamental question in evolutionary biology is what promotes genetic variation at nonneutral loci, a major precursor to adaptation in changing environments. In particular, balanced polymorphism under realistic evolutionary models of temporally varying environments in finite natural populations remains to be demonstrated. Here, we propose a novel mechanism of balancing selection under temporally varying fitnesses. Using forward-in-time computer simulations and mathematical analysis, we show that cyclic selection that spatially varies in magnitude, such as along an environmental gradient, can lead to elevated levels of nonneutral genetic polymorphism in finite populations. Balanced polymorphism is more likely with an increase in gene flow, magnitude and period of fitness oscillations, and spatial heterogeneity. This polymorphism-promoting effect is robust to small systematic fitness differences between competing alleles or to random environmental perturbation. Furthermore, we demonstrate analytically that protected polymorphism arises as spatially heterogeneous cyclic fitness oscillations generate a type of storage effect that leads to negative frequency dependent selection. Our findings imply that spatially variable cyclic environments can promote elevated levels of nonneutral genetic variation in natural populations.

Ancient and recent selective pressures shaped genetic diversity at AIM2-like nucleic acid sensors

AIM2-like receptors (ALRs) are a family of nucleic acid sensors essential for innate immune responses against viruses and bacteria. We performed an evolutionary analysis of ALR genes (MNDA, PYHIN1, IFI16, and AIM2) by analyzing inter- and intraspecies diversity. Maximum-likelihood analyses indicated that IFI16 and AIM2 evolved adaptively in primates, with branch-specific selection at the catarrhini lineage for IFI16. Application of a population genetics–phylogenetics approach also allowed identification of positive selection events in the human lineage. Positive selection in primates targeted sites located at the DNA-binding interface in both IFI16 and AIM2. In IFI16, several sites positively selected in primates and in the human lineage were located in the PYD domain, which is involved in protein–protein interaction and is bound by a human cytomegalovirus immune evasion protein. Finally, positive selection was found to target nuclear localization signals in IFI16 and the spacer region separating the two HIN domains. Population genetic analysis in humans revealed that an IFI16 genic region has been a target of long-standing balancing selection, possibly acting on two nonsynonymous polymorphisms located in the spacer region. Data herein indicate that ALRs have been repeatedly targeted by natural selection. The balancing selection region in IFI16 carries a variant with opposite risk effect for distinct autoimmune diseases, suggesting antagonistic pleiotropy. We propose that the underlying scenario is the result of an ancestral and still ongoing host–pathogen arms race and that the maintenance of susceptibility alleles for autoimmune diseases at IFI16 represents an evolutionary trade-off.

Footprints of ancient-balanced polymorphisms in genetic variation data from closely related species

When long-lasting, balancing selection can lead to “trans-species” polymorphisms that are shared by two or more species identical by descent. In such cases, the gene genealogy at the selected site clusters by allele instead of by species, and nearby neutral sites also have unusual genealogies because of linkage. While this scenario is expected to leave discernible footprints in genetic variation data, the specific patterns remain poorly characterized. Motivated by recent findings in primates, we focus on the case of a biallelic polymorphism under ancient balancing selection and derive approximations for summaries of the polymorphism data from two species. Specifically, we characterize the length of the segment that carries most of the footprints, the expected number of shared neutral single nucleotide polymorphisms (SNPs), and the patterns of allelic associations among them. We confirm the accuracy of our approximations by coalescent simulations. We further show that for humans and chimpanzees—more generally, for pairs of species with low genetic diversity levels—these patterns are highly unlikely to be generated by neutral recurrent mutations. We discuss the implications for the design and interpretation of genome scans for ancient balanced polymorphisms in primates and other taxa.

Durable resistance of crops to disease: a Darwinian perspective

This review takes an evolutionary view of breeding crops for durable resistance to disease. An understanding of coevolution between hosts and parasites leads to predictors of potentially durable resistance, such as corresponding virulence having a high fitness cost to the pathogen or resistance being common in natural populations. High partial resistance can also promote durability. Whether or not resistance is actually durable, however, depends on ecological and epidemiological processes that stabilize genetic polymorphism, many of which are absent from intensive agriculture. There continues to be no biological, genetic, or economic model for durable resistance. The analogy between plant breeding and natural selection indicates that the basic requirements are genetic variation in potentially durable resistance, effective and consistent selection for resistance, and an efficient breeding process in which trials of disease resistance are integrated with other traits. Knowledge about genetics and mechanisms can support breeding for durable resistance once these fundamentals are in place.

The jack of all trades is master of none: a pathogen's ability to infect a greater number of host genotypes comes at a cost of delayed reproduction

A trade-off between a pathogen's ability to infect many hosts and its reproductive capacity on each host genotype is predicted to limit the evolution of an expanded host range, yet few empirical results provide evidence for the magnitude of such trade-offs. Here, we test the hypothesis for a trade-off between the number of host genotypes that a fungal pathogen can infect (host genotype range) and its reproductive capacity on susceptible plant hosts. We used strains of the oat crown rust fungus that carried widely varying numbers of virulence (avr) alleles known to determine host genotype range. We quantified total spore production and the expression of four pathogen life-history stages: infection efficiency, time until reproduction, pustule size, and spore production per pustule. In support of the trade-off hypothesis, we found that virulence level, the number of avr alleles per pathogen strain, was correlated with significant delays in the onset of reproduction and with smaller pustule sizes. Modeling from our results, we conclude that trade-offs have the capacity to constrain the evolution of host genotype range in local populations. In contrast, long-term trends in virulence level suggest that the continued deployment of resistant host lines over wide regions of the United States has generated selection for increased host genotype range.

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.