Luke G. Barrett

Life history determines genetic structure and evolutionary potential of host–parasite interactions

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

Rapid genetic change underpins antagonistic coevolution in a natural host‐pathogen metapopulation

Antagonistic coevolution is a critical force driving the evolution of diversity, yet the selective processes underpinning reciprocal adaptive changes in nature are not well understood. Local adaptation studies demonstrate partner impacts on fitness and adaptive change, but do not directly expose genetic processes predicted by theory. Specifically, we have little knowledge of the relative importance of fluctuating selection vs. arms-race dynamics in maintaining polymorphism in natural systems where metapopulation processes predominate. We conducted cross-year epidemiological, infection and genetic studies of multiple wild host and pathogen populations in the Linum-Melampsora association. We observed asynchronous phenotypic fluctuations in resistance and infectivity among demes. Importantly, changes in allelic frequencies at pathogen infectivity loci, and in host recognition of these genetic variants, correlated with disease prevalence during natural epidemics. These data strongly support reciprocal coevolution maintaining balanced resistance and infectivity polymorphisms, and highlight the importance of characterising spatial and temporal dynamics in antagonistic interactions.

Unifying concepts and mechanisms in the specificity of plant–enemy interactions

Host ranges are commonly quantified to classify herbivores and plant pathogens as either generalists or specialists. Here, we summarize patterns and mechanisms in the interactions of plants with these enemies along different axes of specificity. We highlight the many dimensions within which plant enemies can specify and consider the underlying ecological, evolutionary and molecular mechanisms. Host resistance traits and enemy effectors emerge as central players determining host utilization and thus host range. Finally, we review approaches to studying the causes and consequences of variation in the specificity of plant-enemy interactions. Knowledge of the molecular mechanisms that determine host range is required to understand host shifts, and evolutionary transitions among specialist and generalist strategies, and to predict potential host ranges of pathogens and herbivores.

Variation in infectivity and aggressiveness in space and time in wild host–pathogen systems: causes and consequences

Variation in host resistance and in the ability of pathogens to infect and grow (i.e. pathogenicity) is important as it provides the raw material for antagonistic (co)evolution and therefore underlies risks of disease spread, disease evolution and host shifts. Moreover, the distribution of this variation in space and time may inform us about the mode of coevolutionary selection (arms race vs. fluctuating selection dynamics) and the relative roles of G × G interactions, gene flow, selection and genetic drift in shaping coevolutionary processes. Although variation in host resistance has recently been reviewed, little is known about overall patterns in the frequency and scale of variation in pathogenicity, particularly in natural systems. Using 48 studies from 30 distinct host–pathogen systems, this review demonstrates that variation in pathogenicity is ubiquitous across multiple spatial and temporal scales. Quantitative analysis of a subset of extensively studied plant–pathogen systems shows that the magnitude of within‐population variation in pathogenicity is large relative to among‐population variation and that the distribution of pathogenicity partly mirrors the distribution of host resistance. At least part of the variation in pathogenicity found at a given spatial scale is adaptive, as evidenced by studies that have examined local adaptation at scales ranging from single hosts through metapopulations to entire continents and – to a lesser extent – by comparisons of pathogenicity with neutral genetic variation. Together, these results support coevolutionary selection through fluctuating selection dynamics. We end by outlining several promising directions for future research.

Diversity and evolution of effector loci in natural populations of the plant pathogen Melampsora lini

Genetic variation for pathogen infectivity is an important driver of disease incidence and prevalence in both natural and managed systems. Here, we use the interaction between the rust pathogen, Melampsora lini, and two host plants, Linum marginale and Linum usitatissimum, to examine how host-pathogen interactions influence the maintenance of polymorphism in genes underlying pathogen virulence. Extensive sequence variation at two effector loci (AvrP123, AvrP4) was found in M. lini isolates collected from across the native range of L. marginale in Australia, as well as in isolates collected from a second host, the cultivated species L. usitatissimum. A highly significant excess of nonsynonymous compared with synonymous polymorphism was found at both loci, suggesting that diversifying selection is important for the maintenance of the observed sequence diversity. Agrobacterium-mediated transient transformation assays were used to demonstrate that variants of both the AvrP123 and AvrP4 genes are differentially recognized by resistance genes in L. marginale. We further characterized patterns of nucleotide variation at AvrP123 and AvrP4 in 10 local populations of M. lini infecting the wild host L. marginale. Populations were significantly differentiated with respect to allelic representation at the Avr loci, suggesting the possibility of local selection maintaining distinct genetic structures between pathogen populations, whereas limited diversity may be explained via selective sweeps and demographic bottlenecks. Together, these results imply that interacting selective and nonselective factors, acting across a broad range of scales, are important for the generation and maintenance of adaptively significant variation in populations of M. lini.

Guiding deployment of resistance in cereals using evolutionary principles.

Genetically controlled resistance provides plant breeders with an efficient means of controlling plant disease, but this approach has been constrained by practical difficulties associated with combining many resistance genes together and strong evolutionary responses from pathogen populations leading to subsequent resistance breakdown. However, continuing advances in molecular marker technologies are revolutionizing the ability to rapidly and reliably manipulate resistances of all types – major gene, adult plant and quantitative resistance loci singly or multiply into individual host lines. Here, we argue that these advances provide major opportunities to deliberately design deployment strategies in cereals that can take advantage of the evolutionary pressures faced by target pathogens. Different combinations of genes deployed either within single host individuals or between different individuals within or among crops, can be used to reduce the size of pathogen populations and generate patterns of disruptive selection. This will simultaneously limit immediate epidemic development and reduce the probability of subsequent evolutionary change in the pathogen for broader infectivity or increased aggressiveness. The same general principles are relevant to the control of noncereal diseases, but the most efficacious controls will vary reflecting the range of genetic options available and their fit with specific ecology and life‐history combinations.

Population structure and diversity in sexual and asexual populations of the pathogenic fungus Melampsora lini

Many pathogens undergo both sexual and asexual reproduction to varying degrees, yet the ecological, genetic and evolutionary consequences of different reproductive strategies remain poorly understood. Here we investigate the population genetic structure of wild populations of the plant pathogen Melampsora lini on its host Linum marginale, using amplified fragment length polymorphism (AFLP) markers, two genes underlying pathogen virulence, and phenotypic variation in virulence. In Australia, M. lini occurs as two genetically and geographically divergent lineages (AA and AB), one of which is completely asexual (AB), and the other able to reproduce both clonally and sexually (AA). To quantify the genetic and evolutionary consequences of these different life histories, we sampled five populations in each of two biogeographical regions. Analysis of AFLP data obtained for 275 isolates revealed largely disjunct geographical distributions for the two different lineages, low genetic diversity within lineages, and strong genetic structure among populations within each region. We also detected significant divergence among populations for both Avr genes and virulence phenotypes, although generally these values were lower than those obtained with AFLP markers. Furthermore, isolates belonging to lineage AA collectively harboured significantly higher genotypic and phenotypic diversity than lineage AB isolates. Together these results illustrate the important roles of reproductive modes and geographical structure in the generation and maintenance of virulence diversity in populations of M. lini.

EVOLUTIONARY DIVERSIFICATION THROUGH HYBRIDIZATION IN A WILD HOST–PATHOGEN INTERACTION

Abstract Coevolutionary outcomes between interacting species are predicted to vary across landscapes, as environmental conditions, gene flow, and the strength of selection vary among populations. Using a combination of molecular, experimental, and field approaches, we describe how broad-scale patterns of environmental heterogeneity, genetic divergence, and regional adaptation have the potential to influence coevolutionary processes in the Linum marginale–Melampsora lini plant–pathogen interaction. We show that two genetically and geographically divergent pathogen lineages dominate interactions with the host across Australia, and demonstrate a hybrid origin for one of the lineages. We further demonstrate that the geographic divergence of the two lineages of M. lini in Australia is related to variation among lineages in virulence, life-history characteristics, and response to environmental conditions. When correlated with data describing regional patterns of variation in host resistance diversity and mating system these observations highlight the potential for gene flow and geographic selection mosaics to generate and maintain coevolutionary diversification in long-standing host–pathogen interactions.

Positive selection in AvrP4 avirulence gene homologues across the genus Melampsora

Pathogen genes involved in interactions with their plant hosts are expected to evolve under positive Darwinian selection or balancing selection. In this study a single copy avirulence gene, AvrP4, in the plant pathogen Melampsora lini, was used to investigate the evolution of such a gene across species. Partial translation elongation factor 1-alpha sequences were obtained to establish phylogenetic relationships among the Melampsora species. We amplified AvrP4 homologues from species pathogenic on hosts from different plant families and orders, across the inferred phylogeny. Translations of the AvrP4 sequences revealed a predicted signal peptide and towards the C-terminus of the protein, six identically spaced cysteines were identified in all sequences. Maximum likelihood analysis of synonymous versus non-synonymous substitution rates indicated that positive selection played a role in the evolution of the gene during the diversification of the genus. Fourteen codons under significant positive selection reside in the C-terminal 28 amino acid region, suggesting that this region interacts with host molecules in most sequenced accessions. Selection pressures on the gene may be either due to the pathogenicity or avirulence function of the gene or both.

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.