Parasitism drives host genome evolution: Insights from thePasteuria ramosa-Daphnia magnasystem

Molecular mechanisms of adaptive evolution in wild animals and plants

Wild animals and plants have developed a variety of adaptive traits driven by adaptive evolution, an important strategy for species survival and persistence. Uncovering the molecular mechanisms of adaptive evolution is the key to understanding species diversification, phenotypic convergence, and inter-species interaction. As the genome sequences of more and more non-model organisms are becoming available, the focus of studies on molecular mechanisms of adaptive evolution has shifted from the candidate gene method to genetic mapping based on genome-wide scanning. In this study, we reviewed the latest research advances in wild animals and plants, focusing on adaptive traits, convergent evolution, and coevolution. Firstly, we focused on the adaptive evolution of morphological, behavioral, and physiological traits. Secondly, we reviewed the phenotypic convergences of life history traits and responding to environmental pressures, and the underlying molecular convergence mechanisms. Thirdly, we summarized the advances of coevolution, including the four main types: mutualism, parasitism, predation and competition. Overall, these latest advances greatly increase our understanding of the underlying molecular mechanisms for diverse adaptive traits and species interaction, demonstrating that the development of evolutionary biology has been greatly accelerated by multi-omics technologies. Finally, we highlighted the emerging trends and future prospects around the above three aspects of adaptive evolution.

Draft genomes for one Microcystis-resistant and one Microcystis-sensitive strain of the water flea, Daphnia pulicaria

Daphnia species are well-suited for studying local adaptation and evolutionary responses to stress(ors) including those caused by algal blooms. Algal blooms, characterized by an overgrowth (bloom) of cyanobacteria, are detrimental to the health of aquatic and terrestrial members of freshwater ecosystems. Some strains of Daphnia pulicaria have demonstrated resistance to toxic algae and the ability to mitigate toxic algal blooms. Understanding the genetic mechanism associated with this toxin resistance requires adequate genomic resources. Using whole-genome sequence data mapped to the Daphnia pulex reference genome (PA42), we present reference-guided draft assemblies from one tolerant and one sensitive strain of D. pulicaria, Wintergreen-6 (WI-6), and Bassett-411 (BA-411), respectively. Assessment of the draft assemblies reveal low contamination levels, and high levels (95%) of genic content. Reference scaffolds had coverage breadths of 98.9-99.4%, and average depths of 33X and 29X for BA-411 and WI-6, respectively. Within, we discuss caveats and suggestions for improving these draft assemblies. These genomic resources are presented with a goal of contributing to the resources necessary to understand the genetic mechanisms and associations of toxic prey resistance observed in this species.

Infection phenotypes of a coevolving parasite are highly diverse, structured, and specific

Understanding how diversity is maintained in natural populations is a major goal of evolutionary biology. In coevolving hosts and parasites, negative frequency-dependent selection is one mechanism predicted to maintain genetic variation. While much is known about host diversity, parasite diversity remains understudied in coevolutionary research. Here, we survey natural diversity in a bacterial parasite by characterizing infection phenotypes for over 50 isolates in relation to 12 genotypes of their host, Daphnia magna. We find striking phenotypic variation among parasite isolates, and we discover the parasite can infect its host through at least five different attachment sites. Variation in attachment success at each site is explained to varying degrees by host and parasite genotypes. A spatial correlation analysis showed that infectivity of different isolates does not correlate with geographic distance, meaning isolates from widespread populations are equally able to infect the host. Overall, our results reveal that infection phenotypes of this parasite are highly diverse. Our results are consistent with the prediction that under Red Queen coevolutionary dynamics both the host and the parasite should show high genetic diversity for traits of functional importance in their interactions.

Balancing selection for pathogen resistance reveals an intercontinental signature of Red Queen coevolution

The link between long-term host–parasite coevolution and genetic diversity is key to understanding genetic epidemiology and the evolution of resistance. The model of Red Queen host–parasite coevolution posits that high genetic diversity is maintained when rare host resistance variants have a selective advantage, which is believed to be the mechanistic basis for the extraordinarily high levels of diversity at disease-related genes such as the major histocompatibility complex in jawed vertebrates and R-genes in plants. The parasites that drive long-term coevolution are, however, often elusive. Here we present evidence for long-term balancing selection at the phenotypic (variation in resistance) and genomic (resistance locus) level in a particular host–parasite system: the planktonic crustacean Daphnia magna and the bacterium Pasteuria ramosa. The host shows widespread polymorphisms for pathogen resistance regardless of geographic distance, even though there is a clear genome-wide pattern of isolation by distance at other sites. In the genomic region of a previously identified resistance supergene, we observed consistent molecular signals of balancing selection, including higher genetic diversity, older coalescence times, and lower differentiation between populations, which set this region apart from the rest of the genome. We propose that specific long-term coevolution by negative-frequency-dependent selection drives this elevated diversity at the host's resistance loci on an intercontinental scale and provide an example of a direct link between the host’s resistance to a virulent pathogen and the large-scale diversity of its underlying genes.

A Two-Locus System with Strong Epistasis Underlies Rapid Parasite-Mediated Evolution of Host Resistance

Parasites are a major evolutionary force, driving adaptive responses in host populations. Although the link between phenotypic response to parasite-mediated natural selection and the underlying genetic architecture often remains obscure, this link is crucial for understanding the evolution of resistance and predicting associated allele frequency changes in the population. To close this gap, we monitored the response to selection during epidemics of a virulent bacterial pathogen, Pasteuria ramosa, in a natural host population of Daphnia magna. Across two epidemics, we observed a strong increase in the proportion of resistant phenotypes as the epidemics progressed. Field and laboratory experiments confirmed that this increase in resistance was caused by selection from the local parasite. Using a genome-wide association study, we built a genetic model in which two genomic regions with dominance and epistasis control resistance polymorphism in the host. We verified this model by selfing host genotypes with different resistance phenotypes and scoring their F1 for segregation of resistance and associated genetic markers. Such epistatic effects with strong fitness consequences in host–parasite coevolution are believed to be crucial in the Red Queen model for the evolution of genetic recombination.

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.

Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence

The prevalence and intensity of parasites in wild hosts varies across space and is a key determinant of infection risk in humans, domestic animals and threatened wildlife. Because the immune system serves as the primary barrier to infection, replication and transmission following exposure, we here consider the environmental drivers of immunity. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immunity across spatial scales. Identifying the most important spatial drivers of immunity could help pre-empt infectious disease risks, especially in the context of how large-scale factors such as urbanization affect defence by changing environmental conditions. We provide a synthesis of how to apply macroecological approaches to the study of ecoimmunology (i.e. macroimmunology). We first review spatial factors that could generate spatial variation in defence, highlighting the need for large-scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favoured over small-scale experimental studies. We next conduct a systematic review of the literature to assess the frequency of spatial studies and to classify them according to taxa, immune measures, spatial replication and extent, and statistical methods. We review 210 ecoimmunology studies sampling multiple host populations. We show that whereas spatial approaches are relatively common, spatial replication is generally low and unlikely to provide sufficient environmental variation or power to differentiate competing spatial hypotheses. We also highlight statistical biases in macroimmunology, in that few studies characterize and account for spatial dependence statistically, potentially affecting inferences for the relationships between environmental conditions and immune defence. We use these findings to describe tools from geostatistics and spatial modelling that can improve inference about the associations between environmental and immunological variation. In particular, we emphasize exploratory tools that can guide spatial sampling and highlight the need for greater use of mixed-effects models that account for spatial variability while also allowing researchers to account for both individual- and habitat-level covariates. We finally discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions and urbanization as being especially amenable to large-scale spatial approaches. Methodologically, we highlight critical opportunities posed by assessing spatial variation in host tolerance, using metagenomics to quantify spatial variation in parasite pressure, coupling large-scale field studies with small-scale field experiments and longitudinal approaches, and applying statistical tools from macroecology and meta-analysis to identify generalizable spatial patterns. Such work will facilitate scaling ecoimmunology from individual- to habitat-level insights about the drivers of immune defence and help predict where environmental change may most alter infectious disease risk.

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

Daphnia galeata responds to the exposure to an ichthyosporean gut parasite by down-regulation of immunity and lipid metabolism

BACKGROUND

Regulatory circuits of infection in the emerging experimental model system, water flea Daphnia and their microparasites, remain largely unknown. Here we provide the first molecular insights into the response of Daphnia galeata to its highly virulent and common parasite Caullerya mesnili, an ichthyosporean that infects the gut epithelium. We generated a transcriptomic dataset using RNAseq from parasite-exposed (vs. control) Daphnia, at two time points (4 and 48 h) after parasite exposure.

RESULTS

We found a down-regulation of metabolism and immunity-related genes, at 48 h (but not 4 h) after parasite exposure. These genes are involved in lipid metabolism and fatty acid biosynthesis, as well as microbe recognition (e.g. c-type lectins) and pathogen attack (e.g. gut chitin).

CONCLUSIONS

General metabolic suppression implies host energy shift from reproduction to survival, which is in agreement with the known drastic reduction in Daphnia fecundity after Caullerya infection. The down-regulation of gut chitin indicates a possible interaction between the peritrophic matrix and the evading host immune system. Our study provides the first description of host transcriptional responses in this very promising host-parasite experimental system.

Genome-wide scans of selection highlight the impact of biotic and abiotic constraints in natural populations of the model grass Brachypodium distachyon

Grasses are essential plants for ecosystem functioning. Quantifying the selective pressures that act on natural variation in grass species is therefore essential regarding biodiversity maintenance. In this study, we investigate the selection pressures that act on two distinct populations of the grass model Brachypodium distachyon without prior knowledge about the traits under selection. We took advantage of whole-genome sequencing data produced for 44 natural accessions of B. distachyon and used complementary genome-wide selection scans (GWSS) methods to detect genomic regions under balancing and positive selection. We show that selection is shaping genetic diversity at multiple temporal and spatial scales in this species, and affects different genomic regions across the two populations. Gene ontology annotation of candidate genes reveals that pathogens may constitute important factors of positive and balancing selection in B. distachyon. We eventually cross-validated our results with quantitative trait locus data available for leaf-rust resistance in this species and demonstrate that, when paired with classical trait mapping, GWSS can help pinpointing candidate genes for further molecular validation. Thanks to a near base-perfect reference genome and the large collection of freely available natural accessions collected across its natural range, B. distachyon appears as a prime system for studies in ecology, population genomics and evolutionary biology.

Genomic associations with bill length and disease reveal drift and selection across island bird populations

Island species provide excellent models for investigating how selection and drift operate in wild populations, and for determining how these processes act to influence local adaptation and speciation. Here, we examine the role of selection and drift in shaping genomic and phenotypic variation across recently separated populations of Berthelot's pipit (Anthus berthelotii), a passerine bird endemic to three archipelagos in the Atlantic. We first characterized genetic diversity and population structuring that supported previous inferences of a history of recent colonizations and bottlenecks. We then tested for regions of the genome associated with the ecologically important traits of bill length and malaria infection, both of which vary substantially across populations in this species. We identified a SNP associated with variation in bill length among individuals, islands, and archipelagos; patterns of variation at this SNP suggest that both phenotypic and genotypic variation in bill length is largely shaped by founder effects. Malaria was associated with SNPs near/within genes involved in the immune response, but this relationship was not consistent among archipelagos, supporting the view that disease resistance is complex and rapidly evolving. Although we found little evidence for divergent selection at candidate loci for bill length and malaria resistance, genome scan analyses pointed to several genes related to immunity and metabolism as having important roles in divergence and adaptation. Our findings highlight the utility and challenges involved with combining association mapping and population genetic analysis in nonequilibrium populations, to disentangle the effects of drift and selection on shaping genotypes and phenotypes.

Keeping Pace with the Red Queen: Identifying the Genetic Basis of Susceptibility to Infectious Disease

The results of genome-wide association studies are known to be affected by epistasis and gene-by-environment interactions. Using a statistical model....

Genome-wide association studies are widely used to identify “disease genes” conferring resistance/susceptibility to infectious diseases. Using a combination of mathematical models and simulations, we demonstrate that genetic interactions between hosts and parasites [genotype-by-genotype (G × G) interactions] can drastically affect the results of these association scans and hamper our ability to detect genetic variation in susceptibility. When hosts and parasites coevolve, these G × G interactions often make genome-wide association studies unrepeatable over time or across host populations. Reanalyzing previously published data on Daphnia magna susceptibility to infection by Pasteuria ramosa, we identify genomic regions consistent with G × G interactions. We conclude by outlining possible avenues for designing more powerful and more repeatable association studies.