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

The Evolution of Extreme Genetic Variability in a Parasite-Resistance Complex

Genomic regions that play a role in parasite defense are often found to be highly variable, with the major histocompatibility complex serving as an iconic example. Single nucleotide polymorphisms may represent only a small portion of this variability, with Indel polymorphisms and copy number variation further contributing. In extreme cases, haplotypes may no longer be recognized as orthologous. Understanding the evolution of such highly divergent regions is challenging because the most extreme variation is not visible using reference-assisted genomic approaches. Here we analyze the case of the Pasteuria Resistance Complex in the crustacean Daphnia magna, a defense complex in the host against the common and virulent bacterium Pasteuria ramosa. Two haplotypes of this region have been previously described, with parts of it being nonhomologous, and the region has been shown to be under balancing selection. Using pan-genome analysis and tree reconciliation methods to explore the evolution of the Pasteuria Resistance Complex and its characteristics within and between species of Daphnia and other Cladoceran species, our analysis revealed a remarkable diversity in this region even among host species, with many nonhomologous hyper-divergent haplotypes. The Pasteuria Resistance Complex is characterized by extensive duplication and losses of Fucosyltransferase (FuT) and Galactosyltransferase (GalT) genes that are believed to play a role in parasite defense. The Pasteuria Resistance Complex region can be traced back to common ancestors over 250 million years. The unique combination of an ancient resistance complex and a dynamic, hyper-divergent genomic environment presents a fascinating opportunity to investigate the role of such regions in the evolution and long-term maintenance of resistance polymorphisms. Our findings offer valuable insights into the evolutionary forces shaping disease resistance and adaptation, not only in the genus Daphnia, but potentially across the entire Cladocera class.

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

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

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.

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.