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

The use of evolutionary analyses to predict functionally relevant traits in filamentous plant pathogens

Identifying traits involved in plant-pathogen interactions is one of the major objectives in molecular plant pathology. Evolutionary analyses may assist in the identification of genes encoding traits that are involved in virulence and local adaptation, including adaptation to agricultural intervention strategies. In the past decades, the number of available genome sequences of fungal plant pathogens has rapidly increased, providing a rich source for the discovery of functionally important genes as well as inference of species histories. Positive selection in the form of diversifying or directional selection leaves particular signatures in genome alignments and can be identified with statistical genetics methods. This review summarises the concepts and approaches used in evolutionary genomics and lists major discoveries related to plant-pathogen adaptative evolution. We underline the significant contribution of evolutionary genomics in discovering virulence-related traits and the study of plant-pathogen ecology and adaptive evolution.

Unraveling coevolutionary dynamics using ecological genomics

Coevolutionary interactions, from the delicate co-dependency in mutualistic interactions to the antagonistic relationship of hosts and parasites, are a ubiquitous driver of adaptation. Surprisingly, little is known about the genomic processes underlying coevolution in an ecological context. However, species comprise genetically differentiated populations that interact with temporally variable abiotic and biotic environments. We discuss the recent advances in coevolutionary theory and genomics as well as shortcomings, to identify coevolving genes that take into account this spatial and temporal variability of coevolution, and propose a practical guide to understand the dynamic of coevolution using an ecological genomics lens.

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.

Tackling microbial threats in agriculture with integrative imaging and computational approaches

Pathogens and pests are one of the major threats to agricultural productivity worldwide. For decades, targeted resistance breeding was used to create crop cultivars that resist pathogens and environmental stress while retaining yields. The often decade-long process of crossing, selection, and field trials to create a new cultivar is challenged by the rapid rise of pathogens overcoming resistance. Similarly, antimicrobial compounds can rapidly lose efficacy due to resistance evolution. Here, we review three major areas where computational, imaging and experimental approaches are revolutionizing the management of pathogen damage on crops. Recognizing and scoring plant diseases have dramatically improved through high-throughput imaging techniques applicable both under well-controlled greenhouse conditions and directly in the field. However, computer vision of complex disease phenotypes will require significant improvements. In parallel, experimental setups similar to high-throughput drug discovery screens make it possible to screen thousands of pathogen strains for variation in resistance and other relevant phenotypic traits. Confocal microscopy and fluorescence can capture rich phenotypic information across pathogen genotypes. Through genome-wide association mapping approaches, phenotypic data helps to unravel the genetic architecture of stress- and virulence-related traits accelerating resistance breeding. Finally, joint, large-scale screenings of trait variation in crops and pathogens can yield fundamental insights into how pathogens face trade-offs in the adaptation to resistant crop varieties. We discuss how future implementations of such innovative approaches in breeding and pathogen screening can lead to more durable disease control.

Host-parasite co-evolution and its genomic signature

Studies in diverse biological systems have indicated that host-parasite co-evolution is responsible for the extraordinary genetic diversity seen in some genomic regions, such as major histocompatibility (MHC) genes in jawed vertebrates and resistance genes in plants. This diversity is believed to evolve under balancing selection on hosts by parasites. However, the mechanisms that link the genomic signatures in these regions to the underlying co-evolutionary process are only slowly emerging. We still lack a clear picture of the co-evolutionary concepts and of the genetic basis of the co-evolving phenotypic traits in the interacting antagonists. Emerging genomic tools that provide new options for identifying underlying genes will contribute to a fuller understanding of the co-evolutionary process.