Addressing the Challenges of Pathogen Evolution on the World's Arable Crops

Reconstructing the Global Migration History of Phytophthora infestans Toward Colombia

The evolution of new variants of plant pathogens is one of the biggest challenges to controlling and managing plant diseases. Of the forces driving these evolutionary processes, global migration events are particularly important for widely distributed diseases such as potato late blight, caused by the oomycete Phytophthora infestans. However, little is known about its migration routes outside North America and Europe. This work used genotypic data from population studies to elucidate the migration history originating the Colombian P. infestans population. For this purpose, a dataset of 1,706 P. infestans genotypes was recollected, representing North and South America, Europe, and Asia. Descriptive analysis and historical records from North America and Europe were used to propose three global migration hypotheses, differing on the origin of the disease (Mexico or Peru) and the hypothesis that it returned to South America from Europe. These scenarios were tested using approximate Bayesian computation. According to this analysis, the most probable scenario (posterior probability = 0.631) was the one proposing a Peruvian origin for P. infestans, an initial migration toward Colombia and Mexico, and a later event from Mexico to the United States and then to Europe and Asia, with no return to northern South America. In Colombia, the scenario considering a single migration from Peru and posterior migrations within Colombia was the most probable, with a posterior probability of 0.640. The obtained results support the hypothesis of a Peruvian origin for P. infestans followed by rare colonization events worldwide.

Optimizing Clubroot Management and the Role of Canola Cultivar Mixtures

The sustainable cultivation of canola is under threat from clubroot disease (Plasmodiophora brassicae). The pathogen's resting spores can survive in the soil for extended periods, complicating disease management. Therefore, effective clubroot control requires a combination of tactics that provide multiple layers of protection. Management strategies have focused on pathogen avoidance and reducing disease levels in infested fields. The sanitation of machinery and field equipment remains the most effective method for preventing the pathogen's introduction into non-infested fields. For disease reduction, crop rotation, liming, chemical control, and host resistance are commonly employed, with the use of clubroot-resistant cultivars being the most effective to date. However, resistance breakdown has been observed within four years of the introduction of new cultivars, jeopardizing the long-term effectiveness of this approach. A promising yet underexplored strategy is the use of cultivar mixtures. This approach leverages mechanisms such as the dilution effect, the barrier effect, induced resistance, disruptive selection, and the compensatory effect to control the disease. Cultivar mixtures have the potential to reduce the impact of clubroot on canola production while preserving pathogen population structure, thereby minimizing the likelihood of resistance breakdown. Given its potential, further research into cultivar mixtures as a management strategy for clubroot disease is warranted.

Approximate Bayesian Computation applied to time series of population genetic data disentangles rapid genetic changes and demographic variations in a pathogen population

Adaptation can occur at remarkably short timescales in natural populations, leading to drastic changes in phenotypes and genotype frequencies over a few generations only. The inference of demographic parameters can allow understanding how evolutionary forces interact and shape the genetic trajectories of populations during rapid adaptation. Here we propose a new Approximate Bayesian Computation (ABC) framework that couples a forward and individual-based model with temporal genetic data to disentangle genetic changes and demographic variations in a case of rapid adaptation. We test the accuracy of our inferential framework and evaluate the benefit of considering a dense versus sparse sampling. Theoretical investigations demonstrate high accuracy in both model and parameter estimations, even if a strong thinning is applied to time series data. Then, we apply our ABC inferential framework to empirical data describing the population genetic changes of the poplar rust pathogen following a major event of resistance overcoming. We successfully estimate key demographic and genetic parameters, including the proportion of resistant hosts deployed in the landscape and the level of standing genetic variation from which selection occurred. Inferred values are in accordance with our empirical knowledge of this biological system. This new inferential framework, which contrasts with coalescent-based ABC analyses, is promising for a better understanding of evolutionary trajectories of populations subjected to rapid adaptation.

Fitness difference between two synonymous mutations of Phytophthora infestans ATP6 gene

BACKGROUND

Sequence variation produced by mutation provides the ultimate source of natural selection for species adaptation. Unlike nonsynonymous mutation, synonymous mutations are generally considered to be selectively neutral but accumulating evidence suggests they also contribute to species adaptation by regulating the flow of genetic information and the development of functional traits. In this study, we analysed sequence characteristics of ATP6, a housekeeping gene from 139 Phytophthora infestans isolates, and compared the fitness components including metabolic rate, temperature sensitivity, aggressiveness, and fungicide tolerance among synonymous mutations.

RESULTS

We found that the housekeeping gene exhibited low genetic variation and was represented by two major synonymous mutants at similar frequency (0.496 and 0.468, respectively). The two synonymous mutants were generated by a single nucleotide substitution but differed significantly in fitness as well as temperature-mediated spatial distribution and expression. The synonymous mutant ending in AT was more common in cold regions and was more expressed at lower experimental temperature than the synonymous mutant ending in GC and vice versa.

CONCLUSION

Our results are consistent with the argument that synonymous mutations can modulate the adaptive evolution of species including pathogens and have important implications for sustainable disease management, especially under climate change.

The socio-economic challenges of managing pathogen evolution in agriculture

Genetic resistance forms the foundation of infectious disease management in crops. However, rapid pathogen evolution is causing the breakdown of resistance and threatening disease control. Recent research efforts have identified strategies for resistance gene deployment that aim to disrupt pathogen adaptation and prevent breakdown. To date, there has been limited practical uptake of such strategies. In this paper, we focus on the socio-economic challenges associated with translating applied evolutionary research into scientifically informed management strategies to control pathogen adaptation. We develop a conceptual framework for the economic valuation of resistance and demonstrate that in addition to various direct benefits, resistance delivers considerable indirect and non-market value to farmers and society. Incentives for stakeholders to engage in stewardship strategies are complicated by the uncertain timeframes associated with evolutionary processes, difficulties in assigning ownership rights to genetic resources and lack of governance. These interacting biological, socio-economic and institutional complexities suggest that resistance breakdown should be viewed as a wicked problem, with often conflicting imperatives among stakeholders and no simple cause or solution. Promoting the uptake of scientific research outcomes that address complex issues in sustainable crop disease management will require a mix of education, incentives, legislation and social change. 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.

A GBS-Based GWAS Analysis of Leaf and Stripe Rust Resistance in Diverse Pre-Breeding Germplasm of Bread Wheat (Triticum aestivum L.)

Yellow (YR) and leaf (LR) rusts caused by Puccinia striiformis f. sp. tritici (Pst) and Puccinia triticina, respectively, are of utmost importance to wheat producers because of their qualitative and quantitative effect on yield. The search for new loci resistant to both rusts is an ongoing challenge faced by plant breeders and pathologists. Our investigation was conducted on a subset of 168 pre-breeding lines (PBLs) to identify the resistant germplasm against the prevalent local races of LR and YR under field conditions followed by its genetic mapping. Our analysis revealed a range of phenotypic responses towards both rusts. We identified 28 wheat lines with immune response and 85 resistant wheat genotypes against LR, whereas there were only eight immune and 52 resistant genotypes against YR. A GWAS (genome-wide association study) identified 190 marker-trait associations (MTAs), where 120 were specific to LR and 70 were specific to YR. These MTAs were confined to 86 quantitative trait loci (QTLs), where 50 QTLs carried MTAs associated with only LR, 29 QTLs carried MTAs associated with YR, and seven QTLs carried MTAs associated with both LR and YR. Possible candidate genes at the site of these QTLs are discussed. Overall, 70 PBLs carried all seven LR/YR QTLs. Furthermore, there were five PBLs with less than five scores for both LR and YR carrying positive alleles of all seven YR/LR QTLs, which are fit to be included in a breeding program for rust resistance induction.

Microbial community succession in steam-sterilized greenhouses infected with Fusarium oxysporum

Fusarium is an economically important crop pathogen but spends a large part of its life cycle in bulk soil environments where it interacts with a diverse community of soil microbes. Antagonistic interactions (e.g. competition) between the resident microbial community and Fusarium could constrain the growth of Fusarium in soil, which might therefore slow or prevent Fusarium establishment. We tracked Fusarium oxysporum in floriculture greenhouses where the soil had been steam-sterilized to remove Fusarium. The data indicated a resurgence of soil bacteria and fungi during the first 90 days post-sterilization, followed by a rapid decline in subsequent weeks, which was associated with an increase in F. oxysporum abundance at 148 days post sterilization. These changes over time were associated with successional changes in the bacterial but not the fungal communities. The results illustrate that, although soil steaming clears Fusarium in the short term, it may exacerbate re-emergence as the resident community is continually depleted by the steaming process while Fusarium benefits from nutrients released by steaming. Observations suggest combining steaming with microbial inoculations could help reduce the recovery of Fusarium reducing the fungal load in the first instance and preventing subsequent build-up by giving a head start to its saprophytic competitors.

Global Analysis of Hemileia vastatrix Populations Shows Clonal Reproduction for the Coffee Leaf Rust Pathogen Throughout Most of Its Range

Hemileia vastatrix is the most important fungal pathogen of coffee and the causal agent of recurrent disease epidemics that have invaded nearly every coffee growing region in the world. The development of coffee varieties resistant to H. vastatrix requires fundamental understanding of the biology of the fungus. However, the complete life cycle of H. vastatrix remains unknown, and conflicting studies and interpretations exist as to whether the fungus is undergoing sexual reproduction. Here we used population genetics of H. vastatrix to infer the reproductive mode of the fungus across most of its geographic range, including Central Africa, Southeast Asia, the Caribbean, and South and Central America. The population structure of H. vastatrix was determined via eight simple sequence repeat markers developed for this study. The analyses of the standardized index of association, Hardy-Weinberg equilibrium, and clonal richness all strongly support asexual reproduction of H. vastatrix in all sampled areas. Similarly, a minimum spanning network tree reinforces the interpretation of clonal reproduction in the sampled H. vastatrix populations. These findings may have profound implications for resistance breeding and management programs against H. vastatrix.

Optimizing Plant Disease Management in Agricultural Ecosystems Through Rational In-Crop Diversification

Biodiversity plays multifaceted roles in societal development and ecological sustainability. In agricultural ecosystems, using biodiversity to mitigate plant diseases has received renewed attention in recent years but our knowledge of the best ways of using biodiversity to control plant diseases is still incomplete. In term of in-crop diversification, it is not clear how genetic diversity per se in host populations interacts with identifiable resistance and other functional traits of component genotypes to mitigate disease epidemics and what is the best way of structuring mixture populations. In this study, we created a series of host populations by mixing different numbers of potato varieties showing different late blight resistance levels in different proportions. The amount of naturally occurring late blight disease in the mixture populations was recorded weekly during the potato growing seasons. The percentage of disease reduction (PDR) in the mixture populations was calculated by comparing their observed late blight levels relative to that expected when they were planted in pure stands. We found that PDR in the mixtures increased as the number of varieties and the difference in host resistance (DHR) between the component varieties increased. However, the level of host resistance in the potato varieties had little impact on PDR. In mixtures involving two varieties, the optimum proportion of component varieties for the best PDR depended on their DHR, with an increasing skewness to one of the component varieties as the DHR between the component varieties increased. These results indicate that mixing crop varieties can significantly reduce disease epidemics in the field. To achieve the best disease mitigation, growers should include as many varieties as possible in mixtures or, if only two component mixtures are possible, increase DHR among the component varieties.

Population-level deep sequencing reveals the interplay of clonal and sexual reproduction in the fungal wheat pathogen Zymoseptoria tritici

Pathogens cause significant challenges to global food security. On annual crops, pathogens must re-infect from environmental sources in every growing season. Fungal pathogens have evolved mixed reproductive strategies to cope with the distinct challenges of colonizing growing plants. However, how pathogen diversity evolves during growing seasons remains largely unknown. Here, we performed a deep hierarchical sampling in a single experimental wheat field infected by the major fungal pathogen Zymoseptoria tritici. We analysed whole genome sequences of 177 isolates collected from 12 distinct cultivars replicated in space at three time points of the growing season to maximize capture of genetic diversity. The field population was highly diverse with 37 SNPs per kilobase, a linkage disequilibrium decay within 200-700 bp and a high effective population size. Using experimental infections, we tested a subset of the collected isolates on the dominant cultivar planted in the field. However, we found no significant difference in virulence of isolates collected from the same cultivar compared to isolates collected on other cultivars. About 20 % of the isolate genotypes were grouped into 15 clonal groups. Pairs of clones were disproportionally found at short distances (<5 m), consistent with experimental estimates for per-generation dispersal distances performed in the same field. This confirms predominant leaf-to-leaf transmission during the growing season. Surprisingly, levels of clonality did not increase over time in the field although reproduction is thought to be exclusively asexual during the growing season. Our study shows that the pathogen establishes vast and stable gene pools in single fields. Monitoring short-term evolutionary changes in crop pathogens will inform more durable strategies to contain diseases.

Gene drive strategies of pest control in agricultural systems: Challenges and opportunities

Recent advances in gene-editing technologies have opened new avenues for genetic pest control strategies, in particular around the use of gene drives to suppress or modify pest populations. Significant uncertainty, however, surrounds the applicability of these strategies to novel target species, their efficacy in natural populations and their eventual safety and acceptability as control methods. In this article, we identify issues associated with the potential use of gene drives in agricultural systems, to control pests and diseases that impose a significant cost to agriculture around the world. We first review the need for innovative approaches and provide an overview of the most relevant biological and ecological traits of agricultural pests that could impact the outcome of gene drive approaches. We then describe the specific challenges associated with using gene drives in agricultural systems, as well as the opportunities that these environments may offer, focusing in particular on the advantages of high-threshold gene drives. Overall, we aim to provide a comprehensive view of the potential opportunities and the remaining uncertainties around the use of gene drives in agricultural systems.

Models of Plant Resistance Deployment

Owing to their evolutionary potential, plant pathogens are able to rapidly adapt to genetically controlled plant resistance, often resulting in resistance breakdown and major epidemics in agricultural crops. Various deployment strategies have been proposed to improve resistance management. Globally, these rely on careful selection of resistance sources and their combination at various spatiotemporal scales (e.g., via gene pyramiding, crop rotations and mixtures, landscape mosaics). However, testing and optimizing these strategies using controlled experiments at large spatiotemporal scales are logistically challenging. Mathematical models provide an alternative investigative tool, and many have been developed to explore resistance deployment strategies under various contexts. This review analyzes 69 modeling studies in light of specific model structures (e.g., demographic or demogenetic, spatial or not), underlying assumptions (e.g., whether preadapted pathogens are present before resistance deployment), and evaluation criteria (e.g., resistance durability, disease control, cost-effectiveness). It highlights major research findings and discusses challenges for future modeling efforts.

Impact of the United States Department of Agriculture, Agricultural Research Service on Plant Pathology: 2015-2020

There is an increasing need to supply the world with more food as the population continues to grow. Research on mitigating the effects of plant diseases to improve crop yield and quality can help provide more food without increasing the land area devoted to farming. National Program 303 (NP 303) within the U.S. Department of Agriculture, Agricultural Research Service is dedicated to research across multiple fields in plant pathology. This review article highlights the research impact within NP 303 between 2015 and 2020, including case studies on wheat and citrus diseases and the National Plant Disease Recovery System, which provide specific examples of this impact.

Transcription factor control of virulence in phytopathogenic fungi

Plant-pathogenic fungi are a significant threat to economic and food security worldwide. Novel protection strategies are required and therefore it is critical we understand the mechanisms by which these pathogens cause disease. Virulence factors and pathogenicity genes have been identified, but in many cases their roles remain elusive. It is becoming increasingly clear that gene regulation is vital to enable plant infection and transcription factors play an essential role. Efforts to determine their regulatory functions in plant-pathogenic fungi have expanded since the annotation of fungal genomes revealed the ubiquity of transcription factors from a broad range of families. This review establishes the significance of transcription factors as regulatory elements in plant-pathogenic fungi and provides a systematic overview of those that have been functionally characterized. Detailed analysis is provided on regulators from well-characterized families controlling various aspects of fungal metabolism, development, stress tolerance, and the production of virulence factors such as effectors and secondary metabolites. This covers conserved transcription factors with either specialized or nonspecialized roles, as well as recently identified regulators targeting key virulence pathways. Fundamental knowledge of transcription factor regulation in plant-pathogenic fungi provides avenues to identify novel virulence factors and improve our understanding of the regulatory networks linked to pathogen evolution, while transcription factors can themselves be specifically targeted for disease control. Areas requiring further insight regarding the molecular mechanisms and/or specific classes of transcription factors are identified, and direction for future investigation is presented.

Virulence Structure of Puccinia coronata f. sp. avenae and Effectiveness of Pc Resistance Genes in Poland During 2017-2019

Crown rust caused by Puccinia coronata f. sp. avenae is one of the most destructive diseases of oat, regularly occurring worldwide and leading to significant yield losses. This article characterizes the pathotype structure of P. coronata in Poland and evaluates the potential of crown rust race-specific resistance genes for use in practical breeding conditions in this region. A total of 466 isolates were derived from four locations of intensive oat breeding in Poland in 2017 to 2019, representing P. coronata populations from West, East, South, and Central Poland. Their virulence structure was determined on 35 Pc differential lines in laboratory conditions. In each year and location, high pathotype diversity was observed. In total, 347 (75%) pathotypes were detected. On average P. coronata isolates collected in 2017 and 2018 were virulent to 11% of the oat differentials. In 2019 isolates from East and South of Poland were able to overcome 18.3 and 18.5% of the oat differentials, respectively. There was no isolate virulent against Pc51, Pc52, and Pc91 crown rust resistance genes. P. coronata isolates displayed modest virulence levels, high diversity, and no prevailing pathotype. The information provided here may be helpful for development of resistance breeding strategies and in choosing the most effective major genes for pyramiding into cultivars.

Phylogenetic and phenotypic characterization of Fusarium oxysporum f. sp. niveum isolates from Florida-grown watermelon

Fusarium wilt of watermelon (Citrullus lanatus) caused by Fusarium oxysporum f. sp. niveum (Fon), has become an increasing concern of farmers in the southeastern USA, especially in Florida. Management of this disease, most often through the use of resistant cultivars and crop rotation, requires an accurate understanding of an area’s pathogen population structure and phenotypic characteristics. This study improved the understanding of the state’s pathogen population by completing multilocus sequence analysis (MLSA) of two housekeeping genes (BT and TEF) and two loci (ITS and IGS), aggressiveness and race-determining bioassays on 72 isolates collected between 2011 and 2015 from major watermelon production areas in North, Central, and South Florida. Multilocus sequence analysis (MLSA) failed to group race 3 isolates into a single large clade; moreover, clade membership was not apparently correlated with aggressiveness (which varied both within and between clades), and only slightly with sampling location. The failure of multilocus sequence analysis using four highly conserved housekeeping genes and loci to clearly group and delineate known Fon races provides justification for future whole genome sequencing efforts whose more robust genomic comparisons will provide higher resolution of intra-species genetic distinctions. Consequently, these results suggest that identification of Fon isolates by race determination alone may fail to detect economically important phenotypic characteristics such as aggressiveness leading to inaccurate risk assessment.

Maintenance of variation in virulence and reproduction in populations of an agricultural plant pathogen

Genetic diversity within pathogen populations is critically important for predicting pathogen evolution, disease outcomes and prevalence. However, we lack a good understanding of the processes maintaining genetic variation and constraints on pathogen life-history evolution. Here, we analysed interactions between 12 wheat host genotypes and 145 strains of Zymoseptoria tritici from five global populations to investigate the evolution and maintenance of variation in pathogen virulence and reproduction. We found a strong positive correlation between virulence (amount of leaf necrosis) and reproduction (pycnidia density within lesions), with substantial variation in both traits maintained within populations. On average, highly virulent isolates exhibited higher reproduction, which might increase transmission potential in agricultural fields planted to homogeneous hosts at a high density. We further showed that pathogen strains with a narrow host range (i.e. specialists) for reproduction were on average less virulent, and those with a broader host range (i.e. generalists) were on average less fecund on a given specific host. These costs associated with adaptation to different host genotypes might constrain the emergence of generalists by disrupting the directional evolution of virulence and fecundity. We conclude that selection favouring pathogen strains that are virulent across diverse hosts, coupled with selection that maximizes fecundity on specific hosts, may explain the maintenance of these pathogenicity traits within and among populations.

Rotating and stacking genes can improve crop resistance durability while potentially selecting highly virulent pathogen strains

Rotating crop cultivars with different resistance genes could slow the evolution of virulent strains of fungal pathogens, but could also produce highly virulent pathogen strains. We present a new model that links polycyclic pathogen epidemiology and population genetics in order to predict how different strategies of rotating cultivars with different resistances will affect the evolution of pathogen virulence and the breakdown of crop resistance. We modelled a situation where there were four different resistance genes that can be deployed within each crop cultivar, and four virulence genes that may be present within the pathogen. We simulated four different rotational management strategies: (i) no rotation; (ii) a different gene every year; (iii) a different gene every 5 years; and (iv) a different combination of two stacked genes each year. Results indicate that rotating cultivars can lead to longer periods of disease suppression but also to the selection of highly virulent strains. The efficacy and relative advantage of different resistant cultivar rotation strategies depended on the fitness penalties, initial virulence allele frequencies, and ability of non-virulent pathogen genotypes to grow and reproduce on resistant cultivars. By capturing the essential processes involved, our model provides a useful new tool for investigating the evolutionary dynamics of pathogen virulence and crop resistance breakdown.

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.

Assessing the effects of quantitative host resistance on the life-history traits of sporulating parasites with growing lesions

Assessing life-history traits of parasites on resistant hosts is crucial in evolutionary ecology. In the particular case of sporulating pathogens with growing lesions, phenotyping is difficult because one needs to disentangle properly pathogen spread from sporulation. By considering Phytophthora infestans on potato, we use mathematical modelling to tackle this issue and refine the assessment of pathogen response to quantitative host resistance. We elaborate a parsimonious leaf-scale model by convolving a lesion growth model and a sporulation function, after a latency period. This model is fitted to data obtained on two isolates inoculated on three cultivars with contrasted resistance level. Our results confirm a significant host-pathogen interaction on the various estimated traits, and a reduction of both pathogen spread and spore production, induced by host resistance. Most interestingly, we highlight that quantitative resistance also changes the sporulation function, the mode of which is significantly time-lagged. This alteration of the infectious period distribution on resistant hosts may have strong impacts on the dynamics of parasite populations, and should be considered when assessing the durability of disease control tactics based on plant resistance management. This inter-disciplinary work also supports the relevance of mechanistic models for analysing phenotypic data of plant-pathogen interactions.

Gene drives in plants: opportunities and challenges for weed control and engineered resilience

Plant species, populations and communities are under threat from climate change, invasive pathogens, weeds and habitat fragmentation. Despite considerable research effort invested in genome engineering for crop improvement, the development of genetic tools for the management of wild plant populations has rarely been given detailed consideration. Gene drive systems that allow direct genetic management of plant populations via the spread of fitness-altering genetic modifications could be of great utility. However, despite the rapid development of synthetic tools and their enormous promise, little explicit consideration has been given to their application in plants and, to date, they remain untested. This article considers the potential utility of gene drives for the management of wild plant populations, and examines the factors that might influence the design, spread and efficacy of synthetic drives. To gain insight into optimal ways to design and deploy synthetic drive systems, we investigate the diversity of mechanisms underlying natural gene drives and their dynamics within plant populations and species. We also review potential approaches for engineering gene drives and discuss their potential application to plant genomes. We highlight the importance of considering the impact of plant life-history and genetic architecture on the dynamics of drive, investigate the potential for different types of resistance evolution, and touch on the ethical, regulatory and social challenges ahead.

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.

A whole genome scan of SNP data suggests a lack of abundant hard selective sweeps in the genome of the broad host range plant pathogenic fungus Sclerotinia sclerotiorum

The pathogenic fungus Sclerotinia sclerotiorum infects over 600 species of plant. It is present in numerous environments throughout the world and causes significant damage to many agricultural crops. Fragmentation and lack of gene flow between populations may lead to population sub-structure. Within discrete recombining populations, positive selection may lead to a ‘selective sweep’. This is characterised by an increase in frequency of a favourable allele leading to reduction in genotypic diversity in a localised genomic region due to the phenomenon of genetic hitchhiking. We aimed to assess whether isolates of S. sclerotiorum from around the world formed genotypic clusters associated with geographical origin and to determine whether signatures of population-specific positive selection could be detected. To do this, we sequenced the genomes of 25 isolates of S. sclerotiorum collected from four different continents–Australia, Africa (north and south), Europe and North America (Canada and the northen United States) and conducted SNP based analyses of population structure and selective sweeps. Among the 25 isolates, there was evidence for two major population clusters. One of these consisted of 11 isolates from Canada, the USA and France (population 1), and the other consisted of nine isolates from Australia and one from Morocco (population 2). The rest of the isolates were genotypic outliers. We found that there was evidence of outcrossing in these two populations based on linkage disequilibrium decay. However, only a single candidate selective sweep was observed, and it was present in population 2. This sweep was close to a Major Facilitator Superfamily transporter gene, and we speculate that this gene may have a role in nutrient uptake from the host. The low abundance of selective sweeps in the S. sclerotiorum genome contrasts the numerous examples in the genomes of other fungal pathogens. This may be a result of its slow rate of evolution and low effective recombination rate due to self-fertilisation and vegetative reproduction.

Necrotrophic Exploitation and Subversion of Plant Defense: A Lifestyle or Just a Phase, and Implications in Breeding Resistance

Breeding disease-resistant plants is a critical, environmentally friendly component of any strategy to sustainably feed and clothe the 9.8 billion people expected to live on Earth by 2050. Here, I review current literature detailing plant defense responses as they relate to diverse biological outcomes; disease resistance, susceptibility, and establishment of mutualistic plant-microbial relationships. Of particular interest is the degree to which these outcomes are a function of plant-associated microorganisms' lifestyles; biotrophic, hemibiotrophic, necrotrophic, or mutualistic. For the sake of brevity, necrotrophic pathogens and the necrotrophic phase of pathogenicity are emphasized in this review, with special attention given to the host-specific pathogens that exploit defense. Defense responses related to generalist necrotrophs and mutualists are discussed in the context of excellent reviews by others. In addition, host evolutionary trade-offs of disease resistance with other desirable traits are considered in the context of breeding for durable disease resistance.

Contribution of recent technological advances to future resistance breeding

The development of durable host resistance strategies to control crop diseases is a primary need for sustainable agricultural production in the future. This article highlights the potential of recent progress in the understanding of host resistance for future cereal breeding. Much of the novel work is based on advancements in large-scale sequencing and genomics, rapid gene isolation techniques and high-throughput molecular marker technologies. Moreover, emerging applications on the pathogen side like effector identification or field pathogenomics are discussed. The combination of knowledge from both sides of cereal pathosystems will result in new approaches for resistance breeding. We describe future applications and innovative strategies to implement effective and durable strategies to combat diseases of major cereal crops while reducing pesticide dependency.

Mosaics, mixtures, rotations or pyramiding: What is the optimal strategy to deploy major gene resistance?

Once deployed uniformly in the field, genetically controlled plant resistance is often quickly overcome by pathogens, resulting in dramatic losses. Several strategies have been proposed to constrain the evolutionary potential of pathogens and thus increase resistance durability. These strategies can be classified into four categories, depending on whether resistance sources are varied across time (rotations) or combined in space in the same cultivar (pyramiding), in different cultivars within a field (cultivar mixtures) or among fields (mosaics). Despite their potential to differentially affect both pathogen epidemiology and evolution, to date the four categories of deployment strategies have never been directly compared together within a single theoretical or experimental framework, with regard to efficiency (ability to reduce disease impact) and durability (ability to limit pathogen evolution and delay resistance breakdown). Here, we used a spatially explicit stochastic demogenetic model, implemented in the R package landsepi, to assess the epidemiological and evolutionary outcomes of these deployment strategies when two major resistance genes are present. We varied parameters related to pathogen evolutionary potential (mutation probability and associated fitness costs) and landscape organization (mostly the relative proportion of each cultivar in the landscape and levels of spatial or temporal aggregation). Our results, broadly focused on qualitative resistance to rust fungi of cereal crops, show that evolutionary and epidemiological control are not necessarily correlated and that no deployment strategy is universally optimal. Pyramiding two major genes offered the highest durability, but at high mutation probabilities, mosaics, mixtures and rotations can perform better in delaying the establishment of a universally infective superpathogen. All strategies offered the same short-term epidemiological control, whereas rotations provided the best long-term option, after all sources of resistance had broken down. This study also highlights the significant impact of landscape organization and pathogen evolutionary ability in considering the optimal design of a deployment strategy.

Spatio-temporal connectivity and host resistance influence evolutionary and epidemiological dynamics of the canola pathogen Leptosphaeria maculans

Genetic, physiological and physical homogenization of agricultural landscapes creates ideal environments for plant pathogens to proliferate and rapidly evolve. Thus, a critical challenge in plant pathology and epidemiology is to design durable and effective strategies to protect cropping systems from damage caused by pathogens. Theoretical studies suggest that spatio-temporal variation in the diversity and distribution of resistant hosts across agricultural landscapes may have strong effects on the epidemiology and evolutionary potential of crop pathogens. However, we lack empirical tests of spatio-temporal deployment of host resistance to pathogens can be best used to manage disease epidemics and disrupt pathogen evolutionary dynamics in real-world systems. In a field experiment, we simulated how differences in Brassica napus resistance deployment strategies and landscape connectivity influence epidemic severity and Leptosphaeria maculans pathogen population composition. Host plant resistance, spatio-temporal connectivity [stubble loads], and genetic connectivity of the inoculum source [composition of canola stubble mixtures] jointly impacted epidemiology (disease severity) and pathogen evolution (population composition). Changes in population composition were consistent with directional selection for the ability to infect the host (infectivity), leading to changes in pathotype (multilocus phenotypes) and infectivity frequencies. We repeatedly observed decreases in the frequency of unnecessary infectivity, suggesting that carrying multiple infectivity genes is costly for the pathogen. From an applied perspective, our results indicate that varying resistance genes in space and time can be used to help control disease, even when resistance has already been overcome. Furthermore, our approach extends our ability to test not only for the efficacy of host varieties in a given year, but also for durability over multiple cropping seasons, given variation in the combination of resistance genes deployed.

Advances in Wheat and Pathogen Genomics: Implications for Disease Control

The gene pool of wheat and its wild and domesticated relatives contains a plethora of resistance genes that can be exploited to make wheat more resilient to pathogens. Only a few of these genes have been isolated and studied at the molecular level. In recent years, we have seen a shift from classical breeding to genomics-assisted breeding, which makes use of the enormous advancements in DNA sequencing and high-throughput molecular marker technologies for wheat improvement. These genomic advancements have the potential to transform wheat breeding in the near future and to significantly increase the speed and precision at which new cultivars can be bred. This review highlights the genomic improvements that have been made in wheat and its pathogens over the past years and discusses their implications for disease-resistance breeding.

Pyramiding for Resistance Durability: Theory and Practice

Durable disease resistance is a key component of global food security, and combining resistance genes into "pyramids" is an important way to increase durability of resistance. The mechanisms by which pyramids impart durability are not well known. The traditional view of resistance pyramids considers the use of major resistance gene (R-gene) combinations deployed against pathogens that are primarily asexual. Interestingly, published examples of the successful use of pyramids in the traditional sense are rare. In contrast, most published descriptions of durable pyramids in practice are for cereal rusts, and tend to indicate an association between durability and cultivars combining major R-genes with incompletely expressed, adult plant resistance genes. Pyramids have been investigated experimentally for a diversity of pathogens, and many reduce disease levels below that of the single best gene. Resistance gene combinations have been identified through phenotypic reactions, molecular markers, and challenge against effector genes. As resistance genes do not express equally in all genetic backgrounds, however, a combination of genetic information and phenotypic analyses provide the ideal scenario for testing of putative pyramids. Not all resistance genes contribute equally to pyramids, and approaches have been suggested to identify the best genes and combinations of genes for inclusion. Combining multiple resistance genes into a single plant genotype quickly is a challenge that is being addressed through alternative breeding approaches, as well as through genomics tools such as resistance gene cassettes and gene editing. Experimental and modeling tests of pyramid durability are in their infancy, but have promise to help direct future studies of pyramids. Several areas for further work on resistance gene pyramids are suggested.

Differential impact of landscape-scale strategies for crop cultivar deployment on disease dynamics, resistance durability and long-term evolutionary control

A multitude of resistance deployment strategies have been proposed to tackle the evolutionary potential of pathogens to overcome plant resistance. In particular, many landscape-based strategies rely on the deployment of resistant and susceptible cultivars in an agricultural landscape as a mosaic. However, the design of such strategies is not easy as strategies targeting epidemiological or evolutionary outcomes may not be the same. Using a stochastic spatially explicit model, we studied the impact of landscape organization (as defined by the proportion of fields cultivated with a resistant cultivar and their spatial aggregation) and key pathogen life-history traits on three measures of disease control. Our results show that short-term epidemiological dynamics are optimized when landscapes are planted with a high proportion of the resistant cultivar in low aggregation. Importantly, the exact opposite situation is optimal for resistance durability. Finally, well-mixed landscapes (balanced proportions with low aggregation) are optimal for long-term evolutionary equilibrium (defined here as the level of long-term pathogen adaptation). This work offers a perspective on the potential for contrasting effects of landscape organization on different goals of disease management and highlights the role of pathogen life history.

Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens

Genetically-controlled plant resistance can reduce the damage caused by pathogens. However, pathogens have the ability to evolve and overcome such resistance. This often occurs quickly after resistance is deployed, resulting in significant crop losses and a continuing need to develop new resistant cultivars. To tackle this issue, several strategies have been proposed to constrain the evolution of pathogen populations and thus increase genetic resistance durability. These strategies mainly rely on varying different combinations of resistance sources across time (crop rotations) and space. The spatial scale of deployment can vary from multiple resistance sources occurring in a single cultivar (pyramiding), in different cultivars within the same field (cultivar mixtures) or in different fields (mosaics). However, experimental comparison of the efficiency (i.e. ability to reduce disease impact) and durability (i.e. ability to limit pathogen evolution and delay resistance breakdown) of landscape-scale deployment strategies presents major logistical challenges. Therefore, we developed a spatially explicit stochastic model able to assess the epidemiological and evolutionary outcomes of the four major deployment options described above, including both qualitative resistance (i.e. major genes) and quantitative resistance traits against several components of pathogen aggressiveness: infection rate, latent period duration, propagule production rate, and infectious period duration. This model, implemented in the R package landsepi, provides a new and useful tool to assess the performance of a wide range of deployment options, and helps investigate the effect of landscape, epidemiological and evolutionary parameters. This article describes the model and its parameterisation for rust diseases of cereal crops, caused by fungi of the genus Puccinia. To illustrate the model, we use it to assess the epidemiological and evolutionary potential of the combination of a major gene and different traits of quantitative resistance. The comparison of the four major deployment strategies described above will be the objective of future studies.

There are many recent examples which demonstrate the evolutionary potential of plant pathogens to overcome the resistances deployed in agricultural landscapes to protect our crops. Increasingly, it is recognised that how resistance is deployed spatially and temporally can impact on rates of pathogen evolution and resistance breakdown. Such deployment strategies are mainly based on the combination of several sources of resistance at different spatiotemporal scales. However, comparison of these strategies in a predictive sense is not an easy task, owing to the logistical difficulties associated with experiments involving the spread of a pathogen at large spatio-temporal scales. Moreover, both the durability of a strategy and the epidemiological protection it provides to crops must be assessed since these evaluation criteria are not necessarily correlated. Surprisingly, no current simulation model allows a thorough comparison of the different options. Here we describe a spatio-temporal model able to simulate a wide range of deployment strategies and resistance sources. This model, implemented in the R package landsepi, facilitates assessment of both epidemiological and evolutionary outcomes across simulated scenarios. In this work, the model is used to investigate the combination of different sources of resistance against fungal diseases such as rusts of cereal crops.

Disease Management in the Genomics Era-Summaries of Focus Issue Papers

The genomics revolution has contributed enormously to research and disease management applications in plant pathology. This development has rapidly increased our understanding of the molecular mechanisms underpinning pathogenesis and resistance, contributed novel markers for rapid pathogen detection and diagnosis, and offered further insights into the genetics of pathogen populations on a larger scale. The availability of whole genome resources coupled with next-generation sequencing (NGS) technologies has helped fuel genomics-based approaches to improve disease resistance in crops. NGS technologies have accelerated the pace at which whole plant and pathogen genomes have become available, and made possible the metagenomic analysis of plant-associated microbial communities. Furthermore, NGS technologies can now be applied routinely and cost effectively to rapidly generate plant and/or pathogen genome or transcriptome marker sequences associated with virulence phenotypes in the pathogen or resistance phenotypes in the plant, potentially leading to improvements in plant disease management. In some systems, investments in plant and pathogen genomics have led to immediate, tangible benefits. This focus issue covers some of the systems. The articles in this focus issue range from overall perspective articles to research articles describing specific genomics applications for detection and control of diseases caused by nematode, viral, bacterial, fungal, and oomycete pathogens. The following are representative short summaries of the articles that appear in this Focus Issue .