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Although parasitism is one of the most common lifestyles among eukaryotes, population genetics on parasites lag far behind those on free-living organisms. Yet, the advent of molecular markers offers great tools for studying important processes, such as dispersal, mating systems, adaptation to host and speciation. Here we highlight some studies that used molecular markers to address questions about the population genetics of fungal (including oomycetes) plant pathogens. We conclude that population genetics approaches have provided tremendous insights into the biology of a few fungal parasites and warrant more wide use in phytopathology. However, theoretical advances are badly needed to best apply the existing methods. Fungi are of prime interest not only because they are major parasites of plants and animals, but they also constitute tractable and highly useful models for understanding evolutionary processes. We hope that the emerging field of fungal evolution will attract more evolutionary biologists in the near future.

An F2 population derived from a cross between pearl millet (Pennisetum glaucum) and a wild relative (P. mollissimum) was studied in relation to inheritance of domestication traits. Preferential association between certain characters led to phenotypes similar to cultivated plants. Simple Mendelian inheritance governs traits that determine spikelet structure. A linkage group with quantitative trait loci for spike size and tillering habit as well as spikelet structure was identified.

Worldwide Puccinia striiformis f. sp. tritici (Pst) epidemics have been reported to be driven by few genetic lineages, while a high diversity is evident at the Pst Himalayan centre of diversity. This study investigated the relationship between pathotype diversity and genetic structure in Nepal, the eastern Himalayan region, which has been largely unexplored. Despite the high genetic diversity and recombinant structure detected through microsatellite genotyping, characterization of virulence phenotypes for 62 isolates identified only eight pathotypes, with two pathotypes predominant over all the populations. This is in contrast to the Pakistani and Chinese recombinant populations, where high pathotype diversity is associated with genetic diversity. The most prevalent Nepali pathotype was not a unique clonal lineage, but was represented by seven multilocus genotypes from four distinct genetic subgroups, suggesting strong directional selection on virulence genes, resulting in convergent pathotypes in distinct genetic groups. This convergent selection is discussed in comparison with clonal French and recombinant Pakistani populations. Additionally, the Nepali Pst population carried virulence to 17 out of 24 tested yellow rust resistance genes (Yr), with the absence of virulence to Victo and Early Premium and resistance genes Yr5, Yr10, Yr15, Yr24 and Yr26. Virulence to Yr2, Yr7, Yr27 and YrSu were fixed in all isolates, in line with the deployment of these resistance genes in Nepal. The results reflect the influence of resistance gene deployment on selection of virulence and pathotypes in a recombinant pathogen population, which must be considered in the context of durable resistance gene deployment. [ABSTRACT FROM AUTHOR]

Puccinia striiformisf. sp.tritici(PST), a clonal basidiomycete causing yellow rust disease on wheat, has a long record of‘overcoming’ cultivar resistance introduced by breeders. Despite the long dispersal capacity of its spores, the French population ofPSTpresents a strong geographical structure, with the presence of a specific pathotype (array of avirulence genes) at high frequencies in the south of France. The genetic diversity underlying this differentiation was analysed by microsatellite and AFLP markers. A total of 213 French isolates belonging to 10 pathotypes collected over a 15-year period were investigated. For each of the 12 microsatellites used, polymorphism resulted from a unique allelic variant associated to the south-specific pathotype. This pathotype was characterized by 40 specific markers over the total of 63 polymorphims detected using 15 AFLP primer combinations. Phylogeographical analysis indicated a strictly clonal structure of the population, and a strong genomic divergence between the northern population and a south-specific clone. Both virulence and molecular data show that the northern French population belongs to the northwestern European population, whereas the southern clone is most likely related to a Mediterranean population, the two subpopulations resulting from the ancient divergence of two clonal lineages. While the virulence complexity in the northern population may be explained by the successive introduction of corresponding resistance genes in cultivars, the maintenance of a simple virulence type in southern France, despite gene flow between the two populations, may be explained in terms of host cultivars repartition and local adaptation to specific host or climatic conditions. [ABSTRACT FROM AUTHOR]

Functional-structural plant models are increasingly being used by plant scientists to address a wide variety of questions. However, the calibration of these complex models is often challenging, mainly because of their high computational cost, and, as a result, error propagation is usually ignored. Here we applied an automatic method to the calibration of WALTer: a functional-structural wheat model that simulates the plasticity of tillering in response to competition for light. We used a Bayesian calibration method to jointly estimate the values of five parameters and quantify their uncertainty by fitting the model outputs to tillering dynamics data. We made recourse to Gaussian process metamodels in order to alleviate the computational cost of WALTer. These metamodels are built from an adaptive design that consists of successive runs of WALTer chosen by an efficient global optimization algorithm specifically adapted to this particular calibration task. The method presented here performed well on both synthetic and experimental data. It is an efficient approach for the calibration of WALTer and should be of interest for the calibration of other functional-structural plant models., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Powdery mildew is one of the most important diseases of flax and is particularly prejudicial to its yield and oil or fiber quality. This disease, caused by the obligate biotrophic ascomycete Oïdium lini , is progressing in France. Genetic resistance of varieties is critical for the control of this disease, but very few resistance genes have been identified so far. It is therefore necessary to identify new resistance genes to powdery mildew suitable to the local context of pathogenicity. For this purpose, we studied a worldwide diversity panel composed of 311 flax genotypes both phenotyped for resistance to powdery mildew resistance over 2 years of field trials in France and resequenced. Sequence reads were mapped on the CDC Bethune reference genome revealing 1,693,910 high-quality SNPs, further used for both population structure analysis and genome-wide association studies (GWASs). A number of four major genetic groups were identified, separating oil flax accessions from America or Europe and those from Asia or Middle-East and fiber flax accessions originating from Eastern Europe and those from Western Europe. A number of eight QTLs were detected at the false discovery rate threshold of 5%, located on chromosomes 1, 2, 4, 13, and 14. Taking advantage of the moderate linkage disequilibrium present in the flax panel, and using the available genome annotation, we identified potential candidate genes. Our study shows the existence of new resistance alleles against powdery mildew in our diversity panel, of high interest for flax breeding program., Competing Interests: AS and J-PT were employed by Terre De Lin. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Speck, Trouvé, Enjalbert, Geffroy, Joets and Moreau.)

Cropping system diversification through annual intercropping provides a pathway for agricultural production with reduced inputs of fertilizer and pesticides. While several studies have shown that intercrop performance depends on the genotypes used, the available evidence has not been synthesized in an overarching analysis. Here, we review the effects of genotypes in cereal/legume intercropping systems, showing how genotype choice affects mixture performance. Furthermore, we discuss the mechanisms underlying the interactions between genotype and cropping system (i.e., sole cropping vs. intercropping). Data from 69 articles fulfilling inclusion criteria were analyzed, out of which 35 articles reported land equivalent ratio (LER), yielding 262 LER data points to be extracted. The mean and median LER were 1.26 and 1.24, respectively. The extracted genotype × cropping system interaction effects on yield were reported in 71% out of 69 publications. Out of this, genotype × cropping system interaction effects were significant in 75%, of the studies, whereas 25% reported non-significant interactions. The remaining studies did not report the effects of genotype × cropping system. Phenological and morphological traits, such as differences in days to maturity, plant height, or growth habit, explained variations in the performance of mixtures with different genotypes. However, the relevant genotype traits were not described sufficiently in most of the studies to allow for a detailed analysis. A tendency toward higher intercropping performance with short cereal genotypes was observed. The results show the importance of genotype selection for better in cereal/legume intercropping. This study highlights the hitherto unrevealed aspects of genotype evaluation for intercropping systems that need to be tackled. Future research on genotype effects in intercropping should consider phenology, root growth, and soil nutrient and water acquisition timing, as well as the effects of weeds and diseases, to improve our understanding of how genotype combination and breeding may help to optimize intercropping systems., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Demie, Döring, Finckh, van der Werf, Enjalbert and Seidel.)

Increasing the cultivated diversity has been identified as a major leverage for the agroecological transition as it can help improve the resilience of low input cropping systems. For wheat, which is the most cultivated crop worldwide in terms of harvested area, the use of cultivar mixtures is spreading in several countries, but studies have seldom focused on establishing mixing rules based on plant architecture. Yet, the aerial architecture of plants and the overall canopy structure are critical for field performance as they greatly influence light interception, plant interactions and yield. The very high number of trait combinations in wheat mixtures makes it difficult to conduct experimentations on this issue, which is why a modeling approach appears to be an appropriate solution. In this study, we used WALTer, a functional structural plant model (FSPM), to simulate wheat cultivar mixtures and try to better understand how differences between cultivars in key traits of the aerial architecture influence mixture performance. We simulated balanced binary mixtures of cultivars differing for different critical plant traits: final height, leaf dimensions, leaf insertion angle and tillering capability. Our study highlights the impact of the leaf dimensions and the tillering capability on the performance of the simulated mixtures, which suggests that traits impacting the plants' leaf area index (LAI) have more influence on the performance of the stand than traits impacting the arrangement of the leaves. Our results show that the performance of mixtures is very variable depending on the values of the explored architectural traits. In particular, the best performances were achieved by mixing cultivars with different leaf dimensions and different tillering capability, which is in agreement with numerous studies linking the diversity of functional traits in plant communities to their productivity. However, some of the worst performances were also achieved by mixing varieties differing in their aerial architecture, which suggests that diversity is not a sufficient criterion to design efficient mixtures. Overall, these results highlight the importance of simulation-based explorations for establishing assembly rules to design efficient mixtures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Blanc, Barbillon, Fournier, Lecarpentier, Pradal and Enjalbert.)

Monitoring spatiotemporal changes in varietal resistance and understanding its drivers seem essential to managing plant diseases but require having access to the genetic basis of disease resistance and to its deployment. In this study, we focused on yellow rust ( Puccinia striiformis f. sp. tritici ) for three decades in France, by using field adult plant resistance levels, Yr race-specific resistance genes of varieties, presence of Puccinia striiformis f. sp. tritici pathotypes and their virulence profiles, and systematic surveys of the acreages of bread wheat varieties available at a yearly survey time and at a district level. Based on these data, we studied spatiotemporal changes in varietal resistance over the period from 1985 to 2018 in 54 French administrative districts (hereafter "departments") by using a set of relevant indicators weighted by the relative acreage proportion of the varieties sown at the department level. Our analyses revealed an increase in varietal resistance over decades that would be due to the accumulation of both quantitative resistance and different race-specific resistance genes. We suggest that, beyond breeders, several actors, including examination offices, agricultural advisory services, and farmers, may have had a substantial influence on these spatiotemporal changes, promoting more resistant varieties and the rapid replacement of newly susceptible varieties by still resistant ones at the beginning of each epidemic.

Although widely used in ecology, trait-based approaches are seldom used to study agroecosystems. In particular, there is a need to evaluate how functional trait variability among varieties of a crop species compares to the variability among wild plant species and how variety selection can modify trait syndromes. Here, we quantified 18 above- and below-ground functional traits for 57 varieties of common wheat representative of different modern selection histories. We compared trait variability among varieties and among Pooideae species, and analyzed the effect of selection histories on trait values and trait syndromes. For traits under strong selection, trait variability among varieties was less than 10% of the variability observed among Pooideae species. However, for traits not directly selected, such as root N uptake capacity, the variability was up to 75% of the variability among Pooideae species. Ammonium absorption capacity by roots was counter-selected for conventional varieties compared with organic varieties and landraces. Artificial selection also altered some trait syndromes classically reported for Pooideae. Identifying traits that have high or low variability among varieties and characterizing the hidden effects of selection on trait values and syndromes will benefit the selection of varieties to be used especially for lower N input agroecosystems., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Mixed cropping has been suggested as a resource-efficient approach to meet high produce demands while maintaining biodiversity and minimizing environmental impact. Current breeding programs do not select for enhanced general mixing ability (GMA) and neglect biological interactions within species mixtures. Clear concepts and efficient experimental designs, adapted to breeding for mixed cropping and encoded into appropriate statistical models, are lacking. Thus, a model framework for GMA and SMA (specific mixing ability) was established. Results of a simulation study showed that an incomplete factorial design combines advantages of two commonly used full factorials, and enables to estimate GMA, SMA, and their variances in a resource-efficient way. This model was extended to the Producer (Pr) and Associate (As) concept to exploit additional information based on fraction yields. It was shown that the Pr/As concept allows to characterize genotypes for their contribution to total mixture yield, and, when relating to plant traits, allows to describe biological interaction functions (BIF) in a mixed crop. Incomplete factorial designs show the potential to drastically improve genetic gain by testing an increased number of genotypes using the same amount of resources. The Pr/As concept can further be employed to maximize GMA in an informed and efficient way. The BIF of a trait can be used to optimize species ratios at harvest as well as to extend our understanding of competitive and facilitative interactions in a mixed plant community. This study provides an integrative methodological framework to promote breeding for mixed cropping., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Haug, Messmer, Enjalbert, Goldringer, Forst, Flutre, Mary-Huard and Hohmann.)

Background and Aims: Branching is a main morphogenetic process involved in the adaptation of plants to the environment. In grasses, tillering is divided into three phases: tiller emergence, cessation of tillering and tiller regression. Understanding and prediction of the tillering process is a major challenge to better control cereal yields. In this paper, we present and evaluate WALTer, an individual-based model of wheat built on simple self-adaptive rules for predicting the tillering dynamics at contrasting sowing densities., Methods: WALTer simulates the three-dimensional (3-D) development of the aerial architecture of winter wheat. Tillering was modelled using two main hypotheses: (H1) a plant ceases to initiate new tillers when a critical Green Area Index (GAIc) is reached, and (H2) the regression of a tiller occurs if its interception of light is below a threshold (PARt). The development of vegetative organs follows descriptive rules adapted from the literature. A sensitivity analysis was performed to evaluate the impact of each parameter on tillering and GAI dynamics. WALTer was parameterized and evaluated using an initial dataset providing an extensive description of GAI dynamics, and another dataset describing tillering dynamics under a wide range of sowing densities., Key Results: Sensitivity analysis indicated the predominant importance of GAIc and PARt. Tillering and GAI dynamics of expt 1 were well fit by WALTer. Once calibrated based on the agronomic density of expt 2, tillering parameters allowed an adequate prediction of tillering dynamics at contrasting sowing densities., Conclusions: Using simple rules and a small number of parameters, WALTer efficiently simulated the wheat tillering dynamics observed at contrasting densities in experimental data. These results show that the definition of a critical GAI and a threshold of PAR is a relevant way to represent, respectively, cessation of tillering and tiller regression under competition for light., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Currently, European farmers do not have access to sufficient numbers and diversity of crop species/varieties. This prevents them from designing cropping systems more resilient to abiotic and biotic stresses. Crop diversification is a key lever to reduce pest (pathogens, animal pests and weeds) pressures at all spatial levels from fields to landscapes. In this context, plant breeding should consist of: (1) increased efforts in the development of new or minor crop varieties to foster diversity in cropping systems, and (2) focus on more resilient varieties showing local adaptation. This new breeding paradigm, called here 'breeding for integrated pest management (IPM)', may boost IPM through the development of cultivars with tolerance or resistance to key pests, with the goal of reducing reliance on conventional pesticides. At the same time, this paradigm has legal and practical implications for future breeding programs, including those targeting sustainable agricultural systems. By putting these issues into the context, this article presents the key outcomes of a questionnaire survey and experts' views expressed during an EU workshop entitled 'Breeding for IPM in sustainable agricultural systems'. © 2017 Society of Chemical Industry., (© 2017 Society of Chemical Industry.)

Inferring reproductive and demographic parameters of populations is crucial to our understanding of species ecology and evolutionary potential but can be challenging, especially in partially clonal organisms. Here, we describe a new and accurate method, cloncase, for estimating both the rate of sexual vs. asexual reproduction and the effective population size, based on the frequency of clonemate resampling across generations. Simulations showed that our method provides reliable estimates of sex frequency and effective population size for a wide range of parameters. The cloncase method was applied to Puccinia striiformis f.sp. tritici, a fungal pathogen causing stripe/yellow rust, an important wheat disease. This fungus is highly clonal in Europe but has been suggested to recombine in Asia. Using two temporally spaced samples of P. striiformis f.sp. tritici in China, the estimated sex frequency was 75% (i.e. three-quarter of individuals being sexually derived during the yearly sexual cycle), indicating strong contribution of sexual reproduction to the life cycle of the pathogen in this area. The inferred effective population size of this partially clonal organism (Nc  = 998) was in good agreement with estimates obtained using methods based on temporal variations in allelic frequencies. The cloncase estimator presented herein is the first method allowing accurate inference of both sex frequency and effective population size from population data without knowledge of recombination or mutation rates. cloncase can be applied to population genetic data from any organism with cyclical parthenogenesis and should in particular be very useful for improving our understanding of pest and microbial population biology., (© 2016 John Wiley & Sons Ltd.)

Investigating the origin and dispersal pathways is instrumental to mitigate threats and economic and environmental consequences of invasive crop pathogens. In the case of Puccinia striiformis causing yellow rust on wheat, a number of economically important invasions have been reported, e.g., the spreading of two aggressive and high temperature adapted strains to three continents since 2000. The combination of sequence-characterized amplified region (SCAR) markers, which were developed from two specific AFLP fragments, differentiated the two invasive strains, PstS1 and PstS2 from all other P. striiformis strains investigated at a worldwide level. The application of the SCAR markers on 566 isolates showed that PstS1 was present in East Africa in the early 1980s and then detected in the Americas in 2000 and in Australia in 2002. PstS2 which evolved from PstS1 became widespread in the Middle East and Central Asia. In 2000, PstS2 was detected in Europe, where it never became prevalent. Additional SSR genotyping and virulence phenotyping revealed 10 and six variants, respectively, within PstS1 and PstS2, demonstrating the evolutionary potential of the pathogen. Overall, the results suggested East Africa as the most plausible origin of the two invasive strains. The SCAR markers developed in the present study provide a rapid, inexpensive, and efficient tool to track the distribution of P. striiformis invasive strains, PstS1 and PstS2.

Multiparental populations are innovative tools for fine mapping large numbers of loci. Here we explored the application of a wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population for QTL mapping. This population was created by 12 generations of free recombination among 60 founder lines, following modification of the mating system from strict selfing to strict outcrossing using the ms1b nuclear male sterility gene. Available parents and a subset of 380 SSD lines of the resulting MAGIC population were phenotyped for earliness and genotyped with the 9K i-Select SNP array and additional markers in candidate genes controlling heading date. We demonstrated that 12 generations of strict outcrossing rapidly and drastically reduced linkage disequilibrium to very low levels even at short map distances and also greatly reduced the population structure exhibited among the parents. We developed a Bayesian method, based on allelic frequency, to estimate the contribution of each parent in the evolved population. To detect loci under selection and estimate selective pressure, we also developed a new method comparing shifts in allelic frequency between the initial and the evolved populations due to both selection and genetic drift with expectations under drift only. This evolutionary approach allowed us to identify 26 genomic areas under selection. Using association tests between flowering time and polymorphisms, 6 of these genomic areas appeared to carry flowering time QTL, 1 of which corresponds to Ppd-D1, a major gene involved in the photoperiod sensitivity. Frequency shifts at 4 of 6 areas were consistent with earlier flowering of the evolved population relative to the initial population. The use of this new outcrossing wheat population, mixing numerous initial parental lines through multiple generations of panmixia, is discussed in terms of power to detect genes under selection and association mapping. Furthermore we provide new statistical methods for use in future analyses of multiparental populations., (Copyright © 2015 by the Genetics Society of America.)

Understanding the mode of temporal maintenance of plant pathogens is an important domain of microbial ecology research. Due to the inconspicuous nature of microbes, their temporal maintenance cannot be studied directly through tracking individuals and their progeny. Here, we suggest a series of population genetic analyses on molecular marker variation in temporally spaced samples to infer about the relative contribution of sexual reproduction, off-season survival and migration to the temporal maintenance of pathogen populations. We used the proposed approach to investigate the temporal maintenance of wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici (PST), in the Himalayan region of Pakistan. Multilocus microsatellite genotyping of PST isolates revealed high genotypic diversity and recombinant population structure across all locations, confirming the existence of sexual reproduction in this region. The genotypes were assigned to four genetic groups, revealing a clear differentiation between zones with and without Berberis spp., the alternate host of PST, with an additional subdivision within the Berberis zone. The lack of any differentiation between samples across two sampling years, and the very infrequent resampling of multilocus genotypes over years at a given location was consistent with limited over-year clonal survival, and a limited genetic drift. The off-season oversummering population in the Berberis zone, likely to be maintained locally, served as a source of migrants contributing to the temporal maintenance in the non-Berberis zone. Our study hence demonstrated the contribution of both sexual recombination and off-season oversummering survival to the temporal maintenance of the pathogen. These new insights into the population biology of PST highlight the general usefulness of the analytical approach proposed., (© 2013 John Wiley & Sons Ltd.)

Analyses of large-scale population structure of pathogens enable the identification of migration patterns, diversity reservoirs or longevity of populations, the understanding of current evolutionary trajectories and the anticipation of future ones. This is particularly important for long-distance migrating fungal pathogens such as Puccinia striiformis f.sp. tritici (PST), capable of rapid spread to new regions and crop varieties. Although a range of recent PST invasions at continental scales are well documented, the worldwide population structure and the center of origin of the pathogen were still unknown. In this study, we used multilocus microsatellite genotyping to infer worldwide population structure of PST and the origin of new invasions based on 409 isolates representative of distribution of the fungus on six continents. Bayesian and multivariate clustering methods partitioned the set of multilocus genotypes into six distinct genetic groups associated with their geographical origin. Analyses of linkage disequilibrium and genotypic diversity indicated a strong regional heterogeneity in levels of recombination, with clear signatures of recombination in the Himalayan (Nepal and Pakistan) and near-Himalayan regions (China) and a predominant clonal population structure in other regions. The higher genotypic diversity, recombinant population structure and high sexual reproduction ability in the Himalayan and neighboring regions suggests this area as the putative center of origin of PST. We used clustering methods and approximate Bayesian computation (ABC) to compare different competing scenarios describing ancestral relationship among ancestral populations and more recently founded populations. Our analyses confirmed the Middle East-East Africa as the most likely source of newly spreading, high-temperature-adapted strains; Europe as the source of South American, North American and Australian populations; and Mediterranean-Central Asian populations as the origin of South African populations. Although most geographic populations are not markedly affected by recent dispersal events, this study emphasizes the influence of human activities on recent long-distance spread of the pathogen.