An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis

Hyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypes

BACKGROUND

Precise evaluation of fungal conidia production may facilitate studies on resistance mechanisms and plant breeding for disease resistance. In this study, hyperspectral imaging (HSI) was used to quantify the sporulation of Magnaporthe oryzae on the leaves of rice cultivars grown under controlled conditions. Three rice genotypes (CO 39, Nipponbare, IR64) differing in susceptibility to blast were inoculated with M. oryzae isolates Guy 11 and Li1497. Spectral information (450-850 nm, 140 wavebands) of typical leaf blast symptoms was recorded before and after induction of sporulation of the pathogen.

RESULTS

M. oryzae produced more conidia on the highly susceptible genotype than on the moderately susceptible genotype, whereas the resistant genotype resulted in no sporulation. Changes in reflectance spectra recorded before and after induction of sporulation were significantly higher in genotype CO 39 than in Nipponbare. The spectral angle mapper algorithm for supervised classification allowed for the classification of blast symptom subareas and the quantification of lesion areas with M. oryzae sporulation. The correlation between the area under the difference spectrum (viz. spectral difference without and with sporulation) and the number of conidia per lesion and the number of conidia per lesion area was positive and count-based differences in rice - M. oryzae interaction could be reproduced in the spectral data.

CONCLUSIONS

HSI provided a precise and objective method of assessing M. oryzae conidia production on infected rice plants, revealing differences that could not be detected visually.

Enhancing the potential of phenomic and genomic prediction in winter wheat breeding using high-throughput phenotyping and deep learning

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency.

Natural variation in the pattern-triggered immunity response in plants: Investigations, implications and applications

The pattern-triggered immunity (PTI) response is triggered at the plant cell surface by the recognition of microbe-derived molecules known as microbe- or pathogen-associated molecular patterns or molecules derived from compromised host cells called damage-associated molecular patterns. Membrane-localized receptor proteins, known as pattern recognition receptors, are responsible for this recognition. Although much of the machinery of PTI is conserved, natural variation for the PTI response exists within and across species with respect to the components responsible for pattern recognition, activation of the response, and the strength of the response induced. This review describes what is known about this variation. We discuss how variation in the PTI response can be measured and how this knowledge might be utilized in the control of plant disease and in developing plant varieties with enhanced disease resistance.

SeptoSympto: a precise image analysis of Septoria tritici blotch disease symptoms using deep learning methods on scanned images

BACKGROUND

Investigations on plant-pathogen interactions require quantitative, accurate, and rapid phenotyping of crop diseases. However, visual assessment of disease symptoms is preferred over available numerical tools due to transferability challenges. These assessments are laborious, time-consuming, require expertise, and are rater dependent. More recently, deep learning has produced interesting results for evaluating plant diseases. Nevertheless, it has yet to be used to quantify the severity of Septoria tritici blotch (STB) caused by Zymoseptoria tritici-a frequently occurring and damaging disease on wheat crops.

RESULTS

We developed an image analysis script in Python, called SeptoSympto. This script uses deep learning models based on the U-Net and YOLO architectures to quantify necrosis and pycnidia on detached, flattened and scanned leaves of wheat seedlings. Datasets of different sizes (containing 50, 100, 200, and 300 leaves) were annotated to train Convolutional Neural Networks models. Five different datasets were tested to develop a robust tool for the accurate analysis of STB symptoms and facilitate its transferability. The results show that (i) the amount of annotated data does not influence the performances of models, (ii) the outputs of SeptoSympto are highly correlated with those of the experts, with a similar magnitude to the correlations between experts, and (iii) the accuracy of SeptoSympto allows precise and rapid quantification of necrosis and pycnidia on both durum and bread wheat leaves inoculated with different strains of the pathogen, scanned with different scanners and grown under different conditions.

CONCLUSIONS

SeptoSympto takes the same amount of time as a visual assessment to evaluate STB symptoms. However, unlike visual assessments, it allows for data to be stored and evaluated by experts and non-experts in a more accurate and unbiased manner. The methods used in SeptoSympto make it a transferable, highly accurate, computationally inexpensive, easy-to-use, and adaptable tool. This study demonstrates the potential of using deep learning to assess complex plant disease symptoms such as STB.

Sas3-mediated histone acetylation regulates effector gene activation in a fungal plant pathogen

IMPORTANCE

Pathogen infections require the production of effectors that enable host colonization. Effectors have diverse functions and are only expressed at certain stages of the infection cycle. Thus, effector genes are tightly regulated by several mechanisms, including chromatin remodeling. Here, we investigate the role of histone acetylation in effector gene activation in the fungal wheat pathogen Zymoseptoria tritici. We demonstrate that lysine acetyltransferases (KATs) are essential for the spatiotemporal regulation of effector genes. We show that the KAT Sas3 is involved in leaf symptom development and pycnidia formation. Importantly, our results indicate that Sas3 controls histone acetylation of effector loci and is a regulator of effector gene activation during stomatal penetration. Overall, our work demonstrates the key role of histone acetylation in regulating gene expression associated with plant infection.

Combining High-Resolution Imaging, Deep Learning, and Dynamic Modeling to Separate Disease and Senescence in Wheat Canopies

Maintenance of sufficiently healthy green leaf area after anthesis is key to ensuring an adequate assimilate supply for grain filling. Tightly regulated age-related physiological senescence and various biotic and abiotic stressors drive overall greenness decay dynamics under field conditions. Besides direct effects on green leaf area in terms of leaf damage, stressors often anticipate or accelerate physiological senescence, which may multiply their negative impact on grain filling. Here, we present an image processing methodology that enables the monitoring of chlorosis and necrosis separately for ears and shoots (stems + leaves) based on deep learning models for semantic segmentation and color properties of vegetation. A vegetation segmentation model was trained using semisynthetic training data generated using image composition and generative adversarial neural networks, which greatly reduced the risk of annotation uncertainties and annotation effort. Application of the models to image time series revealed temporal patterns of greenness decay as well as the relative contributions of chlorosis and necrosis. Image-based estimation of greenness decay dynamics was highly correlated with scoring-based estimations (r ≈ 0.9). Contrasting patterns were observed for plots with different levels of foliar diseases, particularly septoria tritici blotch. Our results suggest that tracking the chlorotic and necrotic fractions separately may enable (a) a separate quantification of the contribution of biotic stress and physiological senescence on overall green leaf area dynamics and (b) investigation of interactions between biotic stress and physiological senescence. The high-throughput nature of our methodology paves the way to conducting genetic studies of disease resistance and tolerance.

Quantitative and qualitative plant-pathogen interactions call upon similar pathogenicity genes with a spectrum of effects

Septoria leaf blotch is a foliar wheat disease controlled by a combination of plant genetic resistances and fungicides use. R-gene-based qualitative resistance durability is limited due to gene-for-gene interactions with fungal avirulence (Avr) genes. Quantitative resistance is considered more durable but the mechanisms involved are not well documented. We hypothesize that genes involved in quantitative and qualitative plant-pathogen interactions are similar. A bi-parental population of Zymoseptoria tritici was inoculated on wheat cultivar 'Renan' and a linkage analysis performed to map QTL. Three pathogenicity QTL, Qzt-I05-1, Qzt-I05-6 and Qzt-I07-13, were mapped on chromosomes 1, 6 and 13 in Z. tritici, and a candidate pathogenicity gene on chromosome 6 was selected based on its effector-like characteristics. The candidate gene was cloned by Agrobacterium tumefaciens-mediated transformation, and a pathology test assessed the effect of the mutant strains on 'Renan'. This gene was demonstrated to be involved in quantitative pathogenicity. By cloning a newly annotated quantitative-effect gene in Z. tritici that is effector-like, we demonstrated that genes underlying pathogenicity QTL can be similar to Avr genes. This opens up the previously probed possibility that 'gene-for-gene' underlies not only qualitative but also quantitative plant-pathogen interactions in this pathosystem.

Natural variation in Avr3D1 from Zymoseptoria sp. contributes to quantitative gene-for-gene resistance and to host specificity

Successful host colonization by plant pathogens requires the circumvention of host defense responses, frequently through sequence modifications in secreted pathogen proteins known as avirulence factors (Avrs). Although Avr sequences are often polymorphic, the contribution of these polymorphisms to virulence diversity in natural pathogen populations remains largely unexplored. We used molecular genetic tools to determine how natural sequence polymorphisms of the avirulence factor Avr3D1 in the wheat pathogen Zymoseptoria tritici contributed to adaptive changes in virulence. We showed that there is a continuous distribution in the magnitude of resistance triggered by different Avr3D1 isoforms and demonstrated that natural variation in an Avr gene can lead to a quantitative resistance phenotype. We further showed that homologues of Avr3D1 in two nonpathogenic sister species of Z. tritici are recognized by some wheat cultivars, suggesting that Avr-R gene-for-gene interactions can contribute to nonhost resistance. We suggest that the mechanisms underlying host range, qualitative resistance, and quantitative resistance are not exclusive.

Spatially explicit ecological modeling improves empirical characterization of plant pathogen dispersal

Dispersal is a key ecological process, but it remains difficult to measure. By recording numbers of dispersed individuals at different distances from the source, one acquires a dispersal gradient. Dispersal gradients contain information on dispersal, but they are influenced by the spatial extent of the source. How can we separate the two contributions to extract knowledge about dispersal? One could use a small, point-like source for which a dispersal gradient represents a dispersal kernel, which quantifies the probability of an individual dispersal event from a source to a destination. However, the validity of this approximation cannot be established before conducting measurements. This represents a key challenge hindering progress in characterization of dispersal. To overcome it, we formulated a theory that incorporates the spatial extent of sources to estimate dispersal kernels from dispersal gradients. Using this theory, we re-analyzed published dispersal gradients for three major plant pathogens. We demonstrated that the three pathogens disperse over substantially shorter distances compared to conventional estimates. This method will allow the researchers to re-analyze a vast number of existing dispersal gradients to improve our knowledge about dispersal. The improved knowledge has potential to advance our understanding of species' range expansions and shifts, and inform management of weeds and diseases in crops.

Image-based assessment of plant disease progression identifies new genetic loci for resistance to Ralstonia solanacearum in tomato

A major challenge in global crop production is mitigating yield loss due to plant diseases. One of the best strategies to control these losses is through breeding for disease resistance. One barrier to the identification of resistance genes is the quantification of disease severity, which is typically based on the determination of a subjective score by a human observer. We hypothesized that image-based, non-destructive measurements of plant morphology over an extended period after pathogen infection would capture subtle quantitative differences between genotypes, and thus enable identification of new disease resistance loci. To test this, we inoculated a genetically diverse biparental mapping population of tomato (Solanum lycopersicum) with Ralstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease. We acquired over 40 000 time-series images of disease progression in this population, and developed an image analysis pipeline providing a suite of 10 traits to quantify bacterial wilt disease based on plant shape and size. Quantitative trait locus (QTL) analyses using image-based phenotyping for single and multi-traits identified QTLs that were both unique and shared compared with those identified by human assessment of wilting, and could detect QTLs earlier than human assessment. Expanding the phenotypic space of disease with image-based, non-destructive phenotyping both allowed earlier detection and identified new genetic components of resistance.

Automated Quantitative Measurement of Yellow Halos Suggests Activity of Necrotrophic Effectors in Septoria tritici Blotch

Many necrotrophic plant pathogens utilize host-selective toxins or necrotrophic effectors during the infection process. We hypothesized that the chlorotic yellow halos frequently observed around necrotic lesions caused by the wheat pathogen Zymoseptoria tritici could result from the activity of necrotrophic effectors interacting with the products of toxin sensitivity genes. As an initial step toward testing this hypothesis, we developed an automated image analysis (AIA) workflow that could quantify the degree of yellow halo formation occurring in wheat leaves naturally infected by a highly diverse pathogen population under field conditions. This AIA based on statistical learning was applied to more than 10,000 naturally infected leaves collected from 335 wheat cultivars grown in a replicated field experiment. We estimated a high heritability (h² = 0.71) for the degree of yellow halo formation, suggesting that this quantitative trait has a significant genetic component. Using genome-wide association mapping, we identified six chromosome segments significantly associated with the yellow halo phenotype. Most of these segments contained candidate genes associated with targets of necrotrophic effectors in other necrotrophic pathogens. Our findings conform with the hypothesis that toxin sensitivity genes could account for a significant fraction of the observed variation in quantitative resistance to Septoria tritici blotch. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Activity and Point Mutation G699V in PcoORP1 Confer Resistance to Oxathiapiprolin in Phytophthora colocasiae Field Isolates

The oxysterol-binding protein inhibitor oxathiapiprolin is a new fungicide for controlling oomycetes diseases. Besides, laboratory mutagenesis oxathiapiprolin-resistance among phytopathogenic oomycetes in the field remains unknown. Here, the sensitivity of 97 P. colocasiae isolates to oxathiapiprolin was examined that were collected between 2011 and 2016. We obtained a baseline sensitivity with a mean EC₅₀ value of 5.2639 × 10^-4 μg mL^-1. We showed that 6/32 isolates collected in Fujian Province from 2019 to 2020 were resistant to oxathiapiprolin without a significant fitness penalty on sporulation, vegetative growth, and virulence of the field isolates. The oxathiapiprolin resistance field isolates contained the point mutation glycine to valine at 699 in PcoORP1. The point mutation G699V was verified to confer resistance of P. colocasiae to oxathiapiprolin using the CRISPR/Cas9 system. The mutation G699V decreased the binding affinity between oxathiapiprolin and PcoORP1. These results will improve our understanding of the mechanism of P. colocasiae resistance to oxathiapiprolin under field conditions.

A comparison of ImageJ and machine learning based image analysis methods to measure cassava bacterial blight disease severity

BACKGROUND

Methods to accurately quantify disease severity are fundamental to plant pathogen interaction studies. Commonly used methods include visual scoring of disease symptoms, tracking pathogen growth in planta over time, and various assays that detect plant defense responses. Several image-based methods for phenotyping of plant disease symptoms have also been developed. Each of these methods has different advantages and limitations which should be carefully considered when choosing an approach and interpreting the results.

RESULTS

In this paper, we developed two image analysis methods and tested their ability to quantify different aspects of disease lesions in the cassava-Xanthomonas pathosystem. The first method uses ImageJ, an open-source platform widely used in the biological sciences. The second method is a few-shot support vector machine learning tool that uses a classifier file trained with five representative infected leaf images for lesion recognition. Cassava leaves were syringe infiltrated with wildtype Xanthomonas, a Xanthomonas mutant with decreased virulence, and mock treatments. Digital images of infected leaves were captured overtime using a Raspberry Pi camera. The image analysis methods were analyzed and compared for the ability to segment the lesion from the background and accurately capture and measure differences between the treatment types.

CONCLUSIONS

Both image analysis methods presented in this paper allow for accurate segmentation of disease lesions from the non-infected plant. Specifically, at 4-, 6-, and 9-days post inoculation (DPI), both methods provided quantitative differences in disease symptoms between different treatment types. Thus, either method could be applied to extract information about disease severity. Strengths and weaknesses of each approach are discussed.

How large and diverse are field populations of fungal plant pathogens? The case of Zymoseptoria tritici

Pathogen populations differ in the amount of genetic diversity they contain. Populations carrying higher genetic diversity are thought to have a greater evolutionary potential than populations carrying less diversity. We used published studies to estimate the range of values associated with two critical components of genetic diversity, the number of unique pathogen genotypes and the number of spores produced during an epidemic, for the septoria tritici blotch pathogen Zymoseptoria tritici. We found that wheat fields experiencing typical levels of infection are likely to carry between 3.1 and 14.0 million pathogen genotypes per hectare and produce at least 2.1–9.9 trillion pycnidiospores per hectare. Given the experimentally derived mutation rate of 3 × 10⁻¹⁰ substitutions per site per cell division, we estimate that between 27 and 126 million pathogen spores carrying adaptive mutations to counteract fungicides and resistant cultivars will be produced per hectare during a growing season. This suggests that most of the adaptive mutations that have been observed in Z. tritici populations can emerge through local selection from standing genetic variation that already exists within each field. The consequences of these findings for disease management strategies are discussed.

Management of Septoria Tritici Blotch Using Cultivar Mixtures

Septoria tritici blotch (STB) is among the most devastating diseases in European wheat production. In recent years, there has been increased interest in using cultivar mixtures as part of an integrated control strategy against diseases. This study investigated different cultivar mixtures for their ability to control STB across three years and at seven trial sites in Denmark with a range of fungicide strategies, yielding a total of 194 individual cultivar mixture combinations. The mixtures were composed of two, three, or four cultivars that were either similar or contrasting in their susceptibility to STB. Across all trials, the cultivar mixtures reduced disease severity significantly, by 14% compared with the component cultivars grown in monoculture. The reductions were larger when the disease pressure was high and when the mixtures included more cultivars. Mixtures composed of four cultivars reduced disease severity significantly, by 24%. Across all trials, cultivar mixtures significantly increased yield by 2% compared with the component cultivars grown in monoculture. The yield increase was significant for plots treated with one or two fungicide applications, and cultivar mixtures increased yield significantly, by 4.4% in untreated plots. The yield increase was smaller for mixtures with a high proportion of resistant cultivars. Based on the results from this study, cultivar mixtures can contribute positively to an integrated pest management (IPM) strategy, by reducing disease severity for STB and increasing yield. The most pronounced benefits from cultivar mixtures were found in fields with moderate to low fungicide input, under conditions with high disease pressure, when combining four cultivars with varying susceptibilities.

Fusarium Head Blight of Small Grains in Pennsylvania: Unravelling Species Diversity, Toxin Types, Growth, and Triazole Sensitivity

Fusarium graminearum is the main causal species of Fusarium head blight (FHB) globally. Recent changes in the trichothecene (toxin) types in the North American FHB pathogens support the need for continued surveillance. In this study, 461 isolates were obtained from symptomatic spikes of wheat, spelt, barley, and rye crops during 2018 and 2019. These were all identified to species and toxin types using molecular-based approaches. An additional set of 77 F. graminearum isolates obtained from overwintering crop residues during winter 2012 were molecularly identified to toxin types. A subset of 31 F. graminearum isolates (15 15-acetyl-deoxynivalenol [15ADON] and 16 3-acetyl-deoxynivalenol [3ADON]) were assessed for mycelial growth, macroconidia, perithecia, and ascospore production, and sensitivity to two triazoles. Ninety percent of isolates obtained from the symptomatic spikes (n = 418) belonged to F. graminearum, with four other species found at a lower frequency (n = 39). The F. graminearum isolates from symptomatic spikes were mainly of the 15ADON (95%), followed by 3ADON (4%), nivalenol (0.7%), and NX-2 (0.3%) toxin types. All F. graminearum isolates obtained from overwintering residue were of the 15ADON type. The toxin types could not be differentiated based on the multivariate analysis of growth and reproduction traits. All isolates were sensitive to tebuconazole and metconazole fungicides in vitro. This study confirms the dominance of F. graminearum and suggests ecological and environmental factors, to be further identified, that lead to similar composition of toxin types in the northern United States. Our results may be useful to assess the sustainability of FHB management practices and provide a baseline for future FHB surveys.

Resistance of the Wheat Cultivar ‘Renan’ to Septoria Leaf Blotch Explained by a Combination of Strain Specific and Strain Non-Specific QTL Mapped on an Ultra-Dense Genetic Map

Quantitative resistance is considered more durable than qualitative resistance as it does not involve major resistance genes that can be easily overcome by pathogen populations, but rather a combination of genes with a lower individual effect. This durability means that quantitative resistance could be an interesting tool for breeding crops that would not systematically require phytosanitary products. Quantitative resistance has yet to reveal all of its intricacies. Here, we delve into the case of the wheat/Septoria tritici blotch (STB) pathosystem. Using a population resulting from a cross between French cultivar Renan, generally resistant to STB, and Chinese Spring, a cultivar susceptible to the disease, we built an ultra-dense genetic map that carries 148,820 single nucleotide polymorphism (SNP) markers. Phenotyping the interaction was done with two different Zymoseptoria tritici strains with contrasted pathogenicities on Renan. A linkage analysis led to the detection of three quantitative trait loci (QTL) related to resistance in Renan. These QTL, on chromosomes 7B, 1D, and 5D, present with an interesting diversity as that on 7B was detected with both fungal strains, while those on 1D and 5D were strain-specific. The resistance on 7B was located in the region of Stb8 and the resistance on 1D colocalized with Stb19. However, the resistance on 5D was new, so further designated Stb20q. Several wall-associated kinases (WAK), nucleotide-binding and leucine-rich repeats (NB-LRR) type, and kinase domain carrying genes were present in the QTL regions, and some of them were expressed during the infection. These results advocate for a role of Stb genes in quantitative resistance and for resistance in the wheat/STB pathosystem being as a whole quantitative and polygenic.

Dissecting the Biology of the Fungal Wheat Pathogen Zymoseptoria tritici: A Laboratory Workflow

The fungus Zymoseptoria tritici is one of the most devastating pathogens of wheat. Aside from its importance as a disease-causing agent, this species has emerged as a powerful model system for evolutionary genetic studies of crop-infecting fungal pathogens. Z. tritici exhibits exceptionally high levels of genetic and phenotypic diversity as well as morphological plasticity, which can make experimental studies and comparability of results obtained in different laboratories, e.g., from infection assays, challenging. Therefore, standardized experimental methods are crucial for research on Z. tritici biology and the interaction of this fungus with its wheat host. Here, we describe a suite of well-tested and optimized protocols ranging from isolation of Z. tritici field specimens to analyses of virulence assays under controlled conditions. Several biological and technical aspects of working with Z. tritici under laboratory conditions are considered and carefully described in each protocol. © 2020 The Authors. Basic Protocol 1: Purification of Z. tritici field isolates from leaf material Basic Protocol 2: Molecular identification of Z. tritici isolates Support Protocol 1: Rapid extraction of Z. tritici genomic DNA Support Protocol 2: Extraction of high-quality Z. tritici genomic DNA Basic Protocol 3: In vitro culture and long-term storage of Z. tritici isolates Basic Protocol 4: Analysis of Z. tritici virulence in wheat Support Protocol 3: Preparation of Z. tritici inoculum.

Creation and judicious application of a wheat resistance gene atlas

Disease-resistance (R) gene cloning in wheat (Triticum aestivum) has been accelerated by the recent surge of genomic resources, facilitated by advances in sequencing technologies and bioinformatics. However, with the challenges of population growth and climate change, it is vital not only to clone and functionally characterize a few handfuls of R genes, but also to do so at a scale that would facilitate the breeding and deployment of crops that can recognize the wide range of pathogen effectors that threaten agroecosystems. Pathogen populations are continually changing, and breeders must have tools and resources available to rapidly respond to those changes if we are to safeguard our daily bread. To meet this challenge, we propose the creation of a wheat R-gene atlas by an international community of researchers and breeders. The atlas would consist of an online directory from which sources of resistance could be identified and deployed to achieve more durable resistance to the major wheat pathogens, such as wheat rusts, blotch diseases, powdery mildew, and wheat blast. We present a costed proposal detailing how the interacting molecular components governing disease resistance could be captured from both the host and the pathogen through biparental mapping, mutational genomics, and whole-genome association genetics. We explore options for the configuration and genotyping of diversity panels of hexaploid and tetraploid wheat, as well as their wild relatives and major pathogens, and discuss how the atlas could inform a dynamic, durable approach to R-gene deployment. Set against the current magnitude of wheat yield losses worldwide, recently estimated at 21%, this endeavor presents one route for bringing R genes from the lab to the field at a considerable speed and quantity.

Ago1 Affects the Virulence of the Fungal Plant Pathogen Zymoseptoria tritici

In host-pathogen interactions RNA interference (RNAi) has emerged as a pivotal mechanism to modify both, the immune responses of the host as well as the pathogenicity and virulence of the pathogen. In addition, in some fungi RNAi is also known to affect chromosome biology via its effect on chromatin conformation. Previous studies reported no effect of the RNAi machinery on the virulence of the fungal plant pathogen Zymoseptoria tritici however the role of RNAi is still poorly understood in this species. Herein, we elucidate whether the RNAi machinery is conserved within the genus Zymoseptoria. Moreover, we conduct functional analyses of Argonaute and Dicer-like proteins and test if the RNAi machinery affects chromosome stability. We show that the RNAi machinery is conserved among closely related Zymoseptoria species while an exceptional pattern of allelic diversity was possibly caused by introgression. The deletion of Ago1 reduced the ability of the fungus to produce asexual propagules in planta in a quantitative matter. Chromosome stability of the accessory chromosome of Z. tritici was not prominently affected by the RNAi machinery. These results indicate, in contrast to previous finding, a role of the RNAi pathway during host infection, but not in the stability of accessory chromosomes in Z. tritici.

The maize ZmMIEL1 E3 ligase and ZmMYB83 transcription factor proteins interact and regulate the hypersensitive defence response

The plant hypersensitive response (HR), a rapid cell death at the point of pathogenesis, is mediated by nucleotide-binding site, leucine-rich repeat (NLR) resistance proteins (R-proteins) that recognize the presence of specific pathogen-derived proteins. Rp1-D21 is an autoactive maize NLR R-protein that triggers HR spontaneously. We previously mapped loci associated with variation in the strength of HR induced by Rp1-D21. Here we identify the E3 ligase ZmMIEL1 as the causal gene at a chromosome 10 modifier locus. Transient ZmMIEL1 expression in Nicotiana benthamiana reduced HR induced by Rp1-D21, while suppression of ZmMIEL1 expression in maize carrying Rp1-D21 increased HR. ZmMIEL1 also suppressed HR induced by another autoactive NLR, the Arabidopsis R-protein RPM1D505V, in N. benthamiana. We demonstrated that ZmMIEL1 is a functional E3 ligase and that the effect of ZmMIEL1 was dependent on the proteasome but also that levels of Rp1-D21 and RPM1D505V were not reduced when coexpressed with ZmMIEL1 in the N. benthamiana system. By comparison to a similar system in Arabidopsis, we identify ZmMYB83 as a potential target of ZmMIEL1. Suppression of ZmMYB83 expression in maize lines carrying Rp1-D21 suppressed HR. Suppression of ZmMIEL1 expression caused an increase in ZmMYB83 transcript and protein levels in N. benthamiana and maize. Using coimmunoprecipitation and bimolecular fluorescence complementation assays, we demonstrated that ZmMIEL1 and ZmMYB83 physically interacted. Additionally, ZmMYB83 and ZmMIEL1 regulated the expression of a set of maize very long chain fatty acid (VLCFA) biosynthetic genes that may be involved in regulating HR.

Rapid sequence evolution driven by transposable elements at a virulence locus in a fungal wheat pathogen

BACKGROUND

Plant pathogens cause substantial crop losses in agriculture production and threaten food security. Plants evolved the ability to recognize virulence factors and pathogens have repeatedly escaped recognition due rapid evolutionary change at pathogen virulence loci (i.e. effector genes). The presence of transposable elements (TEs) in close physical proximity of effector genes can have important consequences for gene regulation and sequence evolution. Species-wide investigations of effector gene loci remain rare hindering our ability to predict pathogen evolvability.

RESULTS

Here, we performed genome-wide association studies (GWAS) on a highly polymorphic mapping population of 120 isolates of Zymoseptoria tritici, the most damaging pathogen of wheat in Europe. We identified a major locus underlying significant variation in reproductive success of the pathogen and damage caused on the wheat cultivar Claro. The most strongly associated locus is intergenic and flanked by genes encoding a predicted effector and a serine-type endopeptidase. The center of the locus contained a highly dynamic region consisting of multiple families of TEs. Based on a large global collection of assembled genomes, we show that the virulence locus has undergone substantial recent sequence evolution. Large insertion and deletion events generated length variation between the flanking genes by a factor of seven (5-35 kb). The locus showed also strong signatures of genomic defenses against TEs (i.e. RIP) contributing to the rapid diversification of the locus.

CONCLUSIONS

In conjunction, our work highlights the power of combining GWAS and population-scale genome analyses to investigate major effect loci in pathogens.

Field Phenomics: Will It Enable Crop Improvement?

Field phenomics has been identified as a promising enabling technology to assist plant breeders with the development of improved cultivars for farmers. Yet, despite much investment, there are few examples demonstrating the application of phenomics within a plant breeding program. We review recent progress in field phenomics and highlight the importance of targeting breeders' needs, rather than perceived technology needs, through developing and enhancing partnerships between phenomics researchers and plant breeders.

Combining Genomic and Phenomic Information for Predicting Grain Protein Content and Grain Yield in Spring Wheat

Genomics and high throughput phenomics have the potential to revolutionize the field of wheat (Triticum aestivum L.) breeding. Genomic selection (GS) has been used for predicting various quantitative traits in wheat, especially grain yield. However, there are few GS studies for grain protein content (GPC), which is a crucial quality determinant. Incorporation of secondary correlated traits in GS models has been demonstrated to improve accuracy. The objectives of this research were to compare performance of single and multi-trait GS models for predicting GPC and grain yield in wheat and to identify optimal growth stages for collecting secondary traits. We used 650 recombinant inbred lines from a spring wheat nested association mapping (NAM) population. The population was phenotyped over 3 years (2014-2016), and spectral information was collected at heading and grain filling stages. The ability to predict GPC and grain yield was assessed using secondary traits, univariate, covariate, and multivariate GS models for within and across cycle predictions. Our results indicate that GS accuracy increased by an average of 12% for GPC and 20% for grain yield by including secondary traits in the models. Spectral information collected at heading was superior for predicting GPC, whereas grain yield was more accurately predicted during the grain filling stage. Green normalized difference vegetation index had the largest effect on the prediction of GPC either used individually or with multiple indices in the GS models. An increased prediction ability for GPC and grain yield with the inclusion of secondary traits demonstrates the potential to improve the genetic gain per unit time and cost in wheat breeding.

Genomics-Assisted Breeding for Quantitative Disease Resistances in Small-Grain Cereals and Maize

Generating genomics-driven knowledge opens a way to accelerate the resistance breeding process by family or population mapping and genomic selection. Important prerequisites are large populations that are genomically analyzed by medium- to high-density marker arrays and extensive phenotyping across locations and years of the same populations. The latter is important to train a genomic model that is used to predict genomic estimated breeding values of phenotypically untested genotypes. After reviewing the specific features of quantitative resistances and the basic genomic techniques, the possibilities for genomics-assisted breeding are evaluated for six pathosystems with hemi-biotrophic fungi: Small-grain cereals/Fusarium head blight (FHB), wheat/Septoria tritici blotch (STB) and Septoria nodorum blotch (SNB), maize/Gibberella ear rot (GER) and Fusarium ear rot (FER), maize/Northern corn leaf blight (NCLB). Typically, all quantitative disease resistances are caused by hundreds of QTL scattered across the whole genome, but often available in hotspots as exemplified for NCLB resistance in maize. Because all crops are suffering from many diseases, multi-disease resistance (MDR) is an attractive aim that can be selected by specific MDR QTL. Finally, the integration of genomic data in the breeding process for introgression of genetic resources and for the improvement within elite materials is discussed.

Chromatin Dynamics Contribute to the Spatiotemporal Expression Pattern of Virulence Genes in a Fungal Plant Pathogen

Dynamic changes in transcription profiles are key for the success of pathogens in colonizing their hosts. In many pathogens, genes associated with virulence, such as effector genes, are located in regions of the genome that are rich in transposable elements and heterochromatin. The contribution of chromatin modifications to gene expression in pathogens remains largely unknown. Using a combination of a reporter gene-based approach and chromatin immunoprecipitation, we show that the heterochromatic environment of effector genes in the fungal plant pathogen Zymoseptoria tritici is a key regulator of their specific spatiotemporal expression patterns. Enrichment in trimethylated lysine 27 of histone H3 dictates the repression of effector genes in the absence of the host. Chromatin decondensation during host colonization, featuring a reduction in this repressive modification, indicates a major role for epigenetics in effector gene induction. Our results illustrate that chromatin modifications triggered during host colonization determine the specific expression profile of effector genes at the cellular level and, hence, provide new insights into the regulation of virulence in fungal plant pathogens.IMPORTANCE Fungal plant pathogens possess a large repertoire of genes encoding putative effectors, which are crucial for infection. Many of these genes are expressed at low levels in the absence of the host but are strongly induced at specific stages of the infection. The mechanisms underlying this transcriptional reprogramming remain largely unknown. We investigated the role of the genomic environment and associated chromatin modifications of effector genes in controlling their expression pattern in the fungal wheat pathogen Zymoseptoria tritici Depending on their genomic location, effector genes are epigenetically repressed in the absence of the host and during the initial stages of infection. Derepression of effector genes occurs mainly during and after penetration of plant leaves and is associated with changes in histone modifications. Our work demonstrates the role of chromatin in shaping the expression of virulence components and, thereby, the interaction between fungal pathogens and their plant hosts.

The role of vegetative cell fusions in the development and asexual reproduction of the wheat fungal pathogen Zymoseptoria tritici

BACKGROUND

The ability of fungal cells to undergo cell-to-cell communication and anastomosis, the process of vegetative hyphal fusion, allows them to maximize their overall fitness. Previous studies in a number of fungal species have identified the requirement of several signaling pathways for anastomosis, including the so far best characterized soft (So) gene, and the MAPK pathway components MAK-1 and MAK-2 of Neurospora crassa. Despite the observations of hyphal fusions' involvement in pathogenicity and host adhesion, the connection between cell fusion and fungal lifestyles is still unclear. Here, we address the role of anastomosis in fungal development and asexual reproduction in Zymoseptoria tritici, the most important fungal pathogen of wheat in Europe.

RESULTS

We show that Z. tritici undergoes self-fusion between distinct cellular structures, and its mechanism is dependent on the initial cell density. Contrary to other fungi, cell fusion in Z. tritici only resulted in cytoplasmic mixing but not in multinucleated cell formation. The deletion of the So orthologous ZtSof1 disrupted cell-to-cell communication affecting both hyphal and germling fusion. We show that Z. tritici mutants for MAPK-encoding ZtSlt2 (orthologous to MAK-1) and ZtFus3 (orthologous to MAK-2) genes also failed to undergo anastomosis, demonstrating the functional conservation of this signaling mechanism across species. Additionally, the ΔZtSof1 mutant was severely impaired in melanization, suggesting that the So gene function is related to melanization. Finally, we demonstrated that anastomosis is dispensable for pathogenicity, but essential for the pycnidium development, and its absence abolishes the asexual reproduction of Z. tritici.

CONCLUSIONS

We demonstrate the role for ZtSof1, ZtSlt2, and ZtFus3 in cell fusions of Z. tritici. Cell fusions are essential for different aspects of the Z. tritici biology, and the ZtSof1 gene is a potential target to control septoria tritici blotch (STB) disease.

Evidence for Allele-Specific Levels of Enhanced Susceptibility of Wheat mlo Mutants to the Hemibiotrophic Fungal Pathogen Magnaporthe oryzae pv. Triticum

Barley mlo mutants are well known for their profound resistance against powdery mildew disease. Recently, mlo mutant plants were generated in hexaploid bread wheat (Triticum aestivum) with the help of transgenic (transcription-activator-like nuclease, TALEN) and non-transgenic (targeted induced local lesions in genomes, TILLING) biotechnological approaches. While full-gene knockouts in the three wheat Mlo (TaMlo) homoeologs, created via TALEN, confer full resistance to the wheat powdery mildew pathogen (Blumeria graminis f.sp. tritici), the currently available TILLING-derived Tamlo missense mutants provide only partial protection against powdery mildew attack. Here, we studied the infection phenotypes of TALEN- and TILLING-derived Tamlo plants to the two hemibiotrophic pathogens Zymoseptoria tritici, causing Septoria leaf blotch in wheat, and Magnaporthe oryzae pv. Triticum (MoT), the causal agent of wheat blast disease. While Tamlo plants showed unaltered outcomes upon challenge with Z. tritici, we found evidence for allele-specific levels of enhanced susceptibility to MoT, with stronger powdery mildew resistance correlated with more invasive growth by the blast pathogen. Surprisingly, unlike barley mlo mutants, young wheat mlo mutant plants do not show undesired pleiotropic phenotypes such as spontaneous callose deposits in leaf mesophyll cells or signs of early leaf senescence. In conclusion, our study provides evidence for allele-specific levels of enhanced susceptibility of Tamlo plants to the hemibiotrophic wheat pathogen MoT.

A tradeoff between tolerance and resistance to a major fungal pathogen in elite wheat cultivars

Tolerance and resistance represent two strategies that hosts evolved to protect themselves from pathogens. Tolerance alleviates the reduction in host fitness due to infection without reducing a pathogen's growth, whereas resistance reduces pathogen growth. We investigated the tolerance of wheat to the major fungal pathogen Zymoseptoria tritici in 335 elite wheat cultivars. We used a novel digital phenotyping approach that included 11 152 infected leaves and counted 2069 048 pathogen fruiting bodies. We discovered a new component of tolerance that is based on the relationship between the green area remaining on a leaf and the number of pathogen fruiting bodies. We found a negative correlation between tolerance and resistance among intolerant cultivars, presenting the first compelling evidence for a tradeoff between tolerance and resistance to plant pathogens. Surprisingly, the tradeoff arises due to limits in the host resources available to the pathogen and not due to metabolic constraints, contrary to what ecological theory suggests. The mechanism underlying this tradeoff may be relevant for many plant diseases in which the amount of host resources available to the pathogen can limit the pathogen population. Our analysis indicates that European wheat breeders may have selected for tolerance instead of resistance to an important pathogen.

The transcription factor Zt107320 affects the dimorphic switch, growth and virulence of the fungal wheat pathogen Zymoseptoria tritici

Zymoseptoria tritici is a filamentous fungus causing Septoria tritici blotch in wheat. The pathogen has a narrow host range and infections of grasses other than susceptible wheat are blocked early after stomatal penetration. During these abortive infections, the fungus shows a markedly different gene expression pattern. However, the underlying mechanisms causing differential gene expression during host and non-host interactions are largely unknown, but likely include transcriptional regulators responsible for the onset of an infection programme in compatible hosts. MoCOD1, a member of the fungal Zn(II)₂ Cys₆ transcription factor family, has been shown to directly affect pathogenicity in the rice blast pathogen Magnaporthe oryzae. Here, we analyse the role of the putative transcription factor Zt107320, a homologue of MoCOD1, during infection of compatible and incompatible hosts by Z. tritici. We show for the first time that Zt107320 is differentially expressed in host versus non-host infections and that lower expression corresponds to an incompatible infection of non-hosts. Applying reverse genetics approaches, we further show that Zt107320 regulates the dimorphic switch as well as the growth rate of Z. tritici and affects fungal cell wall composition in vitro. Moreover, ∆Zt107320 mutants showed reduced virulence during compatible infections of wheat. We conclude that Zt107320 directly influences pathogen fitness and propose that Zt107320 is involved in the regulation of growth processes and pathogenicity during infection.

Vitamin B6 Is Under a Tight Balance During Disease Development by Rhizoctonia solani on Different Cultivars of Potato and on Arabidopsis thaliana Mutants

Vitamin B6 is well recognized as an essential antioxidant and plays a role in stress responses. Co-expression of plant and pathogen-derived vitamin B6 genes is critical during disease development of R. solani. However, little is known about the functionality of vitamin B6 vitamers during plant-R. solani interactions and their involvement in disease tolerance. Here, we explored the possible involvement of vitamin B6 during disease progression of potato cultivars of different susceptibility levels to R. solani. A distinct pattern of gene expression, pyridoxine (PN) concentration, and fungal biomass was found in the susceptible cv. Russet Burbank and tolerant cv. Chieftain. Accumulation of reactive oxygen species (ROS) in R. solani mycelia or plant tissues applying non-fluorescence or fluorescence methods was related to up-regulation in the vitamin B6 pathway and is indicative of oxidative stress. Russet Burbank was susceptible to R. solani, which was linked to reduced amounts of VB6 content. Prior to infection, constitutive PN levels were significantly higher in Russet Burbank by 1.6-fold compared to Chieftain. Upon infection with R. solani, PN levels in infected tissues increased more in Chieftain (1.7-fold) compared to Russet Burbank (1.4-fold). R. solani AG3 infection of potato sprouts in both cultivars significantly activates the fungal and plant vitamin B6 and glutathione-S-transferase (GST) genes in a tissue-specific response. Significant fold increases of transcript abundance of the fungal genes ranged from a minimum of 3.60 (RsolSG3GST) to a maximum of 13.91 (RsolAG3PDX2) in the surrounding necrotic lesion tissues (zone 1). On the other hand, PCA showed that the top plant genes STGST and STPDX1.1 were linked to both tissues of necrotic lesions (zone 2) and their surrounding areas of necrotic lesions. Functional characterization of Arabidopsis pdx1.3 mutants challenged with R. solani provided evidence into the role of the vitamin B6 pathway in the maintenance of plant tolerance during disease progression. Overall, we demonstrate that the production of vitamin VB6 is under tight control and is an essential determinant of disease development during the interaction of R. solani with potato cultivars.

In-Field Detection and Quantification of Septoria Tritici Blotch in Diverse Wheat Germplasm Using Spectral-Temporal Features

Hyperspectral remote sensing holds the potential to detect and quantify crop diseases in a rapid and non-invasive manner. Such tools could greatly benefit resistance breeding, but their adoption is hampered by i) a lack of specificity to disease-related effects and ii) insufficient robustness to variation in reflectance caused by genotypic diversity and varying environmental conditions, which are fundamental elements of resistance breeding. We hypothesized that relying exclusively on temporal changes in canopy reflectance during pathogenesis may allow to specifically detect and quantify crop diseases while minimizing the confounding effects of genotype and environment. To test this hypothesis, we collected time-resolved canopy hyperspectral reflectance data for 18 diverse genotypes on infected and disease-free plots and engineered spectral-temporal features representing this hypothesis. Our results confirm the lack of specificity and robustness of disease assessments based on reflectance spectra at individual time points. We show that changes in spectral reflectance over time are indicative of the presence and severity of Septoria tritici blotch (STB) infections. Furthermore, the proposed time-integrated approach facilitated the delineation of disease from physiological senescence, which is pivotal for efficient selection of STB-resistant material under field conditions. A validation of models based on spectral-temporal features on a diverse panel of 330 wheat genotypes offered evidence for the robustness of the proposed method. This study demonstrates the potential of time-resolved canopy reflectance measurements for robust assessments of foliar diseases in the context of resistance breeding.

A High-Throughput Phenotyping System Using Machine Vision to Quantify Severity of Grapevine Powdery Mildew

Powdery mildews present specific challenges to phenotyping systems that are based on imaging. Having previously developed low-throughput, quantitative microscopy approaches for phenotyping resistance to Erysiphe necator on thousands of grape leaf disk samples for genetic analysis, here we developed automated imaging and analysis methods for E. necator severity on leaf disks. By pairing a 46-megapixel CMOS sensor camera, a long-working distance lens providing 3.5× magnification, X-Y sample positioning, and Z-axis focusing movement, the system captured 78% of the area of a 1-cm diameter leaf disk in 3 to 10 focus-stacked images within 13.5 to 26 seconds. Each image pixel represented 1.44 μm² of the leaf disk. A convolutional neural network (CNN) based on GoogLeNet determined the presence or absence of E. necator hyphae in approximately 800 subimages per leaf disk as an assessment of severity, with a training validation accuracy of 94.3%. For an independent image set the CNN was in agreement with human experts for 89.3% to 91.7% of subimages. This live-imaging approach was nondestructive, and a repeated measures time course of infection showed differentiation among susceptible, moderate, and resistant samples. Processing over one thousand samples per day with good accuracy, the system can assess host resistance, chemical or biological efficacy, or other phenotypic responses of grapevine to E. necator. In addition, new CNNs could be readily developed for phenotyping within diverse pathosystems or for diverse traits amenable to leaf disk assays.

Destabilization of chromosome structure by histone H3 lysine 27 methylation

Chromosome and genome stability are important for normal cell function as instability often correlates with disease and dysfunction of DNA repair mechanisms. Many organisms maintain supernumerary or accessory chromosomes that deviate from standard chromosomes. The pathogenic fungus Zymoseptoria tritici has as many as eight accessory chromosomes, which are highly unstable during meiosis and mitosis, transcriptionally repressed, show enrichment of repetitive elements, and enrichment with heterochromatic histone methylation marks, e.g., trimethylation of H3 lysine 9 or lysine 27 (H3K9me3, H3K27me3). To elucidate the role of heterochromatin on genome stability in Z. tritici, we deleted the genes encoding the methyltransferases responsible for H3K9me3 and H3K27me3, kmt1 and kmt6, respectively, and generated a double mutant. We combined experimental evolution and genomic analyses to determine the impact of these deletions on chromosome and genome stability, both in vitro and in planta. We used whole genome sequencing, ChIP-seq, and RNA-seq to compare changes in genome and chromatin structure, and differences in gene expression between mutant and wildtype strains. Analyses of genome and ChIP-seq data in H3K9me3-deficient strains revealed dramatic chromatin reorganization, where H3K27me3 is mostly relocalized into regions that are enriched with H3K9me3 in wild type. Many genome rearrangements and formation of new chromosomes were found in the absence of H3K9me3, accompanied by activation of transposable elements. In stark contrast, loss of H3K27me3 actually increased the stability of accessory chromosomes under normal growth conditions in vitro, even without large scale changes in gene activity. We conclude that H3K9me3 is important for the maintenance of genome stability because it disallows H3K27me3 in regions considered constitutive heterochromatin. In this system, H3K27me3 reduces the overall stability of accessory chromosomes, generating a "metastable" state for these quasi-essential regions of the genome.

Analysis of Epichloë festucae small secreted proteins in the interaction with Lolium perenne

Epichloë festucae is an endophyte of the agriculturally important perennial ryegrass. This species systemically colonises the aerial tissues of this host where its growth is tightly regulated thereby maintaining a mutualistic symbiotic interaction. Recent studies have suggested that small secreted proteins, termed effectors, play a vital role in the suppression of host defence responses. To date only a few effectors with important roles in mutualistic interactions have been described. Here we make use of the fully assembled E. festucae genome and EffectorP to generate a suite of 141 effector candidates. These were analysed with respect to their genome location and expression profiles in planta and in several symbiosis-defective mutants. We found an association between effector candidates and a class of transposable elements known as MITEs, but no correlation with other dynamic features of the E. festucae genome, such as transposable element-rich regions. Three effector candidates and a small GPI-anchored protein were chosen for functional analysis based on their high expression in planta compared to in culture and their differential regulation in symbiosis defective E. festucae mutants. All three candidate effector proteins were shown to possess a functional signal peptide and two could be detected in the extracellular medium by western blotting. Localization of the effector candidates in planta suggests that they are not translocated into the plant cell, but rather, are localized in the apoplastic space or are attached to the cell wall. Deletion and overexpression of the effector candidates, as well as the putative GPI-anchored protein, did not affect the plant growth phenotype or restrict growth of E. festucae mutants in planta. These results indicate that these proteins are either not required for the interaction at the observed life stages or that there is redundancy between effectors expressed by E. festucae.

Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch

Accurate, high-throughput phenotyping for quantitative traits is a limiting factor for progress in plant breeding. We developed an automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance. 335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform the GWAS. We identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four independent resistance traits. Sixteen of the intervals overlapped with known STB resistance intervals, suggesting that our phenotyping approach can identify simultaneously (i.e., in a single experiment) many previously defined STB resistance intervals. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance, perhaps representing resistance to pathogen strains that had not been tested in earlier experiments. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes. Our experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance.

Extraordinary Genome Instability and Widespread Chromosome Rearrangements During Vegetative Growth

The haploid genome of the pathogenic fungus Zymoseptoria tritici is contained on "core" and "accessory" chromosomes. While 13 core chromosomes are found in all strains, as many as eight accessory chromosomes show presence/absence variation and rearrangements among field isolates. The factors influencing these presence/absence polymorphisms are so far unknown. We investigated chromosome stability using experimental evolution, karyotyping, and genome sequencing. We report extremely high and variable rates of accessory chromosome loss during mitotic propagation in vitro and in planta Spontaneous chromosome loss was observed in 2 to >50% of cells during 4 weeks of incubation. Similar rates of chromosome loss in the closely related Zymoseptoria ardabiliae suggest that this extreme chromosome dynamic is a conserved phenomenon in the genus. Elevating the incubation temperature greatly increases instability of accessory and even core chromosomes, causing severe rearrangements involving telomere fusion and chromosome breakage. Chromosome losses do not affect the fitness of Zymoseptoria tritici in vitro, but some lead to increased virulence, suggesting an adaptive role of this extraordinary chromosome instability.

Hyperspectral Canopy Sensing of Wheat Septoria Tritici Blotch Disease

Producing quantitative and reliable measures of crop disease is essential for resistance breeding, but is challenging and time consuming using traditional phenotyping methods. Hyperspectral remote sensing has shown potential for the detection of plant diseases, but its utility for phenotyping large and diverse populations of plants under field conditions requires further evaluation. In this study, we collected canopy hyperspectral data from 335 wheat varieties using a spectroradiometer, and we investigated the use of canopy reflectance for detecting the Septoria tritici blotch (STB) disease and for quantifying the severity of infection. Canopy- and leaf-level infection metrics of STB based on traditional visual assessments and automated analyses of leaf images were used as ground truth data. Results showed (i) that canopy reflectance and the selected spectral indices show promise for quantifying STB infections, and (ii) that the normalized difference water index (NDWI) showed the best performance in detecting STB compared to other spectral indices. Moreover, partial least squares (PLS) regression models allowed for an improvement in the prediction of STB metrics. The PLS discriminant analysis (PLSDA) model calibrated based on the spectral data of four reference varieties was able to discriminate between the diseased and healthy canopies among the 335 varieties with an accuracy of 93% (Kappa = 0.60). Finally, the PLSDA model predictions allowed for the identification of wheat genotypes that are potentially more susceptible to STB, which was confirmed by the STB visual assessment. This study demonstrates the great potential of using canopy hyperspectral remote sensing to improve foliar disease assessment and to facilitate plant breeding for disease resistance.

A fungal avirulence factor encoded in a highly plastic genomic region triggers partial resistance to septoria tritici blotch

Cultivar-strain specificity in the wheat-Zymoseptoria tritici pathosystem determines the infection outcome and is controlled by resistance genes on the host side, many of which have been identified. On the pathogen side, however, the molecular determinants of specificity remain largely unknown. We used genetic mapping, targeted gene disruption and allele swapping to characterise the recognition of the new avirulence factor Avr3D1. We then combined population genetic and comparative genomic analyses to characterise the evolutionary trajectory of Avr3D1. Avr3D1 is specifically recognised by wheat cultivars harbouring the Stb7 resistance gene, triggering a strong defence response without preventing pathogen infection and reproduction. Avr3D1 resides in a cluster of putative effector genes located in a genome region populated by independent transposable element insertions. The gene was present in all 132 investigated strains and is highly polymorphic, with 30 different protein variants identified. We demonstrated that specific amino acid substitutions in Avr3D1 led to evasion of recognition. These results demonstrate that quantitative resistance and gene-for-gene interactions are not mutually exclusive. Localising avirulence genes in highly plastic genomic regions probably facilitates accelerated evolution that enables escape from recognition by resistance proteins.

Ranking Quantitative Resistance to Septoria tritici Blotch in Elite Wheat Cultivars Using Automated Image Analysis

Quantitative resistance is likely to be more durable than major gene resistance for controlling Septoria tritici blotch (STB) on wheat. Earlier studies hypothesized that resistance affecting the degree of host damage, as measured by the percentage of leaf area covered by STB lesions, is distinct from resistance that affects pathogen reproduction, as measured by the density of pycnidia produced within lesions. We tested this hypothesis using a collection of 335 elite European winter wheat cultivars that was naturally infected by a diverse population of Zymoseptoria tritici in a replicated field experiment. We used automated image analysis of 21,420 scanned wheat leaves to obtain quantitative measures of conditional STB intensity that were precise, objective, and reproducible. These measures allowed us to explicitly separate resistance affecting host damage from resistance affecting pathogen reproduction, enabling us to confirm that these resistance traits are largely independent. The cultivar rankings based on host damage were different from the rankings based on pathogen reproduction, indicating that the two forms of resistance should be considered separately in breeding programs aiming to increase STB resistance. We hypothesize that these different forms of resistance are under separate genetic control, enabling them to be recombined to form new cultivars that are highly resistant to STB. We found a significant correlation between rankings based on automated image analysis and rankings based on traditional visual scoring, suggesting that image analysis can complement conventional measurements of STB resistance, based largely on host damage, while enabling a much more precise measure of pathogen reproduction. We showed that measures of pathogen reproduction early in the growing season were the best predictors of host damage late in the growing season, illustrating the importance of breeding for resistance that reduces pathogen reproduction in order to minimize yield losses caused by STB. These data can already be used by breeding programs to choose wheat cultivars that are broadly resistant to naturally diverse Z. tritici populations according to the different classes of resistance.

Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici

We conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using quantitative trait locus (QTL) mapping. High-throughput phenotyping based on automated image analysis allowed the measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540 710 pycnidia were counted and their sizes and grey values were measured. A significant correlation was found between pycnidia size and both spore size and number. Precise measurements of percentage leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotypic datasets with a dense panel of restriction site-associated DNA sequencing (RADseq) genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and those related to pathogen reproduction. We showed that different components of virulence can be under separate genetic control. Large- and small-effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence of four accessory chromosomes with small, but significant, increases in several virulence traits, providing the first evidence for a meaningful function associated with accessory chromosomes in this organism. A large-effect QTL involved in host specialization was identified on chromosome 7, leading to the identification of candidate genes having a large effect on virulence.

Forward Genetics Approach Reveals Host Genotype-Dependent Importance of Accessory Chromosomes in the Fungal Wheat Pathogen Zymoseptoria tritici

The fungal wheat pathogen Zymoseptoria tritici possesses a large complement of accessory chromosomes showing presence/absence polymorphism among isolates. These chromosomes encode hundreds of genes; however, their functional role and why the chromosomes have been maintained over long evolutionary times are so far not known. In this study, we addressed the functional relevance of eight accessory chromosomes in reference isolate IPO323. We induced chromosome losses by inhibiting the β-tubulin assembly during mitosis using carbendazim and generated several independent isogenic strains, each lacking one of the accessory chromosomes. We confirmed chromosome losses by electrophoretic karyotyping and whole-genome sequencing. To assess the importance of the individual chromosomes during host infection, we performed in planta assays comparing disease development results in wild-type and chromosome mutant strains. Loss of the accessory chromosomes 14, 16, 18, 19, and 21 resulted in increased virulence on wheat cultivar Runal but not on cultivars Obelisk, Titlis, and Riband. Moreover, some accessory chromosomes affected the switch from biotrophy to necrotrophy as strains lacking accessory chromosomes 14, 18, 19, and 21 showed a significantly earlier onset of necrosis than the wild type on the Runal cultivar. In general, we observed that the timing of the lifestyle switch affects the fitness of Z. tritici. Taking the results together, this study was the first to use a forward-genetics approach to demonstrate a cultivar-dependent functional relevance of the accessory chromosomes of Z. tritici during host infection.

Zymoseptoria tritici is a prominent fungal pathogen of wheat of worldwide distribution. This fungus shows a remarkable genome organization, with a large number of chromosomes that are present in only some isolates and therefore considered to be “accessory” chromosomes. To date, the function of these accessory chromosomes in Z. tritici has been unknown, although their maintenance in the species over evolutionary times suggests a functional relevance. Here we deleted whole accessory chromosomes to test the effect of these chromosomes on host specificity and virulence of the fungus. We show for the first time that some accessory chromosomes of Z. tritici affect the fitness of the fungus during host infection in a cultivar-dependent manner. These results show that the accessory chromosomes encode host-specific virulence determinants having a negative effect on fitness. Understanding the population dynamic of the accessory chromosomes and the molecular interaction of pathogen and plant traits is crucial to improve wheat-breeding strategies.

How Knowledge of Pathogen Population Biology Informs Management of Septoria Tritici Blotch

Zymoseptoria tritici (previously Mycosphaerella graminicola) causes Septoria tritici blotch (STB) on wheat. The population biology of Z. tritici has been exceptionally well characterized as a result of intensive studies conducted over nearly 30 years. These studies provided important insights into the biology, epidemiology and evolutionary history of Z. tritici that will prove useful for management of STB. The well-documented, rapid adaptation of Z. tritici populations to fungicide applications and deployment of wheat cultivars carrying both major gene and quantitative resistance reflects the high evolutionary potential predicted by the large effective population size, high degree of gene flow and high levels of recombination found in field populations of Z. tritici globally. QST studies that assessed the global diversity for several important quantitative traits confirmed the adaptive potential of field populations and laid the groundwork for quantitative trait loci (QTL) mapping studies. QTL mapping elucidated the genetic architecture of each trait and led to identification of candidate genes affecting fungicide resistance, thermal adaptation, virulence, and host specialization. The insights that emerged through these analyses of Z. tritici population biology can now be used to generate actionable disease management strategies aimed at sustainably reducing losses due to STB. The high evolutionary potential found in field populations of Z. tritici requires deployment of a corresponding dynamically diverse set of control measures that integrate cultural, chemical, biological and resistance breeding strategies. In this review, we describe and prioritize STB control strategies based on current knowledge of Z. tritici population biology and propose a future research agenda oriented toward long-term STB management.