Quantitative pathogenicity and host adaptation in a fungal plant pathogen revealed by whole-genome sequencing.

Knowledge of genetic determinism and evolutionary dynamics mediating host-pathogen interactions is essential to manage fungal plant diseases. Studies on the genetic architecture of fungal pathogenicity often focus on large-effect effector genes triggering strong, qualitative resistance. It is not clear how this translates to predominately quantitative interactions. Here, we use the Zymoseptoria tritici-wheat model to elucidate the genetic architecture of quantitative pathogenicity and mechanisms mediating host adaptation. With a multi-host genome-wide association study, we identify 19 high-confidence candidate genes associated with quantitative pathogenicity. Analysis of genetic diversity reveals that sequence polymorphism is the main evolutionary process mediating differences in quantitative pathogenicity, a process that is likely facilitated by genetic recombination and transposable element dynamics. Finally, we use functional approaches to confirm the role of an effector-like gene and a methyltransferase in phenotypic variation. This study highlights the complex genetic architecture of quantitative pathogenicity, extensive diversifying selection and plausible mechanisms facilitating pathogen adaptation.

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.

Correction: The genetic identity of neighboring plants in intraspecific mixtures modulates disease susceptibility of both wheat and rice.

[This corrects the article DOI: 10.1371/journal.pbio.3002287.].

The genetic identity of neighboring plants in intraspecific mixtures modulates disease susceptibility of both wheat and rice.

Mixing crop cultivars has long been considered as a way to control epidemics at the field level and is experiencing a revival of interest in agriculture. Yet, the ability of mixing to control pests is highly variable and often unpredictable in the field. Beyond classical diversity effects such as dispersal barrier generated by genotypic diversity, several understudied processes are involved. Among them is the recently discovered neighbor-modulated susceptibility (NMS), which depicts the phenomenon that susceptibility in a given plant is affected by the presence of another healthy neighboring plant. Despite the putative tremendous importance of NMS for crop science, its occurrence and quantitative contribution to modulating susceptibility in cultivated species remains unknown. Here, in both rice and wheat inoculated in greenhouse conditions with foliar fungal pathogens considered as major threats, using more than 200 pairs of intraspecific genotype mixtures, we experimentally demonstrate the occurrence of NMS in 11% of the mixtures grown in experimental conditions that precluded any epidemics. Thus, the susceptibility of these 2 major crops results from indirect effects originating from neighboring plants. Quite remarkably, the levels of susceptibility modulated by plant-plant interactions can reach those conferred by intrinsic basal immunity. These findings open new avenues to develop more sustainable agricultural practices by engineering less susceptible crop mixtures thanks to emergent but now predictable properties of mixtures.

A secreted protease-like protein in Zymoseptoria tritici is responsible for avirulence on Stb9 resistance gene in wheat.

Zymoseptoria tritici is the fungal pathogen responsible for Septoria tritici blotch on wheat. Disease outcome in this pathosystem is partly determined by isolate-specific resistance, where wheat resistance genes recognize specific fungal factors triggering an immune response. Despite the large number of known wheat resistance genes, fungal molecular determinants involved in such cultivar-specific resistance remain largely unknown. We identified the avirulence factor AvrStb9 using association mapping and functional validation approaches. Pathotyping AvrStb9 transgenic strains on Stb9 cultivars, near isogenic lines and wheat mapping populations, showed that AvrStb9 interacts with Stb9 resistance gene, triggering an immune response. AvrStb9 encodes an unusually large avirulence gene with a predicted secretion signal and a protease domain. It belongs to a S41 protease family conserved across different filamentous fungi in the Ascomycota class and may constitute a core effector. AvrStb9 is also conserved among a global Z. tritici population and carries multiple amino acid substitutions caused by strong positive diversifying selection. These results demonstrate the contribution of an 'atypical' conserved effector protein to fungal avirulence and the role of sequence diversification in the escape of host recognition, adding to our understanding of host-pathogen interactions and the evolutionary processes underlying pathogen adaptation.

A major genetic locus in neighbours controls changes of gene expression and susceptibility in intraspecific rice mixtures.

Reports indicate that intraspecific neighbours alter the physiology of focal plants, and with a few exceptions, their molecular responses to neighbours are unknown. Recently, changes in susceptibility to pathogen resulting from such interactions were demonstrated, a phenomenon called neighbour-modulated susceptibility (NMS). However, the genetics of NMS and the associated molecular responses are largely unexplored. Here, we analysed in rice the modification of biomass and susceptibility to the blast fungus pathogen in the Kitaake focal genotype in the presence of 280 different neighbours. Using genome-wide association studies, we identified the loci in the neighbour that determine the response in Kitaake. Using a targeted transcriptomic approach, we characterized the molecular responses in focal plants co-cultivated with various neighbours inducing a reduction in susceptibility. Our study demonstrates that NMS is controlled by one major locus in the rice genome of its neighbour. Furthermore, we show that this locus can be associated with characteristic patterns of gene expression in focal plant. Finally, we propose an hypothesis where Pi could play a role in explaining this case of NMS. Our study sheds light on how plants affect the physiology in their neighbourhood and opens perspectives for understanding plant-plant interactions.

From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat.

Agroecosystem diversification through increased crop genetic diversity could provide multiple services such as improved disease control or increased productivity. However, we still poorly understand how genetic diversity affects agronomic performance. We grew 179 inbred lines of durum wheat in pure stands and in 202 binary mixtures in field conditions. We then tested the effect of allelic richness between genotypes and genotype richness on grain yield and Septoria tritici blotch disease. Allelic richness was tested at 19K single nucleotide polymorphisms distributed along the durum wheat genome. Both genotype richness and allelic richness could be equal to 1 or 2. Mixtures were overall more productive and less diseased than their pure stand components. Yet, we identified one locus at which allelic richness between genotypes was associated with increased disease severity and decreased grain yield. The effect of allelic richness at this locus was stronger than the effect of genotype richness on grain yield (-7.6% vs +5.7%). Our results suggest that positive effects of crop diversity can be reversed by unfavourable allelic associations. This highlights the need to integrate genomic data into crop diversification strategies. More generally, investigating plant-plant interactions at the genomic level is promising to better understand biodiversity-ecosystem functioning relationships.

The Rice DNA-Binding Protein ZBED Controls Stress Regulators and Maintains Disease Resistance After a Mild Drought.

BACKGROUND: Identifying new sources of disease resistance and the corresponding underlying resistance mechanisms remains very challenging, particularly in Monocots. Moreover, the modification of most disease resistance pathways made so far is detrimental to tolerance to abiotic stresses such as drought. This is largely due to negative cross-talks between disease resistance and abiotic stress tolerance signaling pathways. We have previously described the role of the rice ZBED protein containing three Zn-finger BED domains in disease resistance against the fungal pathogen Magnaporthe oryzae. The molecular and biological functions of such BED domains in plant proteins remain elusive. RESULTS: Using Nicotiana benthamiana as a heterologous system, we show that ZBED localizes in the nucleus, binds DNA, and triggers basal immunity. These activities require conserved cysteine residues of the Zn-finger BED domains that are involved in DNA binding. Interestingly, ZBED overexpressor rice lines show increased drought tolerance. More importantly, the disease resistance response conferred by ZBED is not compromised by drought-induced stress. CONCLUSIONS: Together our data indicate that ZBED might represent a new type of transcriptional regulator playing simultaneously a positive role in both disease resistance and drought tolerance. We demonstrate that it is possible to provide disease resistance and drought resistance simultaneously.

Emergence of Southern Rice Black-Streaked Dwarf Virus in the Centuries-Old Chinese Yuanyang Agrosystem of Rice Landraces.

Southern rice black-streaked dwarf virus (SRBSDV), which causes severe disease symptoms in rice (Oriza sativa L.) has been emerging in the last decade throughout northern Vietnam, southern Japan and southern, central and eastern China. Here we attempt to quantify the prevalence of SRBSDV in the Honghe Hani rice terraces system (HHRTS)-a Chinese 1300-year-old traditional rice production system. We first confirm that genetically diverse rice varieties are still being cultivated in the HHRTS and categorize these varieties into three main genetic clusters, including the modern hybrid varieties group (MH), the Hongyang improved modern variety group (HY) and the traditional indica landraces group (TIL). We also show over a 2-year period that SRBSDV remains prevalent in the HHRTS (20.1% prevalence) and that both the TIL (17.9% prevalence) and the MH varieties (5.1% prevalence) were less affected by SRBSDV than were the HY varieties (30.2% prevalence). Collectively we suggest that SRBSDV isolates are freely moving within the HHRTS and that TIL, HY and MH rice genetic clusters are not being preferentially infected by particular SRBSDV lineages. Given that SRBSDV can cause 30-50% rice yield losses, our study emphasizes both the need to better monitor the disease in the HHRTS, and the need to start considering ways to reduce its burden on rice production.

A small secreted protein in Zymoseptoria tritici is responsible for avirulence on wheat cultivars carrying the Stb6 resistance gene.

Zymoseptoria tritici is the causal agent of Septoria tritici blotch, a major pathogen of wheat globally and the most damaging pathogen of wheat in Europe. A gene-for-gene (GFG) interaction between Z. tritici and wheat cultivars carrying the Stb6 resistance gene has been postulated for many years, but the genes have not been identified. We identified AvrStb6 by combining quantitative trait locus mapping in a cross between two Swiss strains with a genome-wide association study using a natural population of c. 100 strains from France. We functionally validated AvrStb6 using ectopic transformations. AvrStb6 encodes a small, cysteine-rich, secreted protein that produces an avirulence phenotype on wheat cultivars carrying the Stb6 resistance gene. We found 16 nonsynonymous single nucleotide polymorphisms among the tested strains, indicating that AvrStb6 is evolving very rapidly. AvrStb6 is located in a highly polymorphic subtelomeric region and is surrounded by transposable elements, which may facilitate its rapid evolution to overcome Stb6 resistance. AvrStb6 is the first avirulence gene to be functionally validated in Z. tritici, contributing to our understanding of avirulence in apoplastic pathogens and the mechanisms underlying GFG interactions between Z. tritici and wheat.

Pathogen effectors and plant immunity determine specialization of the blast fungus to rice subspecies.

Understanding how fungi specialize on their plant host is crucial for developing sustainable disease control. A traditional, centuries-old rice agro-system of the Yuanyang terraces was used as a model to show that virulence effectors of the rice blast fungus Magnaporthe oryzaeh play a key role in its specialization on locally grown indica or japonica local rice subspecies. Our results have indicated that major differences in several components of basal immunity and effector-triggered immunity of the japonica and indica rice varieties are associated with specialization of M. oryzae. These differences thus play a key role in determining M. oryzae host specificity and may limit the spread of the pathogen within the Yuanyang agro-system. Specifically, the AVR-Pia effector has been identified as a possible determinant of the specialization of M. oryzae to local japonica rice.

Transcriptional Basis of Drought-Induced Susceptibility to the Rice Blast Fungus Magnaporthe oryzae.

Plants are often facing several stresses simultaneously. Understanding how they react and the way pathogens adapt to such combinational stresses is poorly documented. Here, we developed an experimental system mimicking field intermittent drought on rice followed by inoculation by the pathogenic fungus Magnaporthe oryzae. This experimental system triggers an enhancement of susceptibility that could be correlated with the dampening of several aspects of plant immunity, namely the oxidative burst and the transcription of several pathogenesis-related genes. Quite strikingly, the analysis of fungal transcription by RNASeq analysis under drought reveals that the fungus is greatly modifying its virulence program: genes coding for small secreted proteins were massively repressed in droughted plants compared to unstressed ones whereas genes coding for enzymes involved in degradation of cell-wall were induced. We also show that drought can lead to the partial breakdown of several major resistance genes by affecting R plant gene and/or pathogen effector expression. We propose a model where a yet unknown plant signal can trigger a change in the virulence program of the pathogen to adapt to a plant host that was affected by drought prior to infection.

Cytokinin Production by the Rice Blast Fungus Is a Pivotal Requirement for Full Virulence.

Plants produce cytokinin (CK) hormones for controlling key developmental processes like source/sink distribution, cell division or programmed cell-death. Some plant pathogens have been shown to produce CKs but the function of this mimicry production by non-tumor inducing pathogens, has yet to be established. Here we identify a gene required for CK biosynthesis, CKS1, in the rice blast fungus Magnaporthe oryzae. The fungal-secreted CKs are likely perceived by the plant during infection since the transcriptional regulation of rice CK-responsive genes is altered in plants infected by the mutants in which CKS1 gene was deleted. Although cks1 mutants showed normal in vitro growth and development, they were severely affected for in planta growth and virulence. Moreover, we showed that the cks1 mutant triggered enhanced induction of plant defenses as manifested by an elevated oxidative burst and expression of defense-related markers. In addition, the contents of sugars and key amino acids for fungal growth were altered in and around the infection site by the cks1 mutant in a different manner than by the control strain. These results suggest that fungal-derived CKs are key effectors required for dampening host defenses and affecting sugar and amino acid distribution in and around the infection site.

Genes under positive selection in a model plant pathogenic fungus, Botrytis.

The rapid evolution of particular genes is essential for the adaptation of pathogens to new hosts and new environments. Powerful methods have been developed for detecting targets of selection in the genome. Here we used divergence data to compare genes among four closely related fungal pathogens adapted to different hosts to elucidate the functions putatively involved in adaptive processes. For this goal, ESTs were sequenced in the specialist fungal pathogens Botrytis tulipae and Botrytis ficariarum, and compared with genome sequences of Botrytis cinerea and Sclerotinia sclerotiorum, responsible for diseases on over 200 plant species. A maximum likelihood-based analysis of 642 predicted orthologs detected 21 genes showing footprints of positive selection. These results were validated by resequencing nine of these genes in additional Botrytis species, showing they have also been rapidly evolving in other related species. Twenty of the 21 genes had not previously been identified as pathogenicity factors in B. cinerea, but some had functions related to plant-fungus interactions. The putative functions were involved in respiratory and energy metabolism, protein and RNA metabolism, signal transduction or virulence, similarly to what was detected in previous studies using the same approach in other pathogens. Mutants of B. cinerea were generated for four of these genes as a first attempt to elucidate their functions.