Plant-plant interactions modulate foliar disease susceptibility in intraspecific mixtures. However, the molecular events including signals and responses underlying the reduction in disease susceptibility remain largely unexplored. Here, we developed an experimental system that can abolish root-mediated interactions between plants in a model of bread wheat varietal mixture. We then performed transcriptomic and metabolomic analyses to uncover the molecular responses linked to decreased susceptibility to Septoria tritici blotch in plant-plant interactions. Our analysis revealed that disrupting root chemical interactions impaired the reduction in susceptibility to Septoria and identified phenolic compounds as potential key mediators. The plant-plant interactions under study triggered significant molecular changes in specialized metabolism, biotic interactions, transporters, and responses to resources. Disrupting root interactions canceled both the macroscopic and molecular responses, thus providing a strong link between them. These insights provide a deeper understanding of the molecular basis of plant-plant interactions and the processes involved in reducing disease susceptibility in intraspecific mixtures. ### Competing Interest Statement The authors have declared no competing interest. Agence Nationale de la Recherche, https://ror.org/00rbzpz17, ANR-20-PCPA-0006, ANR-19-CE20-0005

The fungal phytotoxin pyriculol, produced by Magnaporthe oryzae, is potentially implicated in rice blast pathogenesis due to its necrosis-inducing activity. However, its functional role remained enigmatic. Here, we demonstrate that pyriculol does not act as a virulence factor for M. oryzae, as pathogenicity assays using transgenic fungal strains with altered pyriculol biosynthesis showed no correlation between pyriculol levels and disease severity across diverse rice genotypes. Strikingly, exogenous application of pyriculol or its isomer pyriculariol significantly enhanced rice resistance to M. oryzae, reducing lesion expansion by 30% and amplifying oxidative burst and defence-related gene expression (OsPR1a, OsPBZ1, and OsCPS4). Mechanistically, pyriculol mimicked salicylic acid (SA) by suppressing early jasmonate (JA) biosynthesis genes (OsAOS1/2 and OsAOC) and JA-responsive JAZ transcripts post-wounding, yet uniquely spared OsJAR1, enabling systemic JA-Ile conversion from methyl jasmonate. This selective modulation decoupled local JA-SA antagonism, promoting SA-driven defence priming while permitting systemic JA signalling. Histological analyses revealed that pyriculol-induced host cell death restricted fungal hyphal progression, synergizing with pathogen-triggered phytoalexin biosynthesis. Our findings redefine pyriculol as a fungal metabolite that paradoxically bolsters rice immunity via phytohormone crosstalk, offering novel insights into host-pathogen co-evolution and potential applications in plant defence potentiation.

Benzoxazinoids are indole-derived specialized metabolites released into the soil through root exudates. Initially studied for their allelopathic and toxic effects, they are now recognized as broad regulators of plant-organism interactions, including microbiome-mediated pathogen resistance. However, whether benzoxazinoid-containing root exudates can directly influence disease susceptibility in neighboring plants remains unclear. Using an agriculturally relevant rice-maize co-culture system, we show that benzoxazinoids naturally exuded by maize roots are taken up by rice roots and are associated with reduced rice blast disease in leaves. This protection occurs without detectable benzoxazinoid accumulation in rice leaves, constitutive immune activation or decreased plant height. Instead, benzoxazinoid uptake by rice roots is associated with chromatin hyperacetylation, increased expression of key phenylpropanoid biosynthetic genes and broad metabolic reprogramming. These responses extend systemically to leaves, where rice establishes a defense-related chemical state distinct from the systemic acquired resistance previously observed in benzoxazinoid-dependent, microbiome-mediated plant-soil feedbacks. Our findings support a model in which specialized metabolites exuded by one crop species are acquired by a neighbouring species and trigger chromatin-associated metabolic reprogramming linked to systemic chemical defence. This study provides a molecular framework connecting plant-plant chemical interactions, root exudation, chromatin regulation and disease susceptibility.

The interactions between co-cultivated plant cultivars are increasingly recognized as influencing their susceptibility to pathogens in mixtures. However, the underlying mechanisms remain largely unexplored. Using a model of durum wheat cultivar mixtures where susceptibility to Septoria foliar disease is increased, we combined aerial and root phenotyping with transcriptional analyses and untargeted metabolomics to elucidate the potential signaling cascade driving this modulation of susceptibility. We observed contrasting root architectures between cultivars in mixtures. Molecular analysis showed a delayed induction of defense-related genes and metabolites following pathogen inoculation in plants grown in mixtures compared with in a pure stand. The findings suggest that root architecture potentially triggers a competitive response that could delay the induction of defense responses following pathogen inoculation. Altogether, these results point to a possible interplay between root architecture, resource competition, plant metabolism, and defense modulation in shaping plant-pathogen interactions within varietal mixtures.

High-yielding elite rice cultivars exhibit limited genetic variability, raising concerns about our capacity to sustain productivity in the face of changing biotic and abiotic threats. Meeting the challenges that lie ahead largely depends on our ability to make use of novel sources of genetic variation and re-engineer agrosystems. Here, we report on the evolutionary history and population genetic structure of 353 accessions representing 91 landraces from China’s centuries-old Yuanyang terraces of rice paddies (YYT). We found that the indica YYT landrace population is genetically structured and exhibits high standard variation. Analysis of natural selection reveals that innate immunity genes have a marked difference in coevolutionary dynamics between modern and traditional rice, characterized by a stronger influence of directional selection, which reduces diversity, in modern varieties. Our study highlights the importance of preserving landraces and the need for targeted efforts to integrate the standing variation in landraces into new varieties. ### Competing Interest Statement The authors have declared no competing interest. National Key R&D Program of China, 2023YFE0107500 Yunnan Fundamental Research Projects, 202401AS070002 National Natural Science Foundation of China, 31801792, 31960554 Yunnan Provincial Major Science and Technology Project, 202402AE090026 Yunnan Xingdian Talent Support Program SPE division of INRAE, Plantomix

Crop losses to pests, or crop gains to diversification: what matters most? This is a pivotal question for the acceptance of crop diversification solutions by farmers and breeders. At the intraspecific level in particular, the magnitude of beneficial effects of mixing varieties on crop yield compared to disease attacks and weed invasion in the absence of pesticide remains questioned. Here, we quantified for the first time the relative importance of different types of biotic interactions – crop-crop interactions, crop-fungi interactions and crop-weed interactions, on grain yields in a region of the world where alternative agricultural practices are urgently needed to face the multiple pressures induced by global changes. We evaluated the performance of ten upland rice varieties of Madagascar highlands using a field trial where all varieties were grown in pure stands and in bi-variety mixtures. Grain production and disease attacks by Pyricularia oryzea were assessed in all varieties and plots. Weed biomass was recorded in all plots. We also measured plant traits involved in plant-plant interactions - plant height and flowering time in particular - for all plots and varieties to identify generic assembly rules for optimizing the performance of varietal mixtures. We found strong positive effects of rice mixture on both crop yield and pathogen resistance while weed biomass remained constant and high whatever the experimental condition. When statistically controlling for one pressure, we demonstrated that the beneficial effects of crop-crop interactions on yield largely overcame the negative effects of crop-fungi and crop-weed interactions. The average height of varieties in mixtures as well as their height plasticity had strong predictive power of crop yields, confirming the great potential of trait-based approaches to design innovative cropping system. Overall, the predominant, positive effect of varietal mixtures over disease and weed pressures represents a key argument for crop diversification.

Varietal mixtures are a promising agro-ecological approach to stabilizing yields by reducing diseases. The effects of mixtures stem from modifications of epidemiological processes and plant-plant interactions, which are often underestimated and could explain some of the paradoxical observations that have been made in field trials. The role of plant-plant interactions in modifying the susceptibility of bread wheat and durum wheat to Septoria tritici blotch (STB) has not been determined. By producing full matrices of binary mixtures of varieties of each of these species in the absence of epidemics, this study aimed to determine the effect of such plant-plant interactions on STB symptoms-specifically area of necrosis (lesions) and production of pycnidia (spore-containing structures). We employed statistical modeling to compare the mean and variance of the phenotypes of focal plants across all mixture combinations of different genotypes versus the pure condition (one genotype only), and in each specific mixture versus pure conditions. The results demonstrated significant effects of plant-plant interactions on wheat susceptibility to STB. Notably, these interactions had specific rather than general effects, with some but not all genotypic combinations significantly influencing the susceptibility of the focal plant to STB. Furthermore, mixtures resulted in reduced necrosis with lower variance, but increased pycnidia formation. These results reinforce the need to consider specific plant-plant interactions for their contribution to trait means and variances in varietal mixtures.

Increasing intraspecific diversity within crop systems is a promising strategy to manage aerial diseases, particularly those caused by fungal aerial pathogens. This review examines how cultivar mixtures reduce disease incidence and severity using the phytobiome framework, identifying three major types of processes: (1) physical ones, which alter disease dynamics through dilution effects, barrier effects, and microclimate modifications; (2) processes that are mediated by microbial interactions, which influence disease severity via induced resistance and indirect plant–plant interactions mediated by the microbiome; and (3) processes involving direct plant–plant interactions, where danger signaling and signaling from healthy neighbors modulate plant physiology and immunity through resource management and molecular cues. This review provides a comprehensive understanding of how cultivar mixtures enhance disease resistance and emphasizes that direct plant–plant interactions are likely stronger contributors than so far considered. It highlights the need for further research into the roles of microbiomes and direct plant–plant interactions to optimize mixtures' performance.

Plants have powerful defense mechanisms and extensive immune receptor repertoires, yet crop monocultures are prone to epidemic diseases. Rice (Oryza sativa) is susceptible to many diseases, such as rice blast caused by Magnaporthe oryzae. Varietal resistance of rice to blast relies on intracellular nucleotide binding, leucine-rich repeat (NLR) receptors that recognize specific pathogen molecules and trigger immune responses. In the Yuanyang terraces in southwest China, rice landraces rarely show severe losses to disease whereas commercial inbred lines show pronounced field susceptibility. Here, we investigate within-landrace NLR sequence diversity of nine rice landraces and eleven modern varieties using complexity reduction techniques. We find that NLRs display high sequence diversity in landraces, consistent with balancing selection, and that balancing selection at NLRs is more pervasive in landraces than modern varieties. Notably, modern varieties lack many ancient NLR haplotypes that are retained in some landraces. Our study emphasizes the value of standing genetic variation that is maintained in farmer landraces as a resource to make modern crops and agroecosystems less prone to disease. The conservation of landraces is, therefore, crucial for ensuring food security in the face of dynamic biotic and abiotic threats.

The rice blast fungus Magnaporthe oryzae differentiates specialized cells called appressoria that are required for fungal penetration into host leaves. In this study, we identified the novel basic leucine zipper (bZIP) transcription factor BIP1 (B-ZIP Involved in Pathogenesis-1) that is essential for pathogenicity. BIP1 is required for the infection of plant leaves, even if they are wounded, but not for appressorium-mediated penetration of artificial cellophane membranes. This phenotype suggests that BIP1 is not implicated in the differentiation of the penetration peg but is necessary for the initial establishment of the fungus within plant cells. BIP1 expression was restricted to the appressorium by both transcriptional and post-transcriptional control. Genome-wide transcriptome analysis showed that 40 genes were down regulated in a BIP1 deletion mutant. Most of these genes were specifically expressed in the appressorium. They encode proteins with pathogenesis-related functions such as enzymes involved in secondary metabolism including those encoded by the ACE1 gene cluster, small secreted proteins such as SLP2, BAS2, BAS3, and AVR-Pi9 effectors, as well as plant cuticle and cell wall degrading enzymes. Interestingly, this BIP1 network is different from other known infection-related regulatory networks, highlighting the complexity of gene expression control during plant-fungal interactions. Promoters of BIP1-regulated genes shared a GCN4/bZIP-binding DNA motif (TGACTC) binding in vitro to BIP1. Mutation of this motif in the promoter of MGG_08381.7 from the ACE1 gene cluster abolished its appressorium-specific expression, showing that BIP1 behaves as a transcriptional activator. In summary, our findings demonstrate that BIP1 is critical for the expression of early invasion-related genes in appressoria. These genes are likely needed for biotrophic invasion of the first infected host cell, but not for the penetration process itself. Through these mechanisms, the blast fungus strategically anticipates the host plant environment and responses during appressorium-mediated penetration.

Landraces are important resources for breeding programs. However, the diversity harbored at the genomic level by landraces is yet to be analyzed. Here we sequenced more than 200 individual plants from the long-lasting and durably resistant rice landrace Acuce ( Oryza sativa subsp. indica). We found that Acuce exhibits diversity levels as high as 38% of the entire indica sub-species. We pinpoint signatures of selection in favor of polymorphism associated with resistance, but not other agronomic trait genes. Furthermore, we provide evidences that emerging properties upon mixing genomic diversity also increase Acuce’s performances. ### Competing Interest Statement The authors have declared no competing interest.

Plant cytokinins (CKs) affect the outcome of plant-pathogen interactions. However, despite many examples their role remains ambiguous. In rice, CKs act synergistically with salicylic acid (SA) to induce defense genes in vitro but no effect on resistance against the blast fungus, Magnaporthe oryzae, was further observed in planta . Here, we demonstrate that exogenous CKs treatment triggers rice blast resistance in a molecule-, dose- and time-dependent manner by affecting defense- and CK-responsive genes. Similar enhanced resistance and gene expression patterns were confirmed in rice insertion mutant lines impaired for a gene that encodes a putative CK inactivation enzyme, supporting that endogenous CKs affect rice immunity. Together, our work brings insights on the CK-induced resistance of rice to M. oryzae .

Plants interact with each other via a multitude of processes among which belowground communication facilitated by specialized metabolites plays an important but overlooked role. Until now, the exact targets, modes of action, and resulting phenotypes that these metabolites induce in neighboring plants have remained largely unknown. Moreover, positive interactions driven by the release of root exudates are prevalent in both natural field conditions and controlled laboratory environments. In particular, intraspecific positive interactions suggest a genotypic recognition mechanism in addition to non-self perception in plant roots. This review concentrates on recent discoveries regarding how plants interact with one another through belowground signals in intra- and interspecific mixtures. Furthermore, we elaborate on how an enhanced understanding of these interactions can propel the field of agroecology forward.

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.

Identifying the genetic determinants underlying plant-plant interactions is key for understanding plant community dynamics, both in natural and agronomical systems. This report unveils the complex genetic architecture of plant-plant interaction effects on aerial biomass and septoria tritici blotch severity in varietal mixtures of wheat, using co-genome-wide association study. Fifty-four significant allelic interactions between distinct loci were identified, with half involving hub loci. Some inter-individual epistasis might be related to the shade-avoidance syndrome. Our results underscore the critical role of allelic interactions between inter-individual loci in shaping plant phenotypes and community dynamics, offering new perspectives to optimize varietal mixtures.

Traditional agrosystems, where humans, crops and microbes have coevolved over long periods, can serve as models to understand the ecoevolutionary determinants of disease dynamics and help the engineering of durably resistant agrosystems. Here, we investigated the genetic and phenotypic relationship between rice ( Oryza sativa ) landraces and their rice blast pathogen ( Pyricularia oryzae ) in the traditional Yuanyang terraces of flooded rice paddies in China, where rice landraces have been grown and bred over centuries without significant disease outbreaks. Analyses of genetic subdivision revealed that indica rice plants clustered according to landrace names. Three new diverse lineages of rice blast specific to the Yuanyang terraces coexisted with lineages previously detected at the worldwide scale. Population subdivision in the pathogen population did not mirror pattern of population subdivision in the host. Measuring the pathogenicity of rice blast isolates on landraces revealed generalist life history traits. Our results suggest that the implementation of disease control strategies based on the emergence or maintenance of a generalist lifestyle in pathogens may sustainably reduce the burden of disease in crops.

IntroductionRice plays a critical role in human livelihoods and food security. However, its cultivation requires inputs that are not accessible to all farming communities and can have negative effects on ecosystems. simultaneously, ecological research demonstrates that biodiversity management within fields contributes to ecosystem functioning.MethodsThis study aims to evaluate the mixture effect of four functionally distinct rice varieties in terms of characteristics and agronomic performance and their spatial arrangement on the upland rice performance in the highlands of Madagascar. The study was conducted during the 2021-2022 rainfall season at two close sites in Madagascar. Both site differ from each other’s in soil properties and soil fertility management. The experimental design at each site included three modalities: i) plot composition, i.e., pure stand or binary mixture; ii) the balance between the varieties within a mixture; iii) and for the balanced mixture (50% of each variety), the spatial arrangement, i.e., row or checkerboard patterns. Data were collected on yields (grain and biomass), and resistance to Striga asiatica infestation, Pyricularia oryzea and bacterial leaf blight (BLB) caused by Xanthomonas oryzae-pv from each plot.Results and discussionVarietal mixtures produced significantly higher grain and biomass yields, and significantly lower incidence of Pyricularia oryzea compared to pure stands. No significant differences were observed for BLB and striga infestation. These effects were influenced by site fertility, the less fertilized site showed stronger mixture effects with greater gains in grain yield (60%) and biomass yield (42%). The most unbalanced repartition (75% and 25% of each variety) showed the greatest mixture effect for grain yield at both sites, with a strong impact of the varietal identity within the plot. The mixture was most effective when EARLY_MUTANT_IAC_165 constituted 75% of the density associated with other varieties at 25% density. The assessment of the net effect ratio of disease, an index evaluating the mixture effect in disease reduction, indicated improved disease resistance in mixtures, regardless of site conditions. Our study in limited environments suggests that varietal mixtures can enhance rice productivity, especially in low-input situations. Further research is needed to understand the ecological mechanisms behind the positive mixture effect.

Abstract Background Quantitative, accurate, and high-throughput phenotyping of crop diseases is needed for breeding programs and plant-pathogen interaction investigations. However, difficulties in the transferability of available numerical tools encourage maintaining visual assessment of disease symptoms, although this is laborious, time-consuming, requires expertise, and rater dependent. Deep learning has produced interesting results for plant disease evaluation, but has not yet been 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 a Python-coded image analysis script, called SeptoSympto, in which deep learning models based on the U-net and YOLO architectures were used to quantify necrosis and pycnidia, respectively. Small datasets of different sizes (containing 50, 100, 200, and 300 leaves) were trained to create deep learning models and to facilitate the transferability of the tool, and five different datasets were tested to develop a robust tool for the accurate analysis of STB symptoms. The results revealed that (i) the amount of annotated data does not influence the good performance of the models, (ii) the outputs of SeptoSympto are highly correlated with those of the experts, with a similar magnitude to the correlations between experts, and that (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 Although running SeptoSympto takes longer than visual assessment to evaluate STB symptoms, it allows the data to be stored and evaluated by everyone in a more accurate and unbiased manner. Furthermore, the methods used in SeptoSympto were chosen to be not only powerful but also the most frugal, easy to use and adaptable. This study therefore demonstrates the potential of deep learning to assess complex plant disease symptoms such as STB.

Plant ecologists and molecular biologists have long considered the hypothesis of a trade-off between plant growth and defence separately. In particular, how genes thought to control the growth-defence trade-off at the molecular level relate to trait-based frameworks in functional ecology, such as the slow-fast plant economics spectrum, is unknown. We grew 49 phenotypically diverse rice genotypes in pots under optimal conditions and measured growth-related functional traits and the constitutive expression of 11 genes involved in plant defence. We also quantified the concentration of silicon (Si) in leaves to estimate silica-based defences. Rice genotypes were aligned along a slow-fast continuum, with slow-growing, late-flowering genotypes versus fast-growing, early-flowering genotypes. Leaf dry matter content and leaf Si concentrations were not aligned with this axis and negatively correlated with each other. Live-fast genotypes exhibited greater expression of OsNPR1, a regulator of the salicylic acid pathway that promotes plant defence while suppressing plant growth. These genotypes also exhibited greater expression of SPL7 and GH3.2, which are also involved in both stress resistance and growth. Our results do not support the hypothesis of a growth-defence trade-off when leaf Si and leaf dry matter content are considered, but they do when hormonal pathway genes are considered. We demonstrate the benefits of combining ecological and molecular approaches to elucidate the growth-defence trade-off, opening new avenues for plant breeding and crop science.

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.