Rapid identification of an Arabidopsis NLR gene as a candidate conferring susceptibility to Sclerotinia sclerotiorum using time-resolved automated phenotyping

Chemical composition and antifungal activity of the essential oil from the Hymenaea stigonocarpa Mart. Ex Hayne (jatobá-do-cerrado) fruit peel

This study investigated the chemical composition and the antifungal activity of the essential oil extracted from the Hymenaea stigonocarpa fruit peel (HSFPEO) against Botrytis cinerea, Sclerotinia sclerotiorum, Aspergillus flavus and Colletotrichum truncatum. The HSFPEO obtained through hydrodistillation was analyzed with gas chromatography coupled to mass spectrometry. The antifungal activity was determined by the mean mycelial growth inhibition of the fungus treated with essential oils and growth control. The major constituents of HSFPEO were spathulenol (25.19%) and caryophyllene oxide (13.33%). HSFPEO demonstrated antifungal activity against all fungi tested in all concentrations evaluated in a dose-dependent behavior. The best results were observed against B. cinerea and A. flavus, in which the lowest concentration tested inhibited more than 70% of mycelial growth. Based on the current knowledge, this study describes for the first time the chemical composition and the antifungal activity of HSFPEO against the phytopathogenic fungi B. cinerea and C. truncatum.

The complex relationship between disease resistance and yield in crops

In plants, growth and defence are controlled by many molecular pathways that are antagonistic to one another. This results in a 'growth-defence trade-off', where plants temporarily reduce growth in response to pests or diseases. Due to this antagonism, genetic variants that improve resistance often reduce growth and vice versa. Therefore, in natural populations, the most disease resistant individuals are often the slowest growing. In crops, slow growth may translate into a yield penalty, but resistance is essential for protecting yield in the presence of disease. Therefore, plant breeders must balance these traits to ensure optimal yield potential and yield stability. In crops, both qualitative and quantitative disease resistance are often linked with genetic variants that cause yield penalties, but this is not always the case. Furthermore, both crop yield and disease resistance are complex traits influenced by many aspects of the plant's physiology, morphology and environment, and the relationship between the molecular growth-defence trade-off and disease resistance-yield antagonism is not well-understood. In this article, we highlight research from the last 2 years on the molecular mechanistic basis of the antagonism between defence and growth. We then discuss the interaction between disease resistance and crop yield from a breeding perspective, outlining the complexity and nuances of this relationship and where research can aid practical methods for simultaneous improvement of yield potential and disease resistance.

A MAP kinase cascade broadly regulates the lifestyle of Sclerotinia sclerotiorum and can be targeted by HIGS for disease control

Sclerotinia sclerotiorum causes white mold or stem rot in a wide range of economically important plants, bringing significant yield losses worldwide. Control of this pathogen is difficult as its resting structure sclerotia can survive in soil for years, and no Resistance genes have been identified in S. sclerotiorum hosts. Host-induced gene silencing (HIGS) has shown promising effects in controlling many fungal pathogens, including S. sclerotiorum. However, better molecular genetic understanding of signaling pathways involved in its development and pathogenicity is needed to provide effective HIGS gene targets. Here, by employing a forward genetic screen, we characterized an evolutionarily conserved mitogen-activated protein kinase (MAPK) cascade in S. sclerotiorum, consisting of SsSte50-SsSte11-SsSte7-Smk1, which controls mycelial growth, sclerotia development, compound appressoria formation, virulence, and hyphal fusion. Moreover, disruption of the putative downstream transcription factor SsSte12 led to normal sclerotia but deformed appressoria and attenuated host penetration, as well as impaired apothecia formation, suggestive of diverged regulation downstream of the MAPK cascade. Most importantly, targeting SsSte50 using host-expressed double-stranded RNA resulted in largely reduced virulence of S. sclerotiorum on both Nicotiana benthamiana leaves and transgenic Arabidopsis thaliana plants. Therefore, this MAPK signaling cascade is generally needed for its growth, development, and pathogenesis and can serve as ideal HIGS targets for mitigating economic damages caused by S. sclerotiorum infection.

Genome assembly of Medicago truncatula accession SA27063 provides insight into spring black stem and leaf spot disease resistance

Medicago truncatula, model legume and alfalfa relative, has served as an essential resource for advancing our understanding of legume physiology, functional genetics, and crop improvement traits. Necrotrophic fungus, Ascochyta medicaginicola, the causal agent of spring black stem (SBS) and leaf spot is a devasting foliar disease of alfalfa affecting stand survival, yield, and forage quality. Host resistance to SBS disease is poorly understood, and control methods rely on cultural practices. Resistance has been observed in M. truncatula accession SA27063 (HM078) with two recessively inherited quantitative-trait loci (QTL), rnpm1 and rnpm2, previously reported. To shed light on host resistance, we carried out a de novo genome assembly of HM078. The genome, referred to as MtHM078 v1.0, is comprised of 23 contigs totaling 481.19 Mbp. Notably, this assembly contains a substantial amount of novel centromere-related repeat sequences due to deep long-read sequencing. Genome annotation resulted in 98.4% of BUSCO fabales proteins being complete. The assembly enabled sequence-level analysis of rnpm1 and rnpm2 for gene content, synteny, and structural variation between SBS-resistant accession SA27063 (HM078) and SBS-susceptible accession A17 (HM101). Fourteen candidate genes were identified, and some have been implicated in resistance to necrotrophic fungi. Especially interesting candidates include loss-of-function events in HM078 because they fit the inverse gene-for-gene model, where resistance is recessively inherited. In rnpm1, these include a loss-of-function in a disease resistance gene due to a premature stop codon, and a 10.85 kbp retrotransposon-like insertion disrupting a ubiquitin conjugating E2. In rnpm2, we identified a frameshift mutation causing a loss-of-function in a glycosidase, as well as a missense and frameshift mutation altering an F-box family protein. This study generated a high-quality genome of HM078 and has identified promising candidates, that once validated, could be further studied in alfalfa to enhance disease resistance.

An atypical NLR gene confers bacterial wilt susceptibility in Arabidopsis

Quantitative disease resistance (QDR) remains the most prevalent form of plant resistance in crop fields and wild habitats. Genome-wide association studies (GWAS) have proved to be successful in deciphering the quantitative genetic basis of complex traits such as QDR. To unravel the genetics of QDR to the devastating worldwide bacterial pathogen Ralstonia solanacearum, we performed a GWAS by challenging a highly polymorphic local mapping population of Arabidopsis thaliana with four R. solanacearum type III effector (T3E) mutants, identified as key pathogenicity determinants after a first screen on an A. thaliana core collection of 25 accessions. Although most quantitative trait loci (QTLs) were highly specific to the identity of the T3E mutant (ripAC, ripAG, ripAQ, and ripU), we finely mapped a common QTL located on a cluster of nucleotide-binding domain and leucine-rich repeat (NLR) genes that exhibited structural variation. We functionally validated one of these NLRs as a susceptibility factor in response to R. solanacearum, named it Bacterial Wilt Susceptibility 1 (BWS1), and cloned two alleles that conferred contrasting levels of QDR. Further characterization indicated that expression of BWS1 leads to suppression of immunity triggered by different R. solanacearum effectors. In addition, we showed a direct interaction between BWS1 and RipAC T3E, and BWS1 and SUPPRESSOR OF G2 ALLELE OF skp1 (SGT1b), the latter interaction being suppressed by RipAC. Together, our results highlight a putative role for BWS1 as a quantitative susceptibility factor directly targeted by the T3E RipAC, mediating negative regulation of the SGT1-dependent immune response.

The broad host range pathogen Sclerotinia sclerotiorum produces multiple effector proteins that induce host cell death intracellularly

Sclerotinia sclerotiorum is a broad host range necrotrophic fungal pathogen, which causes disease on many economically important crop species. S. sclerotiorum has been shown to secrete small effector proteins to kill host cells and acquire nutrients. We set out to discover novel necrosis-inducing effectors and characterize their activity using transient expression in Nicotiana benthamiana leaves. Five intracellular necrosis-inducing effectors were identified with differing host subcellular localization patterns, which were named intracellular necrosis-inducing effector 1-5 (SsINE1-5). We show for the first time a broad host range pathogen effector, SsINE1, that uses an RxLR-like motif to enter host cells. Furthermore, we provide preliminary evidence that SsINE5 induces necrosis via an NLR protein. All five of the identified effectors are highly conserved in globally sourced S. sclerotiorum isolates. Taken together, these results advance our understanding of the virulence mechanisms employed by S. sclerotiorum and reveal potential avenues for enhancing genetic resistance to this damaging fungal pathogen.

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.

Pathogen-derived mechanical cues potentiate the spatio-temporal implementation of plant defense

BACKGROUND

The ongoing adaptation of plants to their environment is the basis for their survival. In this adaptation, mechanoperception of gravity and local curvature plays a role of prime importance in finely regulating growth and ensuring a dynamic balance preventing buckling. However, the abiotic environment is not the exclusive cause of mechanical stimuli. Biotic interactions between plants and microorganisms also involve physical forces and potentially mechanoperception. Whether pathogens trigger mechanoperception in plants and the impact of mechanotransduction on the regulation of plant defense remains however elusive.

RESULTS

Here, we found that the perception of pathogen-derived mechanical cues by microtubules potentiates the spatio-temporal implementation of plant immunity to fungus. By combining biomechanics modeling and image analysis of the post-invasion stage, we reveal that fungal colonization releases plant cell wall-born tension locally, causing fluctuations of tensile stress in walls of healthy cells distant from the infection site. In healthy cells, the pathogen-derived mechanical cues guide the reorganization of mechanosensing cortical microtubules (CMT). The anisotropic patterning of CMTs is required for the regulation of immunity-related genes in distal cells. The CMT-mediated mechanotransduction of pathogen-derived cues increases Arabidopsis disease resistance by 40% when challenged with the fungus Sclerotinia sclerotiorum.

CONCLUSIONS

CMT anisotropic patterning triggered by pathogen-derived mechanical cues activates the implementation of early plant defense in cells distant from the infection site. We propose that the mechano-signaling triggered immunity (MTI) complements the molecular signals involved in pattern and effector-triggered immunity.

Engineering Resistance against Sclerotinia sclerotiorum Using a Truncated NLR (TNx) and a Defense-Priming Gene

The association of both cell-surface PRRs (Pattern Recognition Receptors) and intracellular receptor NLRs (Nucleotide-Binding Leucine-Rich Repeat) in engineered plants have the potential to activate strong defenses against a broad range of pathogens. Here, we describe the identification, characterization, and in planta functional analysis of a novel truncated NLR (TNx) gene from the wild species Arachis stenosperma (AsTIR19), with a protein structure lacking the C-terminal LRR (Leucine Rich Repeat) domain involved in pathogen perception. Overexpression of AsTIR19 in tobacco plants led to a significant reduction in infection caused by Sclerotinia sclerotiorum, with a further reduction in pyramid lines containing an expansin-like B gene (AdEXLB8) potentially involved in defense priming. Transcription analysis of tobacco transgenic lines revealed induction of hormone defense pathways (SA; JA-ET) and PRs (Pathogenesis-Related proteins) production. The strong upregulation of the respiratory burst oxidase homolog D (RbohD) gene in the pyramid lines suggests its central role in mediating immune responses in plants co-expressing the two transgenes, with reactive oxygen species (ROS) production enhanced by AdEXLB8 cues leading to stronger defense response. Here, we demonstrate that the association of potential priming elicitors and truncated NLRs can produce a synergistic effect on fungal resistance, constituting a promising strategy for improved, non-specific resistance to plant pathogens.

The evolutionary and molecular features of the broad-host-range plant pathogen Sclerotinia sclerotiorum

Sclerotinia sclerotiorum is a pathogenic fungus that infects hundreds of plant species, including many of the world's most important crops. Key features of S. sclerotiorum include its extraordinary host range, preference for dicotyledonous plants, relatively slow evolution, and production of protein effectors that are active in multiple host species. Plant resistance to this pathogen is highly complex, typically involving numerous polymorphisms with infinitesimally small effects, which makes resistance breeding a major challenge. Due to its economic significance, S. sclerotiorum has been subjected to a large amount of molecular and evolutionary research. In this updated pathogen profile, we review the evolutionary and molecular features of S. sclerotiorum and discuss avenues for future research into this important species.

Identification of genetic loci in lettuce mediating quantitative resistance to fungal pathogens

KEY MESSAGE

We demonstrate genetic variation for quantitative resistance against important fungal pathogens in lettuce and its wild relatives, map loci conferring resistance and predict key molecular mechanisms using transcriptome profiling. Lactuca sativa L. (lettuce) is an important leafy vegetable crop grown and consumed globally. Chemicals are routinely used to control major pathogens, including the causal agents of grey mould (Botrytis cinerea) and lettuce drop (Sclerotinia sclerotiorum). With increasing prevalence of pathogen resistance to fungicides and environmental concerns, there is an urgent need to identify sources of genetic resistance to B. cinerea and S. sclerotiorum in lettuce. We demonstrated genetic variation for quantitative resistance to B. cinerea and S. sclerotiorum in a set of 97 diverse lettuce and wild relative accessions, and between the parents of lettuce mapping populations. Transcriptome profiling across multiple lettuce accessions enabled us to identify genes with expression correlated with resistance, predicting the importance of post-transcriptional gene regulation in the lettuce defence response. We identified five genetic loci influencing quantitative resistance in a F6 mapping population derived from a Lactuca serriola (wild relative) × lettuce cross, which each explained 5-10% of the variation. Differential gene expression analysis between the parent lines, and integration of data on correlation of gene expression and resistance in the diversity set, highlighted potential causal genes underlying the quantitative trait loci.

Transcriptome sequencing of Brassica napus highlights the complex issues with soil supplementation with sewage sludge

The soil supplementation with sewage sludge (SS) has become a widespread method to improve soil quality, but its long-term possible consequences are still relatively unknown. SS may contain several groups of contaminants to which the biological responses of the organisms are still poorly understood mainly due to the mixture toxicity. In this context, RNA-seq has been used to assess the impact of the exposure to sewage sludge supplemented soil at the whole-transcriptome level in the Brassica napus (B. napus). Although the municipal sewage sludge passed all safety regulations set by the EU commission (86/278/EEC), soil supplementation with SS caused a significant (p < 0.05) increase in the content of lead (by 68.8%, 71.4% in plant shoots and roots, respectively), zinc (by 22.4% and 31.2%), nickel (by 67.0% and 30.2%), and copper (by 33.1% and 39.2%). The de-novo assembled transcriptome of B. napus identified 555 differently expressed genes (DEGs) in a response to sewage sludge supplementation at the false detection rate below 0.001 (FDR <0.001). Among them, 313 genes were up-regulated and 242 genes were down-regulated. The gene ontology analysis (GO) had shown, that significantly enriched GO groups included genes involved in photosynthesis, carbohydrate metabolism and photosystems repair (41 genes), response to oxidative stress (50 genes), response to pathogens (36 genes), response to xenobiotics (15 genes), and heavy metals (41 genes), cell death (8 genes), cell wall structure (15 genes). These results suggest a significant impact of contaminants in sewage sludge on plants transcriptome. The transcriptomic approach facilitated a better understanding of the molecular level of the potential toxicity of sewage sludge in B. napus. RNA-seq allowed for the identification of potential novel early-warning molecular markers of environmental contamination. This work highlights the crucial necessity for rapid legislation change concerning the allowable levels of contaminants in sewage sludge applied on land, to mitigate the possible adverse outcomes in the ecosystem after its use as a fertilizer.

Sensor-based phenotyping of above-ground plant-pathogen interactions

Plant pathogens cause yield losses in crops worldwide. Breeding for improved disease resistance and management by precision agriculture are two approaches to limit such yield losses. Both rely on detecting and quantifying signs and symptoms of plant disease. To achieve this, the field of plant phenotyping makes use of non-invasive sensor technology. Compared to invasive methods, this can offer improved throughput and allow for repeated measurements on living plants. Abiotic stress responses and yield components have been successfully measured with phenotyping technologies, whereas phenotyping methods for biotic stresses are less developed, despite the relevance of plant disease in crop production. The interactions between plants and pathogens can lead to a variety of signs (when the pathogen itself can be detected) and diverse symptoms (detectable responses of the plant). Here, we review the strengths and weaknesses of a broad range of sensor technologies that are being used for sensing of signs and symptoms on plant shoots, including monochrome, RGB, hyperspectral, fluorescence, chlorophyll fluorescence and thermal sensors, as well as Raman spectroscopy, X-ray computed tomography, and optical coherence tomography. We argue that choosing and combining appropriate sensors for each plant-pathosystem and measuring with sufficient spatial resolution can enable specific and accurate measurements of above-ground signs and symptoms of plant disease.

Transcriptional response to host chemical cues underpins the expansion of host range in a fungal plant pathogen lineage

The host range of parasites is an important factor in assessing the dynamics of disease epidemics. The evolution of pathogens to accommodate new hosts may lead to host range expansion, a process the molecular bases of which are largely enigmatic. The fungus Sclerotinia sclerotiorum has been reported to parasitize more than 400 plant species from diverse eudicot families while its close relative, S. trifoliorum, is restricted to plants from the Fabaceae family. We analyzed S. sclerotiorum global transcriptome reprogramming on hosts from six botanical families and reveal a flexible, host-specific transcriptional program. We generated a chromosome-level genome assembly for S. trifoliorum and found near-complete gene space conservation in two representative strains of broad and narrow host range Sclerotinia species. However, S. trifoliorum showed increased sensitivity to the Brassicaceae defense compound camalexin. Comparative analyses revealed a lack of transcriptional response to camalexin in the S. trifoliorum strain and suggest that regulatory variation in detoxification and effector genes at the population level may associate with the genetic accommodation of Brassicaceae in the Sclerotinia host range. Our work proposes transcriptional plasticity and the co-existence of signatures for generalist and polyspecialist adaptive strategies in the genome of a plant pathogen.

Metatranscriptomic Comparison of Endophytic and Pathogenic Fusarium-Arabidopsis Interactions Reveals Plant Transcriptional Plasticity

Plants are continuously exposed to beneficial and pathogenic microbes, but how plants recognize and respond to friends versus foes remains poorly understood. Here, we compared the molecular response of Arabidopsis thaliana independently challenged with a Fusarium oxysporum endophyte Fo47 versus a pathogen Fo5176. These two F. oxysporum strains share a core genome of about 46 Mb, in addition to 1,229 and 5,415 unique accessory genes. Metatranscriptomic data reveal a shared pattern of expression for most plant genes (about 80%) in responding to both fungal inoculums at all timepoints from 12 to 96 h postinoculation (HPI). However, the distinct responding genes depict transcriptional plasticity, as the pathogenic interaction activates plant stress responses and suppresses functions related to plant growth and development, while the endophytic interaction attenuates host immunity but activates plant nitrogen assimilation. The differences in reprogramming of the plant transcriptome are most obvious in 12 HPI, the earliest timepoint sampled, and are linked to accessory genes in both fungal genomes. Collectively, our results indicate that the A. thaliana and F. oxysporum interaction displays both transcriptome conservation and plasticity in the early stages of infection, providing insights into the fine-tuning of gene regulation underlying plant differential responses to fungal endophytes and pathogens.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Development of a Raspberry Pi-Based Sensor System for Automated In-Field Monitoring to Support Crop Breeding Programs

Sensor applications for plant phenotyping can advance and strengthen crop breeding programs. One of the powerful sensing options is the automated sensor system, which can be customized and applied for plant science research. The system can provide high spatial and temporal resolution data to delineate crop interaction with weather changes in a diverse environment. Such a system can be integrated with the internet to enable the internet of things (IoT)-based sensor system development for real-time crop monitoring and management. In this study, the Raspberry Pi-based sensor (imaging) system was fabricated and integrated with a microclimate sensor to evaluate crop growth in a spring wheat breeding trial for automated phenotyping applications. Such an in-field sensor system will increase the reproducibility of measurements and improve the selection efficiency by investigating dynamic crop responses as well as identifying key growth stages (e.g., heading), assisting in the development of high-performing crop varieties. In the low-cost system developed here-in, a Raspberry Pi computer and multiple cameras (RGB and multispectral) were the main components. The system was programmed to automatically capture and manage the crop image data at user-defined time points throughout the season. The acquired images were suitable for extracting quantifiable plant traits, and the images were automatically processed through a Python script (an open-source programming language) to extract vegetation indices, representing crop growth and overall health. Ongoing efforts are conducted towards integrating the sensor system for real-time data monitoring via the internet that will allow plant breeders to monitor multiple trials for timely crop management and decision making.

Comparative transcriptome profiling identifies maize line specificity of fungal effectors in the maize-Ustilago maydis interaction

The biotrophic pathogen Ustilago maydis causes smut disease on maize (Zea mays) and induces the formation of tumours on all aerial parts of the plant. Unlike in other biotrophic interactions, no gene-for-gene interactions have been identified in the maize-U. maydis pathosystem. Thus, maize resistance to U. maydis is considered a polygenic, quantitative trait. Here, we study the molecular mechanisms of quantitative disease resistance (QDR) in maize, and how U. maydis interferes with its components. Based on quantitative scoring of disease symptoms in 26 maize lines, we performed an RNA sequencing (RNA-Seq) analysis of six U. maydis-infected maize lines of highly distinct resistance levels. The different maize lines showed specific responses of diverse cellular processes to U. maydis infection. For U. maydis, our analysis identified 406 genes being differentially expressed between maize lines, of which 102 encode predicted effector proteins. Based on this analysis, we generated U. maydis CRISPR/Cas9 knock-out mutants for selected candidate effector sets. After infections of different maize lines with the fungal mutants, RNA-Seq analysis identified effectors with quantitative, maize line-specific virulence functions, and revealed auxin-related processes as a possible target for one of them. Thus, we show that both transcriptional activity and virulence function of fungal effector genes are modified according to the infected maize line, providing insights into the molecular mechanisms underlying QDR in the maize-U. maydis interaction.

Tackling microbial threats in agriculture with integrative imaging and computational approaches

Pathogens and pests are one of the major threats to agricultural productivity worldwide. For decades, targeted resistance breeding was used to create crop cultivars that resist pathogens and environmental stress while retaining yields. The often decade-long process of crossing, selection, and field trials to create a new cultivar is challenged by the rapid rise of pathogens overcoming resistance. Similarly, antimicrobial compounds can rapidly lose efficacy due to resistance evolution. Here, we review three major areas where computational, imaging and experimental approaches are revolutionizing the management of pathogen damage on crops. Recognizing and scoring plant diseases have dramatically improved through high-throughput imaging techniques applicable both under well-controlled greenhouse conditions and directly in the field. However, computer vision of complex disease phenotypes will require significant improvements. In parallel, experimental setups similar to high-throughput drug discovery screens make it possible to screen thousands of pathogen strains for variation in resistance and other relevant phenotypic traits. Confocal microscopy and fluorescence can capture rich phenotypic information across pathogen genotypes. Through genome-wide association mapping approaches, phenotypic data helps to unravel the genetic architecture of stress- and virulence-related traits accelerating resistance breeding. Finally, joint, large-scale screenings of trait variation in crops and pathogens can yield fundamental insights into how pathogens face trade-offs in the adaptation to resistant crop varieties. We discuss how future implementations of such innovative approaches in breeding and pathogen screening can lead to more durable disease control.

Robustness of plant quantitative disease resistance is provided by a decentralized immune network

Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to XcampestrisRKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in Athaliana Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.

Phylotranscriptomics of the Pentapetalae Reveals Frequent Regulatory Variation in Plant Local Responses to the Fungal Pathogen Sclerotinia sclerotiorum

Quantitative disease resistance (QDR) is a conserved form of plant immunity that limits infections caused by a broad range of pathogens. QDR has a complex genetic determinism. The extent to which molecular components of the QDR response vary across plant species remains elusive. The fungal pathogen Sclerotinia sclerotiorum, causal agent of white mold diseases on hundreds of plant species, triggers QDR in host populations. To document the diversity of local responses to S. sclerotiorum at the molecular level, we analyzed the complete transcriptomes of six species spanning the Pentapetalae (Phaseolus vulgaris, Ricinus communis, Arabidopsis [Arabidopsis thaliana], Helianthus annuus, Solanum lycopersicum, and Beta vulgaris) inoculated with the same strain of S. sclerotiorum About one-third of plant transcriptomes responded locally to S. sclerotiorum, including a high proportion of broadly conserved genes showing frequent regulatory divergence at the interspecific level. Evolutionary inferences suggested a trend toward the acquisition of gene induction relatively recently in several lineages. Focusing on a group of ABCG transporters, we propose that exaptation by regulatory divergence contributed to the evolution of QDR. This evolutionary scenario has implications for understanding the QDR spectrum and durability. Our work provides resources for functional studies of gene regulation and QDR molecular mechanisms across the Pentapetalae.