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

Genome-Wide Association Study Reveals Polygenic Architecture for Limber Pine Quantitative Disease Resistance to White Pine Blister Rust

Development of durable resistance effective against a broad range of pathotypes is crucial for restoration of pathogen-damaged ecosystems. This study dissected the complex genetic architecture for limber pine quantitative disease resistance (QDR) to Cronartium ribicola using a genome-wide association study. Eighteen-month-old seedlings were inoculated for resistance screening under controlled conditions. Disease development was quantitatively assessed for QDR-related traits over 4 years postinoculation. To reveal the genomic architecture contributing to QDR-related traits, a set of genes related to disease resistance with genome-wide distribution was selected for targeted sequencing for genotyping of single-nucleotide polymorphisms (SNPs). The genome-wide association study revealed a set of SNPs significantly associated with quantitative traits for limber pine QDR to white pine blister rust, including number of needle spots and stem cankers, as well as survival 4 years postinoculation. The peaks of marker-trait associations displayed a polygenic pattern, with genomic regions as potential resistant quantitative trait loci, distributed over 10 of the 12 linkage groups (LGs) of Pinus. None of them was linked to the Cr4-controlled major gene resistance previously mapped on LG08. Both normal canker and bole infection were mapped on LG05, and the associated SNPs explained their phenotypic variance up to 52%, tagging a major resistant quantitative trait locus. Candidate genes containing phenotypically associated SNPs encoded putative nucleotide-binding site leucine-rich repeat proteins, leucine-rich repeat-receptor-like kinase, cytochrome P450 superfamily protein, heat shock cognate protein 70, glutamate receptor, RNA-binding family protein, and unknown protein. The confirmation of resistant quantitative trait loci broadens the genetic pool of limber pine resistance germplasm for resistance breeding.

Molecular complexity of quantitative immunity in plants: from QTL mapping to functional and systems biology

In nature, plants defend themselves against pathogen attack by activating an arsenal of defense mechanisms. During the last decades, work mainly focused on the understanding of qualitative disease resistance mediated by a few genes conferring an almost complete resistance, while quantitative disease resistance (QDR) remains poorly understood despite the fact that it represents the predominant and more durable form of resistance in natural populations and crops. Here, we review our past and present work on the dissection of the complex mechanisms underlying QDR in Arabidopsis thaliana. The strategies, main steps and challenges of our studies related to one atypical QDR gene, RKS1 (Resistance related KinaSe 1), are presented. First, from genetic analyses by QTL (Quantitative Trait Locus) mapping and GWAs (Genome Wide Association studies), the identification, cloning and functional analysis of this gene have been used as a starting point for the exploration of the multiple and coordinated pathways acting together to mount the QDR response dependent on RKS1. Identification of RKS1 protein interactors and complexes was a first step, systems biology and reconstruction of protein networks were then used to decipher the molecular roadmap to the immune responses controlled by RKS1. Finally, exploration of the potential impact of key components of the RKS1-dependent gene network on leaf microbiota offers interesting and challenging perspectives to decipher how the plant immune systems interact with the microbial communities' systems.

The Role of Salicylic Acid in the Expression of RECEPTOR-LIKE PROTEIN 23 and Other Immunity-Related Genes

The hormone salicylic acid (SA) plays a crucial role in plant immunity by activating responses that arrest pathogen ingress. SA accumulation also penalizes growth, a phenomenon visible in mutants that hyperaccumulate SA, resulting in strong growth inhibition. An important question, therefore, is why healthy plants produce basal levels of this hormone when defense responses are not activated. Here, we show that basal SA levels in unchallenged plants are needed for the expression of a number of immunity-related genes and receptors, such as RECEPTOR-LIKE PROTEIN 23 (RLP23). This was shown by depleting basal SA levels in transgenic Arabidopsis lines through the overexpression of the SA-inactivating hydroxylases DOWNY MILDEW-RESISTANT 6 (DMR6) or DMR6-LIKE OXYGENASE 1. RNAseq analysis revealed that the expression of a subset of immune receptor and signaling genes is strongly reduced in the absence of SA. The biological relevance of this was shown for RLP23: In SA-depleted and SA-insensitive plants, responses to the RLP23 ligand, the microbial pattern nlp24, were strongly reduced, whereas responses to flg22 remained unchanged. We hypothesize that low basal SA levels are needed for the expression of a subset of immune system components that enable early pathogen detection and activation of immunity.

Quantitative disease resistance in wild Silene vulgaris to its endemic pathogen Microbotryum silenes-inflatae

The evolution of disease resistances is an expected feature of plant-pathogen systems, but whether the genetics of this trait most often produces qualitative or quantitative phenotypic variation is a significant gap in our understanding of natural populations. These two forms of resistance variation are often associated with differences in number of underlying loci, the specificities of host-pathogen coevolution, as well as contrasting mechanisms of preventing or slowing the infection process. Anther-smut disease is a commonly studied model for disease of wild species, where infection has severe fitness impacts, and prior studies have suggested resistance variation in several host species. However, because the outcome of exposing the individual host to this pathogen is binary (healthy or diseased), resistance has been previously measured at the family level, as the proportion of siblings that become diseased. This leaves uncertain whether among-family variation reflects contrasting ratios of segregating discrete phenotypes or continuous trait variation among individuals. In the host Silene vulgaris, plants were replicated by vegetative propagation in order to quantify the infection rates of the individual genotype with the endemic anther-smut pathogen, Microbotryum silenes-inflatae. The variance among field-collected families for disease resistance was significant, while there was unimodal continuous variation in resistance among genotypes. Using crosses between genotypes within ranked resistance quartiles, the offspring infection rate was predicted by the parental resistance values. While the potential remains in this system for resistance genes having major effects, as there were suggestions of such qualitative resistance in a prior study, here the quantitative disease resistance to the endemic anther-smut pathogen is indicated for S. vulgaris. The variation in natural populations and strong heritability of the trait, combined with severe fitness consequences of anther-smut disease, suggests that resistance in these host populations is highly capable of responding to disease-induced selection.

Genome scans capture key adaptation and historical hybridization signatures in tetraploid wheat

Tetraploid wheats (Triticum turgidum L.), including durum wheat (T. turgidum ssp. durum (Desf.) Husn.), are important crops with high nutritional and cultural values. However, their production is constrained by sensitivity to environmental conditions. In search of adaptive genetic signatures tracing historical selection and hybridization events, we performed genome scans on two datasets: (1) Durum Global Diversity Panel comprising a total of 442 tetraploid wheat and wild progenitor accessions including durum landraces (n = 286), domesticated emmer (T. turgidum ssp. dicoccum (Schrank) Thell.; n = 103) and wild emmer (T. turgidum ssp. dicoccoides (Korn. ex Asch. & Graebn.) Thell.; n = 53) wheats genotyped using the 90K single nucleotide polymorphism (SNP) array, and (2) a second dataset comprising a total 121 accessions of nine T. turgidum subspecies including wild emmer genotyped with >100 M SNPs from whole-genome resequencing. The genome scan on the first dataset detected six outlier loci on chromosomes 1A, 1B, 3A (n = 2), 6A, and 7A. These loci harbored important genes for adaptation to abiotic stresses, phenological responses, such as seed dormancy, circadian clock, flowering time, and key yield-related traits, including pleiotropic genes, such as HAT1, KUODA1, CBL1, and ZFN1. The scan on the second dataset captured a highly differentiated region on chromosome 2B that shows significant differentiation between two groups: one group consists of Georgian (T. turgidum ssp. paleocolchicum A. Love & D. Love) and Persian (T. turgidum ssp. carthlicum (Nevski) A. Love & D. Love) wheat accessions, while the other group comprises all the remaining tetraploids including wild emmer. This is consistent with a previously reported introgression in this genomic region from T. timopheevii Zhuk. which naturally cohabit in the Georgian and neighboring areas. This region harbored several adaptive genes, including the thermomorphogenesis gene PIF4, which confers temperature-resilient disease resistance and regulates other biological processes. Genome scans can be used to fast-track germplasm housed in gene banks and in situ; which helps to identify environmentally resilient accessions for breeding and/or to prioritize them for conservation.

Tomato deploys defence and growth simultaneously to resist bacterial wilt disease

Plant disease limits crop production, and host genetic resistance is a major means of control. Plant pathogenic Ralstonia causes bacterial wilt disease and is best controlled with resistant varieties. Tomato wilt resistance is multigenic, yet the mechanisms of resistance remain largely unknown. We combined metaRNAseq analysis and functional experiments to identify core Ralstonia-responsive genes and the corresponding biological mechanisms in wilt-resistant and wilt-susceptible tomatoes. While trade-offs between growth and defence are common in plants, wilt-resistant plants activated both defence responses and growth processes. Measurements of innate immunity and growth, including reactive oxygen species production and root system growth, respectively, validated that resistant plants executed defence-related processes at the same time they increased root growth. In contrast, in wilt-susceptible plants roots senesced and root surface area declined following Ralstonia inoculation. Wilt-resistant plants repressed genes predicted to negatively regulate water stress tolerance, while susceptible plants repressed genes predicted to promote water stress tolerance. Our results suggest that wilt-resistant plants can simultaneously promote growth and defence by investing in resources that act in both processes. Infected susceptible plants activate defences, but fail to grow and so succumb to Ralstonia, likely because they cannot tolerate the water stress induced by vascular wilt.

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.

Plant and pathogen genomics: essential approaches for stem rust resistance gene stacks in wheat

The deployment of disease resistance genes is currently the most economical and environmentally sustainable method of crop protection. However, disease resistance genes can rapidly break down because of constant pathogen evolution, particularly when they are deployed singularly. Polygenic resistance is, therefore, considered the most durable, but combining and maintaining these genes by breeding is a laborious process as effective genes are usually unlinked. The deployment of polygenic resistance with single-locus inheritance is a promising innovation that overcomes these difficulties while enhancing resistance durability. Because of major advances in genomic technologies, increasing numbers of plant resistance genes have been cloned, enabling the development of resistance transgene stacks (RTGSs) that encode multiple genes all located at a single genetic locus. Gene stacks encoding five stem rust resistance genes have now been developed in transgenic wheat and offer both breeding simplicity and potential resistance durability. The development of similar genomic resources in phytopathogens has advanced effector gene isolation and, in some instances, enabled functional validation of individual resistance genes in RTGS. Here, the wheat stem rust pathosystem is used as an illustrative example of how host and pathogen genomic advances have been instrumental in the development of RTGS, which is a strategy applicable to many other agricultural crop species.

Tobamovirus infection aggravates gray mold disease caused by Botrytis cinerea by manipulating the salicylic acid pathway in tomato

Botrytis cinerea is the causative agent of gray mold disease, and infects more than 1400 plant species, including important crop plants. In tomato, B. cinerea causes severe damage in greenhouses and post-harvest storage and transport. Plant viruses of the Tobamovirus genus cause significant damage to various crop species. In recent years, the tobamovirus tomato brown rugose fruit virus (ToBRFV) has significantly affected the global tomato industry. Most studies of plant-microbe interactions focus on the interaction between the plant host and a single pathogen, however, in agricultural or natural environments, plants are routinely exposed to multiple pathogens. Here, we examined how preceding tobamovirus infection affects the response of tomato to subsequent infection by B. cinerea. We found that infection with the tobamoviruses tomato mosaic virus (ToMV) or ToBRFV resulted in increased susceptibility to B. cinerea. Analysis of the immune response of tobamovirus-infected plants revealed hyper-accumulation of endogenous salicylic acid (SA), upregulation of SA-responsive transcripts, and activation of SA-mediated immunity. Deficiency in SA biosynthesis decreased tobamovirus-mediated susceptibility to B. cinerea, while exogenous application of SA enhanced B. cinerea symptoms. These results suggest that tobamovirus-mediated accumulation of SA increases the plants' susceptibility to B. cinerea, and provide evidence for a new risk caused by tobamovirus infection in agriculture.

Genome-wide association studies in plant pathosystems: success or failure?

Harnessing natural genetic variation is an established alternative to artificial genetic variation for investigating the molecular dialog between partners in plant pathosystems. Herein, we review the successes of genome-wide association studies (GWAS) in both plants and pathogens. While GWAS in plants confirmed that the genetic architecture of disease resistance is polygenic, dynamic during the infection kinetics, and dependent on the environment, GWAS shortened the time of identification of quantitative trait loci (QTLs) and revealed both complex epistatic networks and a genetic architecture dependent upon the geographical scale. A similar picture emerges from the few GWAS in pathogens. In addition, the ever-increasing number of functionally validated QTLs has revealed new molecular plant defense mechanisms and pathogenicity determinants. Finally, we propose recommendations to better decode the disease triangle.

Novel gene loci associated with susceptibility or cryptic quantitative resistance to Pyrenopeziza brassicae in Brassica napus

Quantitative disease resistance (QDR) controls the association of the light leaf spot pathogen with Brassica napus; four QDR loci that were in linkage disequilibrium and eight gene expression markers were identified. Quantitative disease resistance (QDR) can provide durable control of pathogens in crops in contrast to resistance (R) gene-mediated resistance which can break down due to pathogen evolution. QDR is therefore a desirable trait in crop improvement, but little is known about the causative genes, and so it is difficult to incorporate into breeding programmes. Light leaf spot, caused by Pyrenopeziza brassicae, is an important disease of oilseed rape (canola, Brassica napus). To identify new QDR gene loci, we used a high-throughput screening pathosystem with P. brassicae on 195 lines of B. napus combined with an association transcriptomics platform. We show that all resistance against P. brassicae was associated with QDR and not R gene-mediated. We used genome-wide association analysis with an improved B. napus population structure to reveal four gene loci significantly (P = 0.0001) associated with QDR in regions showing linkage disequilibrium. On chromosome A09, enhanced resistance was associated with heterozygosity for a cytochrome P450 gene co-localising with a previously described locus for seed glucosinolate content. In addition, eight significant gene expression markers with a false discovery rate of 0.001 were associated with QDR against P. brassicae. For seven of these, expression was positively correlated with resistance, whereas for one, a HXXXD-type acyl-transferase, negative correlation indicated a potential susceptibility gene. The study identifies novel QDR loci for susceptibility and resistance, including novel cryptic QDR genes associated with heterozygosity, that will inform future crop improvement.

Hydathode immunity protects the Arabidopsis leaf vasculature against colonization by bacterial pathogens

Plants prevent disease by passively and actively protecting potential entry routes against invading microbes. For example, the plant immune system actively guards roots, wounds, and stomata. How plants prevent vascular disease upon bacterial entry via guttation fluids excreted from specialized glands at the leaf margin remains largely unknown. These so-called hydathodes release xylem sap when root pressure is too high. By studying hydathode colonization by both hydathode-adapted (Xanthomonas campestris pv. campestris) and non-adapted pathogenic bacteria (Pseudomonas syringae pv. tomato) in immunocompromised Arabidopsis mutants, we show that the immune hubs BAK1 and EDS1-PAD4-ADR1 restrict bacterial multiplication in hydathodes. Both immune hubs effectively confine bacterial pathogens to hydathodes and lower the number of successful escape events of an hydathode-adapted pathogen toward the xylem. A second layer of defense, which is dependent on the plant hormones' pipecolic acid and to a lesser extent on salicylic acid, reduces the vascular spread of the pathogen. Thus, besides glands, hydathodes represent a potent first line of defense against leaf-invading microbes.

The LeEIX Locus Determines Pathogen Resistance in Tomato

The mechanisms underlying the ability of plants to differentiate between pathogens and commensals in their environment are currently unresolved. It has been suggested that spatiotemporal regulation of pattern-recognition receptor (PRR) content could be one of the components providing plants with the ability to distinguish between pathogens and nonpathogenic microbes. The LeEIX PRRs recognize xylanases derived from beneficial or commensal plant colonizers of Trichoderma species, including the xylanase known as EIX. Here, we investigated possible general roles of PRRs from the LeEIX locus in immunity and pathogen resistance in tomato. Mutating the inhibitory PRR LeEIX1, or overexpressing the activating PRR LeEIX2, resulted in resistance to a wide range of pathogens and increased basal and elicited immunity. LeEIX1 knockout caused increases in the expression level of several tested PRRs, including FLS2, as well as bacterial pathogen resistance coupled with an increase in flg22-mediated immunity. The wild tomato relative Solanum pennellii contains inactive LeEIX PRR variants. S. pennellii does not respond to elicitation with the LeEIX PRR ligand EIX. Given that EIX is derived from a mostly nonpathogenic microbe, the connection of its PRRs to disease resistance has not previously been investigated directly. Here, we observed that compared with S. lycopersicum cultivar M82, S. pennellii was more sensitive to several fungal and bacterial pathogens. Our results suggest that the LeEIX locus might determine resistance to fungal necrotrophs, whereas the resistance to biotrophs is effected in combination with a gene/quantitative trait locus not within the LeEIX locus.

The ecologically relevant genetics of plant-plant interactions

Interactions among plants have been long recognized as a major force driving plant community dynamics and crop yield. Surprisingly, our knowledge of the ecological genetics associated with variation of plant-plant interactions remains limited. In this opinion article by scientists from complementary disciplines, the international PLANTCOM network identified four timely questions to foster a better understanding of the mechanisms mediating plant assemblages. We propose that by identifying the key relationships among phenotypic traits involved in plant-plant interactions and the underlying adaptive genetic and molecular pathways, while considering environmental fluctuations at diverse spatial and time scales, we can improve predictions of genotype-by-genotype-by-environment interactions and modeling of productive and stable plant assemblages in wild habitats and crop fields.

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.

A Genome-Wide Association study in Arabidopsis thaliana to decipher the adaptive genetics of quantitative disease resistance in a native heterogeneous environment

Pathogens are often the main selective agents acting in plant communities, thereby influencing the distribution of polymorphism at loci affecting resistance within and among natural plant populations. In addition, the outcome of plant-pathogen interactions can be drastically affected by abiotic and biotic factors at different spatial and temporal grains. The characterization of the adaptive genetic architecture of disease resistance in native heterogeneous environments is however still missing. In this study, we conducted an in situ Genome-Wide Association study in the spatially heterogeneous native habitat of a highly genetically polymorphic local mapping population of Arabidopsis thaliana, to unravel the adaptive genetic architecture of quantitative disease resistance. Disease resistance largely differed among three native soils and was affected by the presence of the grass Poa annua. The observation of strong crossing reactions norms among the 195 A. thaliana genotypes for disease resistance among micro-habitats, combined with a negative fecundity-disease resistance relationship in each micro-habitat, suggest that alternative local genotypes of A. thaliana are favored under contrasting environmental conditions at the scale of few meters. A complex genetic architecture was detected for disease resistance and fecundity. However, only few QTLs were common between these two traits. Heterogeneous selection in this local population should therefore promote the maintenance of polymorphism at only few candidate resistance genes.

Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat

This study performed comprehensive analyses on the predictive abilities of single-trait and two multi-trait models in three populations. Our results demonstrated the superiority of multi-traits over single-trait models across seven agronomic and four to seven disease resistance traits of different genetic architecture. The predictive ability of multi-trait and single-trait prediction models has not been investigated on diverse traits evaluated under organic and conventional management systems. Here, we compared the predictive abilities of 25% of a testing set that has not been evaluated for a single trait (ST), not evaluated for multi-traits (MT1), and evaluated for some traits but not others (MT2) in three spring wheat populations genotyped either with the wheat 90K single nucleotide polymorphisms array or DArTseq. Analyses were performed on seven agronomic traits evaluated under conventional and organic management systems, four to seven disease resistance traits, and all agronomic and disease resistance traits simultaneously. The average prediction accuracies of the ST, MT1, and MT2 models varied from 0.03 to 0.78 (mean 0.41), from 0.05 to 0.82 (mean 0.47), and from 0.05 to 0.92 (mean 0.67), respectively. The predictive ability of the MT2 model was significantly greater than the ST model in all traits and populations except common bunt with the MT1 model being intermediate between them. The MT2 model increased prediction accuracies over the ST and MT1 models in all traits by 9.0-82.4% (mean 37.3%) and 2.9-82.5% (mean 25.7%), respectively, except common bunt that showed up to 7.7% smaller accuracies in two populations. A joint analysis of all agronomic and disease resistance traits further improved accuracies within the MT1 and MT2 models on average by 21.4% and 17.4%, respectively, as compared to either the agronomic or disease resistance traits, demonstrating the high potential of the multi-traits models in improving prediction accuracies.

Genomic Predictions for Common Bunt, FHB, Stripe Rust, Leaf Rust, and Leaf Spotting Resistance in Spring Wheat

Some studies have investigated the potential of genomic selection (GS) on stripe rust, leaf rust, Fusarium head blight (FHB), and leaf spot in wheat, but none of them have assessed the effect of the reaction norm model that incorporated GE interactions. In addition, the prediction accuracy on common bunt has not previously been studied. Here, we investigated within-population prediction accuracies using the baseline M1 model and two reaction norm models (M2 and M3) with three random cross-validation (CV1, CV2, and CV0) schemes. Three Canadian spring wheat populations were evaluated in up to eight field environments and genotyped with 3158, 5732, and 23,795 polymorphic markers. The M3 model that incorporated GE interactions reduced residual variance by an average of 10.2% as compared with the main effect M2 model and increased prediction accuracies on average by 2-6%. In some traits, the M3 model increased prediction accuracies up to 54% as compared with the M2 model. The average prediction accuracies of the M3 model with CV1, CV2, and CV0 schemes varied from 0.02 to 0.48, from 0.25 to 0.84, and from 0.14 to 0.87, respectively. In both CV2 and CV0 schemes, stripe rust in all three populations, common bunt and leaf rust in two populations, as well as FHB severity, FHB index, and leaf spot in one population had high to very high (0.54-0.87) prediction accuracies. This is the first comprehensive genomic selection study on five major diseases in spring wheat.

Genomic prediction of strawberry resistance to postharvest fruit decay caused by the fungal pathogen Botrytis cinerea

Gray mold, a disease of strawberry (Fragaria × ananassa) caused by the ubiquitous necrotroph Botrytis cinerea, renders fruit unmarketable and causes economic losses in the postharvest supply chain. To explore the feasibility of selecting for increased resistance to gray mold, we undertook genetic and genomic prediction studies in strawberry populations segregating for fruit quality and shelf life traits hypothesized to pleiotropically affect susceptibility. As predicted, resistance to gray mold was heritable but quantitative and genetically complex. While every individual was susceptible, the speed of symptom progression and severity differed. Narrow-sense heritability ranged from 0.38 to 0.71 for lesion diameter (LD) and 0.39 to 0.44 for speed of emergence of external mycelium (EM). Even though significant additive genetic variation was observed for LD and EM, the phenotypic ranges were comparatively narrow and genome-wide analyses did not identify any large-effect loci. Genomic selection (GS) accuracy ranged from 0.28 to 0.59 for LD and 0.37 to 0.47 for EM. Additive genetic correlations between fruit quality and gray mold resistance traits were consistent with prevailing hypotheses: LD decreased as titratable acidity increased, whereas EM increased as soluble solid content decreased and firmness increased. We concluded that phenotypic and GS could be effective for reducing LD and increasing EM, especially in long shelf life populations, but that a significant fraction of the genetic variation for resistance to gray mold was caused by the pleiotropic effects of fruit quality traits that differ among market and shelf life classes.

Network organization of the plant immune system: from pathogen perception to robust defense induction

The plant immune system has been explored essentially through the study of qualitative resistance, a simple form of immunity, and from a reductionist point of view. The recent identification of genes conferring quantitative disease resistance revealed a large array of functions, suggesting more complex mechanisms. In addition, thanks to the advent of high-throughput analyses and system approaches, our view of the immune system has become more integrative, revealing that plant immunity should rather be seen as a distributed and highly connected molecular network including diverse functions to optimize expression of plant defenses to pathogens. Here, we review the recent progress made to understand the network complexity of regulatory pathways leading to plant immunity, from pathogen perception, through signaling pathways and finally to immune responses. We also analyze the topological organization of these networks and their emergent properties, crucial to predict novel immune functions and test them experimentally. Finally, we report how these networks might be regulated by environmental clues. Although system approaches remain extremely scarce in this area of research, a growing body of evidence indicates that the plant response to combined biotic and abiotic stresses cannot be inferred from responses to individual stresses. A view of possible research avenues in this nascent biology domain is finally proposed.

Dissection of Quantitative Blackleg Resistance Reveals Novel Variants of Resistance Gene Rlm9 in Elite Brassica napus

Blackleg is one of the major fungal diseases in oilseed rape/canola worldwide. Most commercial cultivars carry R gene-mediated qualitative resistances that confer a high level of race-specific protection against Leptosphaeria maculans, the causal fungus of blackleg disease. However, monogenic resistances of this kind can potentially be rapidly overcome by mutations in the pathogen's avirulence genes. To counteract pathogen adaptation in this evolutionary arms race, there is a tremendous demand for quantitative background resistance to enhance durability and efficacy of blackleg resistance in oilseed rape. In this study, we characterized genomic regions contributing to quantitative L. maculans resistance by genome-wide association studies in a multiparental mapping population derived from six parental elite varieties exhibiting quantitative resistance, which were all crossed to one common susceptible parental elite variety. Resistance was screened using a fungal isolate with no corresponding avirulence (AvrLm) to major R genes present in the parents of the mapping population. Genome-wide association studies revealed eight significantly associated quantitative trait loci (QTL) on chromosomes A07 and A09, with small effects explaining 3-6% of the phenotypic variance. Unexpectedly, the qualitative blackleg resistance gene Rlm9 was found to be located within a resistance-associated haploblock on chromosome A07. Furthermore, long-range sequence data spanning this haploblock revealed high levels of single-nucleotide and structural variants within the Rlm9 coding sequence among the parents of the mapping population. The results suggest that novel variants of Rlm9 could play a previously unknown role in expression of quantitative disease resistance in oilseed rape.

Advances in functional proteomics to study plant-pathogen interactions

Pathogen infection triggers complex signaling networks in plant cells that ultimately result in either susceptibility or resistance. We have made substantial progress in dissecting many of these signaling events, and it is becoming clear that changes in proteome composition and protein activity are major drivers of plant-microbe interactions. Here, we highlight different approaches to analyze the functional proteomes of hosts and pathogens and discuss how they have been used to further our understanding of plant disease. Global proteome profiling can quantify the dynamics of proteins, posttranslational modifications, and biological pathways that contribute to immune-related outcomes. In addition, emerging techniques such as enzyme activity-based profiling, proximity labeling, and kinase-substrate profiling are being used to dissect biochemical events that operate during infection. Finally, we discuss how these functional approaches can be integrated with other profiling data to gain a mechanistic, systems-level view of plant and pathogen signaling.

The Same against Many: AtCML8, a Ca2+ Sensor Acting as a Positive Regulator of Defense Responses against Several Plant Pathogens

Calcium signals are crucial for the activation and coordination of signaling cascades leading to the establishment of plant defense mechanisms. Here, we studied the contribution of CML8, an Arabidopsis calmodulin-like protein in response to Ralstonia solanacearum and to pathogens with different lifestyles, such as Xanthomonas campestris pv. campestris and Phytophtora capsici. We used pathogenic infection assays, gene expression, RNA-seq approaches, and comparative analysis of public data on CML8 knockdown and overexpressing Arabidopsis lines to demonstrate that CML8 contributes to defense mechanisms against pathogenic bacteria and oomycetes. CML8 gene expression is finely regulated at the root level and manipulated during infection with Ralstonia, and CML8 overexpression confers better plant tolerance. To understand the processes controlled by CML8, genes differentially expressed at the root level in the first hours of infection have been identified. Overexpression of CML8 also confers better tolerance against Xanthomonas and Phytophtora, and most of the genes differentially expressed in response to Ralstonia are differentially expressed in these different pathosystems. Collectively, CML8 acts as a positive regulator against Ralstonia solanaceraum and against other vascular or root pathogens, suggesting that CML8 is a multifunctional protein that regulates common downstream processes involved in the defense response of plants to several pathogens.

Arabidopsis-Based Dual-Layered Biological Network Analysis Elucidates Fully Modulated Pathways Related to Sugarcane Resistance on Biotrophic Pathogen Infection

We assembled a dual-layered biological network to study the roles of resistance gene analogs (RGAs) in the resistance of sugarcane to infection by the biotrophic fungus causing smut disease. Based on sugarcane-Arabidopsis orthology, the modeling used metabolic and protein-protein interaction (PPI) data from Arabidopsis thaliana (from Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioGRID databases) and plant resistance curated knowledge for Viridiplantae obtained through text mining of the UniProt/SwissProt database. With the network, we integrated functional annotations and transcriptome data from two sugarcane genotypes that differ significantly in resistance to smut and applied a series of analyses to compare the transcriptomes and understand both signal perception and transduction in plant resistance. We show that the smut-resistant sugarcane has a larger arsenal of RGAs encompassing transcriptionally modulated subnetworks with other resistance elements, reaching hub proteins of primary metabolism. This approach may benefit molecular breeders in search of markers associated with quantitative resistance to diseases in non-model systems.

Quantitative interactions: the disease outcome of Botrytis cinerea across the plant kingdom

Botrytis cinerea is a fungal pathogen that causes necrotic disease on more than a thousand known hosts widely spread across the plant kingdom. How B. cinerea interacts with such extensive host diversity remains largely unknown. To address this question, we generated an infectivity matrix of 98 strains of B. cinerea on 90 genotypes representing eight host plants. This experimental infectivity matrix revealed that the disease outcome is largely explained by variations in either the host resistance or pathogen virulence. However, the specific interactions between host and pathogen account for 16% of the disease outcome. Furthermore, the disease outcomes cluster among genotypes of a species but are independent of the relatedness between hosts. When analyzing the host specificity and virulence of B. cinerea, generalist strains are predominant. In this fungal necrotroph, specialization may happen by a loss in virulence on most hosts rather than an increase of virulence on a specific host. To uncover the genetic architecture of Botrytis host specificity and virulence, a genome-wide association study (GWAS) was performed and revealed up to 1492 genes of interest. The genetic architecture of these traits is widespread across the B. cinerea genome. The complexity of the disease outcome might be explained by hundreds of functionally diverse genes putatively involved in adjusting the infection to diverse hosts.

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.

Comparison with Arabidopsis reveals optimal nitrogen allocation strategy and mechanism in Chorispora bungeana, a cryophyte with strong freezing tolerance

The stress responses of plant compete for resources with growth and development. Resource allocations among these processes may have been optimized in plants adapted to natural habitats. Here, nitrogen (N) allocations were compared in leaves of Arabidopsis and Chorispora bungeana, a cryophyte with strong freezing tolerance. The results showed that the two species differed not only in N partitions among N forms and allocations among leaves, but also in their responses to cold stress. Interestingly, leaf protein contents were enhanced in C. bungeana while reduced in Arabidopsis, though the N allocations to leaves were reduced in both plants upon cold stress. Profoundly, when grown at warm temperature, contents of total free amino acids (FAAs) in leaves of C. bungeana were 6-11 times higher than those in Arabidopsis. In contrast, cold treatment induced FAAs accumulation in leaves of Arabidopsis without having significant effect in any leaf of C. bungeana. Considerable discrepancy was also found between the two species in the expressions of nitrate transporter genes and the activities of nitrate assimilation enzymes. Correlation and network analysis showed that most NPFs were clustered in a single network module and had loose relations with protein synthesis in Arabidopsis, while they were distributed in different modules in a decentralized network in C. bungeana. Therefore, our results reveal that C. bungeana may have optimized its N allocation strategy by producing and storing amino acids as efficient N reserve and adopting a decentralized network for N utilization, which may equip the plant with powerful capabilities for environmental adaptions.

Early transcriptional response of terpenoid metabolism to Colletotrichum gloeosporioides in a resistant wild strawberry Fragaria nilgerrensis

Modern strawberry production is often threatened by microbe pathogens. Anthracnose is among the most prominent fungal disease caused mainly by Colletotrichum gloeosporioides and leads to large-scale losses both in quality and yield. Little is known regarding the mechanisms underlying the genetics in the strawberry-C. gloeosporioides interaction. In the current research, a wild accession 'Fragaria nilgerrensis' is used as a resistant model to study the roles of terpenoid and terpene genes in leaf response to C. gloeosporioides. We found that several terpenoids and terpene genes were up-regulated at early time points after challenged with C. gloeosporioides. Among the metabolites detected, sesquiterpenes were the most significantly accumulated compounds, increasing up to ~12-fold at 18 h post infection (hpi), followed by monoterpenes which showed a slight increase upon infection. Consistently, the time-resolved transcriptome data revealed that genes pertaining to terpenoid metabolism were rapidly up-regulated and co-expressed with signaling pathway genes relevant to defense response. Notably, quantitative real-time PCR confirmed that the expression of five terpene synthase genes (TPS) were greatly enhanced, by a factor of one to three orders of magnitude at 3-6 hpi. Our results reveal a possible link between rapidly induced terpenoid metabolism and the autoimmunity underlying anthracnose resistance in a wild strawberry species.