Quantitative Disease Resistance Research Articles

Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to Sclerotinia sclerotiorum.

Sclerotinia sclerotiorum (Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor genes. Genome-wide identification of genes involved in QDR to Ss is yet to be conducted. In this study, we integrated several assays including genome-wide association study (GWAS), multi-omics co-localization, and machine learning prediction to identify, on a genome-wide scale, genes involved in the oilseed rape QDR to Ss. Employing GWAS and multi-omics co-localization, we identified seven resistance-associated loci (RALs) associated with oilseed rape resistance to Ss. Furthermore, we developed a machine learning algorithm and named it Integrative Multi-Omics Analysis and Machine Learning for Target Gene Prediction (iMAP), which integrates multi-omics data to rapidly predict disease resistance-related genes within a broad chromosomal region. Through iMAP based on the identified RALs, we revealed multiple calcium signaling genes related to the QDR to Ss. Population-level analysis of selective sweeps and haplotypes of variants confirmed the positive selection of the predicted calcium signaling genes during evolution. Overall, this study has developed an algorithm that integrates multi-omics data and machine learning methods, providing a powerful tool for predicting target genes associated with specific traits. Furthermore, it makes a basis for further understanding the role and mechanisms of calcium signaling genes in the QDR to Ss.

Comparative transcriptomics of soybean genotypes with partial resistance towards Phytophthora sojae, Conrad, and M92-220, to moderately susceptible fast neutron mutant soybeans and Sloan.

The breeding of disease-resistant soybeans cultivars to manage Phytophthora root and stem rot caused by the pathogen Phytophthora sojae involves combining quantitative disease resistance (QDR) and Rps gene-mediated resistance. To identify and confirm potential mechanisms of QDR towards P. sojae, we conducted a time course study comparing changes in gene expression among Conrad and M92-220 with high QDR to susceptible genotypes, Sloan and 3 mutants derived from fast neutron (FN) irradiation of M92-220. Differentially expressed genes from Conrad and M92-220 indicated several shared defense-related pathways at the transcriptomic level, but also defense pathways unique to each cultivar such as stilbenoid, diarylheptanoid and gingerol biosynthesis, and monobactam biosynthesis. Gene Ontology pathway analysis showed that the susceptible FN mutants lacked enrichment of three terpenoid related-pathways and two cell wall-related pathways at either one or both timepoints, in contrast to M92-220. The susceptible mutants also lacked enrichment of potentially important KEGG pathways at either one or both timepoints, including sesquiterpenoid and triterpenoid biosynthesis, thiamine metabolism, arachidonic acid, stilbenoid, diarylheptanoid and gingerol biosynthesis, and monobactam biosynthesis. Additionally, thirty-one genes which were differentially expressed in M92-220 following P. sojae infection were not expressed in the mutants. These 31 genes have annotations related to unknown proteins, valine, leucine, and isoleucine biosynthesis and protein and lipid metabolic processes. The results of this study confirm previously proposed mechanisms of QDR, provide evidence for potential novel QDR pathways in M92-220, and furthers our understanding of the complex network associated with QDR mechanisms in soybean towards P. sojae.

Molecular complexity of quantitative immunity inplants: 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 KinaSe1), 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 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.

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.

Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus)

Key messageUsing associative transcriptomics, our study identifies genes conferring resistance to four diverse fungal pathogens in crops, emphasizing key genetic determinants of multi-pathogen resistance.Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species. Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus constitutive QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae, and Verticillium longisporum. We did not identify any shared loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen—hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR. This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight constitutive expressed candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. In conclusion, this study represents an advancement in our understanding of broad-spectrum QDR in B. napus and is a significant resource for the scientific community.

The Effects of Genetic Distance and Genetic Diversity on Genomic Prediction Accuracy for Soybean Quantitative Disease Resistance to Phytophthora sojae

Assessing quantitative disease resistance and other complex traits can be time- and space-consuming, limiting the number of lines that can be evaluated in a breeding program. A potential improvement is the application of genomic prediction models, where genotypic data are used to calculate genomic estimated breeding values, referred to as genomic selection. Genomic prediction uses training datasets, where a germplasm panel is phenotyped and genotyped to calculate genomic estimated breeding values in a validation panel of lines based solely on genotypic data. To develop an initial phenotypic dataset, breeders may consider utilizing previously phenotyped lines in a publicly available dataset, such as plant introductions (PIs) from the USDA Soybean collection. A relevant question is, how effective is genomic prediction across diverse training and prediction panels? To answer this, we used previously collected phenotypic data for quantitative disease resistance toward Phytophthora sojae. Diverse germplasm panels were represented by sets of PIs originating from the United States, the Republic of Korea, and worldwide, for a total collection of 1,768 PIs. The accuracy of the prediction model was significantly influenced by population differentiation between panels, as well as genetic and phenotypic diversity. Low prediction accuracy resulted when the panel used to create the prediction model was highly differentiated from the validation panel. However, the addition of a small number of accessions to the training panel that were more closely related to the validation panel resulted in increased accuracy. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The ZmWAKL-ZmWIK-ZmBLK1-ZmRBOH4 module provides quantitative resistance to gray leaf spot in maize.

Gray leaf spot (GLS), caused by the fungal pathogens Cercospora zeae-maydis and Cercospora zeina, is a major foliar disease of maize worldwide (Zea mays L.). Here we demonstrate that ZmWAKL encoding cell-wall-associated receptor kinase-like protein is the causative gene at the major quantitative disease resistance locus against GLS. The ZmWAKLY protein, encoded by the resistance allele, can self-associate and interact with a leucine-rich repeat immune-related kinase ZmWIK on the plasma membrane. The ZmWAKLY/ZmWIK receptor complex interacts with and phosphorylates the receptor-like cytoplasmic kinase (RLCK) ZmBLK1, which in turn phosphorylates its downstream NADPH oxidase ZmRBOH4. Upon pathogen infection, ZmWAKLY phosphorylation activity is transiently increased, initiating immune signaling from ZmWAKLY, ZmWIK, ZmBLK1 to ZmRBOH4, ultimately triggering a reactive oxygen species burst. Our study thus uncovers the role of the maize ZmWAKL-ZmWIK-ZmBLK1-ZmRBOH4 receptor/signaling/executor module in perceiving the pathogen invasion, transducing immune signals, activating defense responses and conferring increased resistance to GLS.

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.

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach.

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for 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.

Toward combining qualitative race-specific and quantitative race-nonspecific disease resistance by genomic selection

Key messageA novel genomic selection strategy offers the unique opportunity to develop qualitative race-specific resistant varieties that possess high levels of the more durable quantitative race-nonspecific resistance in their genetic background.Race-specific qualitative resistance genes (R-genes) are conferring complete resistance in many pathosystems, but are frequently overcome by new virulent pathogen races. Once the deployed R-genes are overcome, a wide variation of quantitative disease resistance (QDR) can be observed in a set of previously race-specific, i.e., completely resistant genotypes—a phenomenon known as “vertifolia effect.” This race-nonspecific QDR is considered to be more durable in the long term, but provides merely a partial protection against pathogens. This simulation study aimed to detangle race-specific R-gene-mediated resistance of pending selection candidates and the QDR in their genetic background by employing different genomic selection strategies. True breeding values that reflected performance data for rust resistance in wheat were simulated, and used in a recurrent genomic selection based on several prediction models and training population designs. Using training populations that were devoid of race-specific R-genes was thereby pivotal for an efficient improvement of QDR in the long term. Marker-assisted preselection for the presence of R-genes followed by a genomic prediction for accumulating the many small to medium effect loci underlying QDR in the genetic background of race-specific resistant genotypes appeared furthermore to be a promising approach to select simultaneously for both types of resistance. The practical application of such a knowledge-driven genomic breeding strategy offers the opportunity to develop varieties with multiple layers of resistance, which have the potential to prevent intolerable crop losses under epidemic situations by displaying a high level of QDR even when race-specific R-genes have been overcome by evolving pathogen populations.

Temperature increase modifies susceptibility to Verticillium wilt in Medicago spp and may contribute to the emergence of more aggressive pathogenic strains.

Global warming is expected to have a direct impact on plant disease patterns in agro-eco-systems. However, few analyses report the effect of moderate temperature increase on disease severity due to soil-borne pathogens. For legumes, modifications of root plant-microbe interactions either mutualistic or pathogenic due to climate change may have dramatic effects. We investigated the effect of increasing temperature on the quantitative disease resistance to Verticillium spp., a major soil-borne fungal pathogen, in the model legume Medicago truncatula and the crop M. sativa. First, twelve pathogenic strains isolated from various geographical origin were characterized with regard to their in vitro growth and pathogenicity at 20°C, 25°C and 28°C. Most of them exhibited 25°C as the optimum temperature for in vitro parameters, and between 20°C and 25°C for pathogenicity. Second, a V. alfalfae strain was adapted to the higher temperature by experimental evolution, i.e. three rounds of UV mutagenesis and selection for pathogenicity at 28°C on a susceptible M. truncatula genotype. Inoculation of monospore isolates of these mutants on resistant and susceptible M. truncatula accessions revealed that at 28°C they were all more aggressive than the wild type strain, and that some had acquired the ability to cause disease on resistant genotype. Third, one mutant strain was selected for further studies of the effect of temperature increase on the response of M. truncatula and M. sativa (cultivated alfalfa). The response of seven contrasted M. truncatula genotypes and three alfalfa varieties to root inoculation was followed using disease severity and plant colonization, at 20°C, 25°C and 28°C. With increasing temperature, some lines switched from resistant (no symptoms, no fungus in the tissues) to tolerant (no symptoms but fungal growth into the tissues) phenotypes, or from partially resistant to susceptible. Further studies in greenhouse evidence the reduction in plant fitness due to disease in susceptible lines. We thus report that root pathogenic interactions are affected by anticipated global warming, with trends towards increased plant susceptibility and larger virulence for hot-adapted strains. New threats due to hot-adapted strains of soil-borne pathogens, with possibly wider host range and increased aggressiveness, might occur.

Overexpression of SQUALENE SYNTHASE Reduces Nicotiana benthamiana Resistance against Phytophthora infestans

Plant triterpenoids play a critical role in plant resistance against Phytophthora infestans de Bary, the causal pathogen of potato and tomato late blight. However, different triterpenoids could have contrasting functions on plant resistance against P. infestans. In this study, we targeted the key biosynthetic gene of all plant triterpenoids, SQUALENE SYNTHASE (SQS), to examine the function of this gene in plant-P. infestans interactions. A post-inoculation, time-course gene expression analysis revealed that SQS expression was induced in Nicotiana benthamiana but was transiently suppressed in Solanum lycopersicum. Consistent with the host-specific changes in SQS expression, concentrations of major triterpenoid compounds were only induced in S. lycopersicum. A stable overexpression of SQS in N. benthamiana reduced plant resistance against P. infestans and induced the hyperaccumulation of stigmasterol. A comparative transcriptomics analysis of the transgenic lines showed that diverse plant physiological processes were influenced by SQS overexpression, suggesting that phytosterol content regulation may not be the sole mechanism through which SQS promotes plant susceptibility towards P. infestans. This study provides experimental evidence for the host-specific transcriptional regulation and function of SQS in plant interactions with P. infestans, offering a novel perspective in examining the quantitative disease resistance against late blight.

Quantitative disease resistance: Multifaceted players in plant defense.

In contrast to large-effect qualitative disease resistance, quantitative disease resistance (QDR) exhibits partial and generally durable resistance and has been extensively utilized in crop breeding. The molecular mechanisms underlying QDR remain largely unknown but considerable progress has been made in this area in recent years. In this review, we summarize the genes that have been associated with plant QDR and their biological functions. Many QDR genes belong to the canonical resistance gene categories with predicted functions in pathogen perception, signal transduction, phytohormone homeostasis, metabolite transport and biosynthesis, and epigenetic regulation. However, other "atypical" QDR genes are predicted to be involved in processes that are not commonly associated with disease resistance, such as vesicle trafficking, molecular chaperones, and others. This diversity of function for QDR genes contrasts with qualitative resistance, which is often based on the actions of nucleotide-binding leucine-rich repeat (NLR) resistance proteins. An understanding of the diversity of QDR mechanisms and of which mechanisms are effective against which classes of pathogens will enable the more effective deployment of QDR to produce more durably resistant, resilient crops.

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.

Identification and characterization of pleiotropic and epistatic QDRL conferring partial resistance to Pythium irregulare and P. sylvaticum in soybean.

Pleiotropic and epistatic quantitative disease resistance loci (QDRL) were identified for soybean partial resistance to different isolates of Pythium irregulare and Pythium sylvaticum. Pythium root rot is an important seedling disease of soybean [Glycine max (L.) Merr.], a crop grown worldwide for protein and oil content. Pythium irregulare and P. sylvaticum are two of the most prevalent and aggressive Pythium species in soybean producing regions in the North Central U.S. Few studies have been conducted to identify soybean resistance for management against these two pathogens. In this study, a mapping population (derived from E13390 x E13901) with 228 F4:5 recombinant inbred lines were screened against P. irregulare isolate MISO 11-6 and P. sylvaticum isolate C-MISO2-2-30 for QDRL mapping. Correlation analysis indicated significant positive correlations between soybean responses to the two pathogens, and a pleiotropic QDRL (qPirr16.1) was identified. Further investigation found that the qPirr16.1 imparts dominant resistance against P. irregulare, but recessive resistance against P. sylvaticum. In addition, two QDRL, qPsyl15.1, and qPsyl18.1 were identified for partial resistance to P. sylvaticum. Further analysis revealed epistatic interactions between qPirr16.1 and qPsyl15.1 for RRW and DRX, whereas qPsyl18.1 contributed resistance to RSE. Marker-assisted resistance spectrum analysis using F6:7 progeny lines verified the resistance of qPirr16.1 against four additional P. irregulare isolates. Intriguingly, although the epistatic interaction of qPirr16.1 and qPsyl15.1 can be confirmed using two additional isolates of P. sylvaticum, the interaction appears to be suppressed for the other two P. sylvaticum isolates. An 'epistatic gene-for-gene' model was proposed to explain the isolate-specific epistatic interactions. The integration of the QDRL into elite soybean lines containing all the desirable alleles has been initiated.

"Late" effectors from Leptosphaeria maculans as tools for identifying novel sources of resistance in Brassica napus.

The Dothideomycete Leptosphaeria maculans, causing stem canker (blackleg) of Brassica napus, secretes different cocktails of effectors at specific infection stages. Some effectors (“Late” effectors) are specifically produced during the long asymptomatic phase of stem colonization. By manipulating their expression so that they are overexpressed during cotyledon infection (OEC transformants of the fungus), we previously postulated that resistance genes operating in the stem may be involved in gene‐for‐gene relationship and thus contribute to quantitative disease resistance (QDR). Here, we selected 10 relevant new effector genes, and we generated OEC transformants to screen a collection of 130 B. napus genotypes, representative of the available diversity in the species. Five B. napus accessions showed a typical hypersensitive response when challenged with effectors LmSTEE98 or LmSTEE6826 at the cotyledon stage, and all belong to the semi‐winter type of the diversity panel. In addition, five winter‐type genotypes displayed an intermediate response to another late effector, LmSTEE7919. These new interactions now have to be genetically validated to check that they also correspond to gene‐for‐gene interactions. In all cases, they potentially provide novel resources, easy to breed for, and accounting for part of the quantitative resistance in a species for which we are currently facing limited resistance sources.

Analysis of Tissue-Specific Defense Responses to Sclerotinia sclerotiorum in Brassica napus.

Sclerotinia stem rot (SSR) caused by Sclerotinia sclerotiorum (S. sclerotiorum) is the main disease threat of oilseed rape (Brassica napus), resulting in huge economic losses every year. SSR resistance manifests as quantitative disease resistance (QDR), and no gene with complete SSR resistance has been cloned or reported so far. Transcriptome analysis has revealed a large number of defense-related genes and response processes. However, the similarities and differences in the defense responses of different tissues are rarely reported. In this study, we analyzed the similarities and differences of different tissues in response to S. sclerotiorum at 24 h post inoculation (hpi) by using the published transcriptome data for respective leaf and stem inoculation. At 24 hpi, large differences in gene expression exist in leaf and stem, and there are more differentially expressed genes and larger expression differences in leaf. The leaf is more sensitive to S. sclerotiorum and shows a stronger response than stem. Different defense responses appear in the leaf and stem, and the biosynthesis of lignin, callose, lectin, chitinase, PGIP, and PR protein is activated in leaf. In the stem, lipid metabolism-mediated defense responses are obviously enhanced. For the common defense responses in both leaf and stem, the chain reactions resulting from signal transduction and biological process take the primary responsibility. This research will be beneficial to exploit the potential of different tissues in plant defense and find higher resistance levels of genotypic variability in different environments. Our results are significant in the identification of resistance genes and analysis of defense mechanisms.

Identification of Candidate Genes for a Major Quantitative Disease Resistance Locus From Soybean PI 427105B for Resistance to Phytophthora sojae

Phytophthora root and stem rot is a yield-limiting soybean disease caused by the soil-borne oomycete Phytophthora sojae. Although multiple quantitative disease resistance loci (QDRL) have been identified, most explain <10% of the phenotypic variation (PV). The major QDRL explaining up to 45% of the PV were previously identified on chromosome 18 and represent a valuable source of resistance for soybean breeding programs. Resistance alleles from plant introductions 427105B and 427106 significantly increase yield in disease-prone fields and result in no significant yield difference in fields with less to no disease pressure. In this study, high-resolution mapping reduced the QDRL interval to 3.1 cm, and RNA-seq analysis of near-isogenic lines (NILs) varying at QDRL-18 pinpointed a single gene of interest which was downregulated in inoculated NILs carrying the resistant allele compared to inoculated NILs with the susceptible allele. This gene of interest putatively encodes a serine–threonine kinase (STK) related to the AtCR4 family and may be acting as a susceptibility factor, based on the specific increase of jasmonic acid concentration in inoculated NILs. This work facilitates further functional analyses and marker-assisted breeding efforts by prioritizing candidate genes and narrowing the targeted region for introgression.