Genetic Architecture of Charcoal Rot (Macrophomina phaseolina) Resistance in Soybean Revealed Using a Diverse Panel

Genome-wide association study for resistance to Macrophomina phaseolina in maize (Zea mays L.)

Maize (Zea mays L.) is a frequently used food source in human and animal nutrition. Macrophomina phaseolina is a fungal pathogen causing charcoal rot disease in many plants, especially maize. This pathogen causes high yield losses in maize. The development of resistant maize genotypes is of great importance in controlling this disease. In this study, the population structure of 120 different maize genotypes with varying levels of disease resistance was determined and genome-wide association studies were performed. Each genotype was subjected to the pathogen under controlled conditions and their phenotypic responses to the disease were analyzed. Afterwards, single nucleotide polymorphisms were determined by DArT-seq sequencing. After filtering the SNP data, 37,470 clean SNPs were obtained. The population structure was analyzed with STRUCTURE software, and it was determined that the population was divided into two subgroups. The relationship between phenotypic and genotypic data was analyzed using the MLM (Q + K) model in TASSEL software. As a result, seven SNPs markers located on four different chromosomes were associated with disease resistance. The related markers can be used in the future for the development of maize varieties resistant to M. phaseolina by marker-assisted selection.

Morpho-cultural, pathogenic, and genetic characterization of Indian isolates of Macrophomina phaseolina causing charcoal rot in soybean

Macrophomina phaseolina, a devastating soil and seed-borne fungus causing charcoal rot in soybean, poses a significant challenge to soybean production and breeding programs across all major soybean-growing regions of India. Fifty-five M. phaseolina isolates were collected from India's eight diverse soybean-growing agroecological regions. These isolates were examined for morpho-cultural, molecular, and pathogenic variability. All these isolates were pathogenic to the soybean and had significant variability for different Morpho-cultural characters. Principal component analysis (PCA) showed that most of Morpho-cultural traits are not having association with pathogenic traits. Cluster analysis showed that all these 55 isolates of M. phaseolina were classified into two major groups, and virulence characters did not separate based on origin. Group B showed more diversity and included the most virulent pathogen isolates. Phylogenetic analysis of the Internal Transcribed Spacer (ITS), a conserved rDNA region, revealed limited diversity among the 55 isolates. Irrespective of morpho-cultural and pathogenic characters, most isolates (n = 52) were clustered in a group. Pathogenic variability analysis has revealed region specific most virulent isolate from diverse agroecological regions of India. GGE biplot segregated the main effect of each component, cultivars (G), isolates (I), and G × I interactions with significant levels (p < 0.001). The virulence of isolates contributed 56.30 % of the total variation, followed by varieties (36.79 %) and G × I interaction (4.96 %). GGE biplot also provides information on two highly discriminative isolates. These isolates may be useful for screening genotypes and identifying quantitative trait loci (QTL) linked to soybean charcoal rot.

Identification of novel genes associated with herbicide tolerance in Lentil (Lens culinaris ssp. culinaris Medik.)

Weeds pose a major constraint in lentil cultivation, leading to decrease farmers' revenues by reducing the yield and increasing the management costs. The development of herbicide tolerant cultivars is essential to increase lentil yield. Even though herbicide tolerant lines have been identified in lentils, breeding efforts are still limited and lack proper validation. Marker assisted selection (MAS) can increase selection accuracy at early generations. Total 292 lentil accessions were evaluated under different dosages of two herbicides, metribuzin and imazethapyr, during two seasons at Marchouch, Morocco and Terbol, Lebanon. Highly significant differences among accessions were observed for days to flowering (DF) and maturity (DM), plant height (PH), biological yield (BY), seed yield (SY), number of pods per plant (NP), as well as the reduction indices (RI) for PH, BY, SY and NP. A total of 10,271 SNPs markers uniformly distributed along the lentil genome were assayed using Multispecies Pulse SNP chip developed at Agriculture Victoria, Melbourne. Meta-GWAS analysis was used to detect marker-trait associations, which detected 125 SNPs markers associated with different traits and clustered in 85 unique quantitative trait loci. These findings provide valuable insights for initiating MAS programs aiming to enhance herbicide tolerance in lentil crop.

Transgressive segregation, hopeful monsters, and phenotypic selection drove rapid genetic gains and breakthroughs in predictive breeding for quantitative resistance to Macrophomina in strawberry

Two decades have passed since the strawberry (Fragaria x ananassa) disease caused by Macrophomina phaseolina, a necrotrophic soilborne fungal pathogen, began surfacing in California, Florida, and elsewhere. This disease has since become one of the most common causes of plant death and yield losses in strawberry. The Macrophomina problem emerged and expanded in the wake of the global phase-out of soil fumigation with methyl bromide and appears to have been aggravated by an increase in climate change-associated abiotic stresses. Here we show that sources of resistance to this pathogen are rare in gene banks and that the favorable alleles they carry are phenotypically unobvious. The latter were exposed by transgressive segregation and selection in populations phenotyped for resistance to Macrophomina under heat and drought stress. The genetic gains were immediate and dramatic. The frequency of highly resistant individuals increased from 1% in selection cycle 0 to 74% in selection cycle 2. Using GWAS and survival analysis, we found that phenotypic selection had increased the frequencies of favorable alleles among 10 loci associated with resistance and that favorable alleles had to be accumulated among four or more of these loci for an individual to acquire resistance. An unexpectedly straightforward solution to the Macrophomina disease resistance breeding problem emerged from our studies, which showed that highly resistant cultivars can be developed by genomic selection per se or marker-assisted stacking of favorable alleles among a comparatively small number of large-effect loci.

Genome-wide association study for charcoal rot resistance in soybean harvested in Kazakhstan

Charcoal rot (CR) caused by the fungal pathogen Macrophomina phaseolina is a devastating disease affecting soybean (Glycine max (L.) Merrill.) worldwide. Identifying the genetic factors associated with resistance to charcoal rot is crucial for developing disease-resistant soybean cultivars. In this research, we conducted a genome-wide association study (GWAS) using different models and genotypic data to unravel the genetic determinants underlying soybean resistance to сharcoal rot. The study relied on a panel of 252 soybean accessions, comprising commercial cultivars and breeding lines, to capture genetic variations associated with resistance. The phenotypic evaluation was performed under natural conditions during the 2021-2022 period. Disease severity and survival rates were recorded to quantify the resistance levels in the accessions. Genotypic data consisted of two sets: the results of genotyping using the Illumina iSelect 6K SNP (single-nucleotide polymorphism) array and the results of whole-genome resequencing. The GWAS was conducted using four different models (MLM, MLMM, FarmCPU, and BLINK) based on the GAPIT platform. As a result, SNP markers of 11 quantitative trait loci associated with CR resistance were identified. Candidate genes within the identified genomic regions were explored for their functional annotations and potential roles in plant defense responses. The findings from this study may further contribute to the development of molecular breeding strategies for enhancing CR resistance in soybean cultivars. Marker-assisted selection can be efficiently employed to accelerate the breeding process, enabling the development of cultivars with improved resistance to сharcoal rot. Ultimately, deploying resistant cultivars may significantly reduce yield losses and enhance the sustainability of soybean production, benefiting farmers and ensuring a stable supply of this valuable crop.

Deciphering the genetic architecture of resistance to Corynespora cassiicola in soybean (Glycine max L.) by integrating genome-wide association mapping and RNA-Seq analysis

Target spot caused by Corynespora cassiicola is a problematic disease in tropical and subtropical soybean (Glycine max) growing regions. Although resistant soybean genotypes have been identified, the genetic mechanisms underlying target spot resistance has not yet been studied. To address this knowledge gap, this is the first genome-wide association study (GWAS) conducted using the SoySNP50K array on a panel of 246 soybean accessions, aiming to unravel the genetic architecture of resistance. The results revealed significant associations of 14 and 33 loci with resistance to LIM01 and SSTA C. cassiicola isolates, respectively, with six loci demonstrating consistent associations across both isolates. To identify potential candidate genes within GWAS-identified loci, dynamic transcriptome profiling was conducted through RNA-Seq analysis. The analysis involved comparing gene expression patterns between resistant and susceptible genotypes, utilizing leaf tissue collected at different time points after inoculation. Integrating results of GWAS and RNA-Seq analyses identified 238 differentially expressed genes within a 200 kb region encompassing significant quantitative trait loci (QTLs) for disease severity ratings. These genes were involved in defense response to pathogen, innate immune response, chitinase activity, histone H3-K9 methylation, salicylic acid mediated signaling pathway, kinase activity, and biosynthesis of flavonoid, jasmonic acid, phenylpropanoid, and wax. In addition, when combining results from this study with previous GWAS research, 11 colocalized regions associated with disease resistance were identified for biotic and abiotic stress. This finding provides valuable insight into the genetic resources that can be harnessed for future breeding programs aiming to enhance soybean resistance against target spot and other diseases simultaneously.

Molecular interactions between the soilborne pathogenic fungus Macrophomina phaseolina and its host plants

Mentioned for the first time in an article 1971, the occurrence of the term "Macrophomina phaseolina" has experienced a steep increase in the scientific literature over the past 15 years. Concurrently, incidences of M. phaseolina-caused crop diseases have been getting more frequent. The high levels of diversity and plasticity observed for M. phasolina genomes along with a rich equipment of plant cell wall degrading enzymes, secondary metabolites and putative virulence effectors as well as the unusual longevity of microsclerotia, their asexual reproduction structures, make this pathogen very difficult to control and crop protection against it very challenging. During the past years several studies have emerged reporting on host defense measures against M. phaseolina, as well as mechanisms of pathogenicity employed by this fungal pathogen. While most of these studies have been performed in crop systems, such as soybean or sesame, recently interactions of M. phaseolina with the model plant Arabidopsis thaliana have been described. Collectively, results from various studies are hinting at a complex infection cycle of M. phaseolina, which exhibits an early biotrophic phase and switches to necrotrophy at later time points during the infection process. Consequently, responses of the hosts are complex and seem coordinated by multiple defense-associated phytohormones. However, at this point no robust and strong host defense mechanism against M. phaseolina has been described.

Identification and genetic diversity analysis of high-yielding charcoal rot resistant soybean genotypes

Charcoal rot disease caused by Macrophomina phaseolina (Tassi) Goid is one of the most devastating diseases in soybean in India. During 2018, 226 diverse soybean genotypes were evaluated for genetic resistance under hot-spot conditions. Out of them, a subset of 151 genotypes were selected based on Percent Disease Incidence (PDI) and better agronomic performance. Out of these 151 genotypes evaluated during 2019, 43 genotypes were selected based on PDI and superior agronomic performance for further field evaluation and molecular characterization. During 2020 and 2021, these forty-three genotypes, were evaluated for PDI, Area Under Disease Progress Curve (AUDPC), and grain yield. In 2020, genotype JS 20-20 showed least PDI (0.42) and AUDPC (9.37).Highest grain yield was recorded by the genotype JS 21-05 (515.00 g). In 2021, genotype JS 20-20 exhibited least PDI (0.00) and AUDPC (0.00).Highest grain yield was recorded in JS 20-98 (631.66 g). Across both years, JS 20-20 had the least PDI (0.21) and AUDPC (4.68), while grain yield was highest in JS 20-98 (571.67 g). Through MGIDI (multi-trait genotype-ideotype distance) analysis, JS 21-05 (G19), JS 22-01 (G43), JS 20-98 (G28) and JS 20-20 (G21) were identified as the ideotypes with respect to the traits that were evaluated. Two unique alleles, Satt588 (100 bp) on linkage group K (Chromosome no 9) and Sat_218 (200 bp) on linkage group H (Chromosome no 12), were specific for thetwo resistant genotypes JS 21-71and DS 1318, respectively. Through cluster analysis, it was observed that the genotypes bred at Jabalpur were more genetically related.

Status of Phytotoxins Isolated from Necrotrophic Fungi Causing Diseases on Grain Legumes

Fungal phytotoxins can be defined as secondary metabolites toxic to host plants and are believed to be involved in the symptoms developed of a number of plant diseases by targeting host cellular machineries or interfering with host immune responses. As any crop, legumes can be affected by a number of fungal diseases, causing severe yield losses worldwide. In this review, we report and discuss the isolation, chemical, and biological characterization of fungal phytotoxins produced by the most important necrotrophic fungi involved in legume diseases. Their possible role in plant-pathogen interaction and structure-toxicity relationship studies have also been reported and discussed. Moreover, multidisciplinary studies on other prominent biological activity conducted on reviewed phytotoxins are described. Finally, we explore the challenges in the identification of new fungal metabolites and their possible applications in future experiments.

Genome-wide association study reveals novel loci and a candidate gene for resistance to frogeye leaf spot (Cercospora sojina) in soybean

Frogeye leaf spot, caused by the fungus Cercospora sojina, is a threat to soybeans in the southeastern and midwestern United States that can be controlled by crop genetic resistance. Limited genetic resistance to the disease has been reported, and only three sources of resistance have been used in modern soybean breeding. To discover novel sources and identify the genomic locations of resistance that could be used in soybean breeding, a GWAS was conducted using a panel of 329 soybean accessions selected to maximize genetic diversity. Accessions were phenotyped using a 1-5 visual rating and by using image analysis to count lesion number and measure the percent of leaf area diseased. Eight novel loci on eight chromosomes were identified for three traits utilizing the FarmCPU or BLINK models, of which a locus on chromosome 11 was highly significant across all model-trait combinations. KASP markers were designed using the SoySNP50K Beadchip and variant information from 65 of the accessions that have been sequenced to target SNPs in the gene model Glyma.11g230400, a LEUCINE-RICH REPEAT RECEPTOR-LIKE PROTEIN KINASE. The association of a KASP marker, GSM990, designed to detect a missense mutation in the gene was the most significant with all three traits in a genome-wide association, and the marker may be useful to select for resistance to frogeye leaf spot in soybean breeding.

Soybean Seed Sugars: A Role in the Mechanism of Resistance to Charcoal Rot and Potential Use as Biomarkers in Selection

Charcoal rot, caused by Macrophomina phaseolina, is a major soybean disease resulting in significant yield loss and poor seed quality. Currently, no resistant soybean cultivar is available in the market and resistance mechanisms to charcoal rot are unknown, although the disease is believed to infect plants from infected soil through the roots by unknown toxin-mediated mechanisms. The objective of this research was to investigate the association between seed sugars (sucrose, raffinose, stachyose, glucose, and fructose) and their role as biomarkers in the soybean defense mechanism in the moderately resistant (MR) and susceptible (S) genotypes to charcoal rot. Seven MR and six S genotypes were grown under irrigated (IR) and non-irrigated (NIR) conditions. A two-year field experiment was conducted in 2012 and 2013 at Jackson, TN, USA. The main findings in this research were that MR genotypes generally had the ability to maintain higher seed levels of sucrose, glucose, and fructose than did S genotypes. Conversely, susceptible genotypes showed a higher level of stachyose and lower levels of sucrose, glucose, and fructose. This was observed in 6 out of 7 MR genotypes and in 4 out of 6 S genotypes in 2012; and in 5 out of 7 MR genotypes and in 5 out of 6 S genotypes in 2013. The response of S genotypes with higher levels of stachyose and lower sucrose, glucose, and fructose, compared with those of MR genotypes, may indicate the possible role of these sugars in a defense mechanism against charcoal rot. It also indicates that nutrient pathways in MR genotypes allowed for a higher influx of nutritious sugars (sucrose, glucose, and fructose) than did S genotypes, suggesting these sugars as potential biomarkers for selecting MR soybean plants after harvest. This research provides new knowledge on seed sugars and helps in understanding the impact of charcoal rot on seed sugars in moderately resistant and susceptible genotypes.

Identification of sources of resistance in cowpea lines to Macrophomina root rot disease in Northern Ghana

Macrophomina root rot disease (MRRD) caused by Macrophomina phaseolina is an emerging threat to the profitable cowpea production in northern Ghana. Recommended control methods including the use of fungicides are ineffective and expensive for resource poor farmers whilst biocontrol options are not commercially available. An integrated method based on host plant resistance is considered the cheapest and most effective method of managing the disease. This study sought to confirm and characterize previously identified MRRD isolates from Northern Ghana using molecular technology, and to identify cowpea with potential sources of resistance to the MRRD. A PCR assay of ten isolates of the cowpea root rot pathogen revealed all isolates belonged to the species M. phaseolina, whilst a nucleotide BLAST of eight isolates showed 98% similarity with the sequences of Macrophomina isolates from other host available in GenBank. A sick pot method evaluation of 49 cowpea lines found 10 lines resistant to MRRD on a 1-9 disease severity scale (disease score, less than 5). A selection of eight resistant lines (Suvita 2, Abagbaala, IT97K573-1-1, IT93K-503-1-1, Hewale, AV2 3224, Nhyira and T2T4), and a susceptible check (Songotra) were evaluated against 10 isolates of M. phaseolina using a sick pot method. All the genotypes except for the susceptible check were resistant to MRRD. Thus, these genotypes could be used in cowpea MRRD resistance breeding programs.

Breeding for disease resistance in soybean: a global perspective

KEY MESSAGE

This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean

Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accessions, and have been used for a myriad of traits. In field studies, genetic accessions are phenotyped across multiple environments and replications, which takes a significant amount of labor and resources. Deep Learning (DL) techniques can be effective for analyzing image-based tasks; thus DL methods are becoming more routine for phenotyping traits to save time and effort. This research aims to conduct GWAS on sudden death syndrome (SDS) of soybean [Glycine max L. (Merr.)] using disease severity from both visual field ratings and DL-based (using images) severity ratings collected from 473 accessions. Images were processed through a DL framework that identified soybean leaflets with SDS symptoms, and then quantified the disease severity on those leaflets into a few classes with mean Average Precision of 0.34 on unseen test data. Both visual field ratings and image-based ratings identified significant single nucleotide polymorphism (SNP) markers associated with disease resistance. These significant SNP markers are either in the proximity of previously reported candidate genes for SDS or near potentially novel candidate genes. Four previously reported SDS QTL were identified that contained a significant SNPs, from this study, from both a visual field rating and an image-based rating. The results of this study provide an exciting avenue of using DL to capture complex phenotypic traits from images to get comparable or more insightful results compared to subjective visual field phenotyping of traits for disease symptoms.

Molecular Breeding to Overcome Biotic Stresses in Soybean: Update

Soybean (Glycine max (L.) Merr.) is an important leguminous crop and biotic stresses are a global concern for soybean growers. In recent decades, significant development has been carried outtowards identification of the diseases caused by pathogens, sources of resistance and determination of loci conferring resistance to different diseases on linkage maps of soybean. Host-plant resistance is generally accepted as the bestsolution because of its role in the management of environmental and economic conditions of farmers owing to low input in terms of chemicals. The main objectives of soybean crop improvement are based on the identification of sources of resistance or tolerance against various biotic as well as abiotic stresses and utilization of these sources for further hybridization and transgenic processes for development of new cultivars for stress management. The focus of the present review is to summarize genetic aspects of various diseases caused by pathogens in soybean and molecular breeding research work conducted to date.

Occurrence of Macrophomina phaseolina in Israel: Challenges for Disease Management and Crop Germplasm Enhancement

Macrophomina phaseolina is a soil-borne fungal pathogen infecting many important crop plants. The fungus, which can survive on crop debris for a long period of time, causes charcoal rot disease by secreting a diverse array of cell-wall degrading enzymes and toxins. M. phaseolina thrives during periods of high temperatures and arid conditions, as typically occur in Israel and other countries with a Mediterranean climate. Crop losses due to charcoal rot can be expected to increase and spread to other countries in a warming global climate. Management of this pathogen is challenging, requiring an array of approaches for the various crop hosts. Approaches that have had some success in Israel include grafting of melons and watermelons on resistant squash rootstocks and soil application of fungicide to reduce disease incidence in melons, fumigation and alterations in planting date and mulching of strawberries, and alteration in irrigation regime of cotton. Elsewhere, these approaches, as well as soil amendments and addition of organisms that are antagonistic to M. phaseolina, have had success in some crop situations. Management through host resistance would be the most sustainable approach, but it requires identifying a resistant germplasm for each crop and introgressing the resistance into the leading cultivars. Resistance to charcoal rot is under complex genetic control in most crops, posing a great challenge for its introgression into elite germplasm. Moreover, fast, reliable methods of screening for resistance would have to be developed for each crop. The toothpick-inoculation method used by us holds great promise for selecting resistant germplasm for melons and possibly for sesame, but other methodologies have to be devised for each individual crop.

Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies

Soybean is one of the most valuable agricultural crops in the world. Besides, this legume is constantly attacked by a wide range of pathogens (fungi, bacteria, viruses, and nematodes) compromising yield and increasing production costs. One of the major disease management strategies is the genetic resistance provided by single genes and quantitative trait loci (QTL). Identifying the genomic regions underlying the resistance against these pathogens on soybean is one of the first steps performed by molecular breeders. In the past, genetic mapping studies have been widely used to discover these genomic regions. However, over the last decade, advances in next-generation sequencing technologies and their subsequent cost decreasing led to the development of cost-effective approaches to high-throughput genotyping. Thus, genome-wide association studies applying thousands of SNPs in large sets composed of diverse soybean accessions have been successfully done. In this chapter, a comprehensive review of the majority of GWAS for soybean diseases published since this approach was developed is provided. Important diseases caused by Heterodera glycines, Phytophthora sojae, and Sclerotinia sclerotiorum have been the focus of the several GWAS. However, other bacterial and fungi diseases also have been targets of GWAS. As such, this GWAS summary can serve as a guide for future studies of these diseases. The protocol begins by describing several considerations about the pathogens and bringing different procedures of molecular characterization of them. Advice to choose the best isolate/race to maximize the discovery of multiple R genes or to directly map an effective R gene is provided. A summary of protocols, methods, and tools to phenotyping the soybean panel is given to several diseases. We also give details of options of DNA extraction protocols and genotyping methods, and we describe parameters of SNP quality to soybean data. Websites and their online tools to obtain genotypic and phenotypic data for thousands of soybean accessions are highlighted. Finally, we report several tricks and tips in Subheading 4, especially related to composing the soybean panel as well as generating and analyzing the phenotype data. We hope this protocol will be helpful to achieve GWAS success in identifying resistance genes on soybean.

Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens

Soybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application ( https://soyfungigcn.venanciogroup.uenf.br/ ) and an R/Shiny package ( https://github.com/almeidasilvaf/SoyFungiGCN ) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.

Genome-wide association of single nucleotide polymorphism loci and candidate genes for frogeye leaf spot (Cercospora sojina) resistance in soybean

BACKGROUND

Frogeye leaf spot (FLS) is a destructive fungal disease that affects soybean production. The most economical and effective strategy to control FLS is the use of resistant cultivars. However, the use of a limited number of resistant loci in FLS management will be countered by the emergence of new high-virulence Cercospora sojina races. Therefore, we identified quantitative trait loci (QTL) that control resistance to FLS and identified novel resistant genes using a genome-wide association study (GWAS) on 234 Chinese soybean cultivars.

RESULTS

A total of 30,890 single nucleotide polymorphism (SNP) markers were used to estimate linkage disequilibrium (LD) and population structure. The GWAS results showed four loci (p < 0.0001) distributed over chromosomes (Chr.) 5 and 20, that are significantly associated with FLS resistance. No previous studies have reported resistance loci in these regions. Subsequently, 45 genes in the two resistance-related haplotype blocks were annotated. Among them, Glyma20g31630 encoding pyruvate dehydrogenase (PDH), Glyma05g28980, which encodes mitogen-activated protein kinase 7 (MPK7), and Glyma20g31510, Glyma20g31520 encoding calcium-dependent protein kinase 4 (CDPK4) in the haplotype blocks deserves special attention.

CONCLUSIONS

This study showed that GWAS can be employed as an effective strategy for identifying disease resistance traits in soybean and narrowing SNPs and candidate genes. The prediction of candidate genes in the haplotype blocks identified by disease resistance loci can provide a useful reference to study systemic disease resistance.

Molecular interaction of charcoal rot pathogenesis in soybean: a complex interaction

Charcoal rot (CR) is a major disease of soybean, which is caused by Macrophomina phaseolina (Mp). Increasing temperatures and low rainfall in recent years have immensely benefitted the pathogen. Hence, the search for genetically acquired resistance to this pathogen is essential. The pathogen is a hemibiotroph, which germinates on the root surface and colonizes epidermal tissue. Several surface receptors initiate pathogenesis, followed by the secretion of various enzymes that provide entry to host tissue. Several enzymes and other converging cascades in the pathogen participate against host defensive responses. β-glucan of the fungal cell wall is recognized as MAMPs (microbe-associated molecular patterns) in plants, which trigger host immune responses. Kinase receptors, resistance, and pathogenesis-related genes correspond to host defense response. They work in conjunction with hormone-mediated defense pathway especially, the systemic acquired resistance, calcium-signaling, and production of phytoalexins. Due to its quantitative nature, limited QTLs have been identified in soybean for CR resistance. The present review attempts to provide a functional link between M. phaseolina pathogenicity and soybean responses. Elucidation of CR resistance responses would facilitate improved designing of breeding programs, and may help in the selection of corresponding genes to introgress CR resistant traits.

Effects of Charcoal Rot on Soybean Seed Composition in Soybean Genotypes That Differ in Charcoal Rot Resistance under Irrigated and Non-Irrigated Conditions

Charcoal rot is a major disease of soybean (Glycine max) caused by Macrophomina phaseolina and results in significant loss in yield and seed quality. The effects of charcoal rot on seed composition (seed protein, oil, and fatty acids), a component of seed quality, is not well understood. Therefore, the objective of this research was to investigate the impact of charcoal rot on seed protein, oil, and fatty acids in different soybean genotypes differing in their charcoal rot susceptibility under irrigated and non-irrigated conditions. Two field experiments were conducted in 2012 and 2013 in Jackson, TN, USA. Thirteen genotypes differing in charcoal rot resistance (moderately resistant and susceptible) were evaluated. Under non-irrigated conditions, moderately resistant genotypes showed either no change or increased protein and oleic acid but had lower linolenic acid. Under non-irrigated conditions, most of the susceptible genotypes showed lower protein and linolenic acid but higher oleic acid. Most of the moderately resistant genotypes had higher protein than susceptible genotypes under irrigated and non-irrigated conditions but lower oil than susceptible genotypes. The different responses among genotypes for protein, oil, oleic acid, and linolenic acid observed in each year may be due to both genotype tolerance to drought and environmental conditions, especially heat differences in each year (2012 was warmer than 2013). This research showed that the increases in protein and oleic acid and the decrease in linolenic acid may be a possible physiological mechanism underlying the plant's responses to the charcoal rot infection. This research further helps scientists understand the impact of irrigated and non-irrigated conditions on seed nutrition changes, using resistant and susceptible genotypes.

Cultivar Selection Is an Effective and Economic Strategy for Managing Charcoal Rot of Strawberry in Florida

Macrophomina phaseolina, the causal agent of charcoal rot, is a soilborne pathogen that affects strawberry crowns leading to plant wilt and collapse. Disease management involves a combination of physical, cultural, and chemical methods. Field trials were conducted for 10 consecutive Florida seasons (2010-11 to 2019-20) to determine the susceptibility of strawberry cultivars to charcoal rot and the effect of cultivar selection on disease and to estimate the economic impact of cultivar selection on disease management. Six cultivars grown commercially in Florida were chosen and grouped as highly susceptible (HS) ('Strawberry Festival' and 'Treasure'), susceptible (S) ('Florida Radiance' and 'Florida Beauty'), and moderately resistant (MR) (Sensation 'Florida127' and Winterstar 'FL05-107') according to their susceptibility levels. After a primary analysis of the individual trials, a network meta-analysis was conducted to estimate and compare the final disease incidence and the disease progress rate of each susceptibility group. The economic impact of charcoal rot on strawberry production and gross revenue was estimated based on plant production functions, weekly fruit prices, and disease progress over time with parameters obtained via the meta-analytical models. Disease incidence was reduced by 91.5 and 77.3%, respectively, when the MR and S cultivar groups were adopted instead of the HS group. There was a 62.5% reduction in the disease incidence when the MR group was used instead of the S group. Significant differences in disease progress rates were also observed when the MR and S groups were adopted instead of the HS group. Therefore, the adoption of more resistant cultivars is an effective strategy when incorporated into a charcoal rot integrated management program and can significantly impact growers' revenue by reducing disease incidence, preventing yield loss, and, consequently, minimizing economic losses.

Meta-GWAS for quantitative trait loci identification in soybean

We report a meta-Genome Wide Association Study involving 73 published studies in soybean [Glycine max L. (Merr.)] covering 17,556 unique accessions, with improved statistical power for robust detection of loci associated with a broad range of traits. De novo GWAS and meta-analysis were conducted for composition traits including fatty acid and amino acid composition traits, disease resistance traits, and agronomic traits including seed yield, plant height, stem lodging, seed weight, seed mottling, seed quality, flowering timing, and pod shattering. To examine differences in detectability and test statistical power between single- and multi-environment GWAS, comparison of meta-GWAS results to those from the constituent experiments were performed. Using meta-GWAS analysis and the analysis of individual studies, we report 483 peaks at 393 unique loci. Using stringent criteria to detect significant marker-trait associations, 59 candidate genes were identified, including 17 agronomic traits loci, 19 for seed-related traits, and 33 for disease reaction traits. This study identified potentially valuable candidate genes that affect multiple traits. The success in narrowing down the genomic region for some loci through overlapping mapping results of multiple studies is a promising avenue for community-based studies and plant breeding applications.

Macrophomina phaseolina : General Characteristics of Pathogenicity and Methods of Control

Macrophomina phaseolina is a generalist soil-borne fungus present all over the world. It cause diseases such as stem and root rot, charcoal rot and seedling blight. Under high temperatures and low soil moisture, this fungus can cause substantial yield losses in crops such as soybean, sorghum and groundnut. The wide host range and high persistence of M. phaseolina in soil as microsclerotia make disease control challenging. Therefore, understanding the basis of the pathogenicity mechanisms as well as its interactions with host plants is crucial for controlling the pathogen. In this work, we aim to describe the general characteristics and pathogenicity mechanisms of M. phaseolina, as well as the hosts defense response. We also review the current methods and most promising forecoming ones to reach a responsible control of the pathogen, with minimal impacts to the environment and natural resources.

Secretory Peptides as Bullets: Effector Peptides from Pathogens against Antimicrobial Peptides from Soybean

Soybean is an important crop as both human food and animal feed. However, the yield of soybean is heavily impacted by biotic stresses including insect attack and pathogen infection. Insect bites usually make the plants vulnerable to pathogen infection, which causes diseases. Fungi, oomycetes, bacteria, viruses, and nematodes are major soybean pathogens. The infection by pathogens and the defenses mounted by soybean are an interactive and dynamic process. Using fungi, oomycetes, and bacteria as examples, we will discuss the recognition of pathogens by soybean at the molecular level. In this review, we will discuss both the secretory peptides for soybean plant infection and those for pathogen inhibition. Pathogenic secretory peptides and peptides secreted by soybean and its associated microbes will be included. We will also explore the possible use of externally applied antimicrobial peptides identical to those secreted by soybean and its associated microbes as biopesticides.

Identification of New Biocontrol Agent against Charcoal Rot Disease Caused by Macrophomina phaseolina in Soybean (Glycine max L.)

Controlling agricultural pests using suitable biocontrol agents has been considered the best strategy for sustainable agriculture. Charcoal rot caused by a necrotrophic fungus Macrophomina phaseolina is responsible for a 30–50% annual reduction in soybean yield worldwide. Little is known about the role of Bacillus clausii in reducing charcoal rot disease severity in the soybean crop. In this study, we investigated plant growth promoting and antagonistic potential of Pseudomonas putida (MT604992) and Bacillus clausii (MT604989) against charcoal rot disease incidence in soybean. Among twenty bacteria isolated from soil and water samples of two different hot springs of Gilgit-Baltistan, Pakistan, 80% were siderophore positive; 65% were hydrogen cyanide (HCN) positive; 55%, 30%, and 75% were phosphate, potassium, and zinc solubilizers, respectively. Based on higher antagonistic activities and plant growth promoting traits five strains were selected for in vitro screening. Out of all tested strains, Pseudomonas putida and Bacillus clausii showed a significant increase in germination, growth, and disease suppression in soybean. These strains produced a pronounced increase in relative water content, photosynthetic pigments, membrane stability, proline, antioxidant enzymes status, phytohormones content (Salicylic acid, and Jasmonic acid), and disease suppression in comparison to control plants. Bacillus clausii mitigated the disease by 97% with a marked increase in the proline content (73% and 89%), superoxide dismutase (356% and 208%), peroxidase (439% and 138.6%), catalase (255.8% and 80.8%), and ascorbate peroxidase (228% and 90%) activities in shoots and roots, respectively. Infected plants showed an increase in salicylic acid and jasmonic acid content which was further increased with the application of the selected strains to increase resistance against pathogens. To our knowledge, this is the first study showing a rise in salicylic acid and jasmonic acid in Macrophomina phaseolina infected plants. These two strains are suggested as a cost-effective, eco-friendly, and sustainable alternative to chemical fungicides. However, there is a need to explore the field testing and molecular mechanisms leading to disease suppression by these strains.

Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters

We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications = 14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.

Genetic Control and Geo-Climate Adaptation of Pod Dehiscence Provide Novel Insights into Soybean Domestication

Loss of pod dehiscence was a key step in soybean [Glycine max (L.) Merr.] domestication. Genome-wide association analysis for soybean shattering identified loci harboring Pdh1, NST1A and SHAT1-5 Pairwise epistatic interactions were observed, and the dehiscent Pdh1 overcomes resistance conferred by NST1A or SHAT1-5 locus. Further candidate gene association analysis identified a nonsense mutation in NST1A associated with pod dehiscence. Geographic analysis showed that in Northeast China (NEC), indehiscence at both Pdh1 and NST1A were required in cultivated soybean, while indehiscent Pdh1 alone is capable of preventing shattering in Huang-Huai-Hai (HHH) valleys. Indehiscent Pdh1 allele was only identified in wild soybean (Glycine soja L.) accession from HHH valleys suggesting that it may have originated in this region. No specific indehiscence was required in Southern China. Geo-climatic investigation revealed strong correlation between relative humidity and frequency of indehiscent Pdh1 across China. This study demonstrates that epistatic interaction between Pdh1 and NST1A fulfills a pivotal role in determining the level of resistance against pod dehiscence, and humidity shapes the distribution of indehiscent alleles. Our results give further evidence to the hypothesis that HHH valleys was at least one of the origin centers of cultivated soybean.

Deconstructing the genetic architecture of iron deficiency chlorosis in soybean using genome-wide approaches

BACKGROUND

Iron (Fe) is an essential micronutrient for plant growth and development. Iron deficiency chlorosis (IDC), caused by calcareous soils or high soil pH, can limit iron availability, negatively affecting soybean (Glycine max) yield. This study leverages genome-wide association study (GWAS) and a genome-wide epistatic study (GWES) with previous gene expression studies to identify regions of the soybean genome important in iron deficiency tolerance.

RESULTS

A GWAS and a GWES were performed using 460 diverse soybean PI lines from 27 countries, in field and hydroponic iron stress conditions, using more than 36,000 single nucleotide polymorphism (SNP) markers. Combining this approach with available RNA-sequencing data identified significant markers, genomic regions, and novel genes associated with or responding to iron deficiency. Sixty-nine genomic regions associated with IDC tolerance were identified across 19 chromosomes via the GWAS, including the major-effect quantitative trait locus (QTL) on chromosome Gm03. Cluster analysis of significant SNPs in this region deconstructed this historically prominent QTL into four distinct linkage blocks, enabling the identification of multiple candidate genes for iron chlorosis tolerance. The complementary GWES identified SNPs in this region interacting with nine other genomic regions, providing the first evidence of epistatic interactions impacting iron deficiency tolerance.

CONCLUSIONS

This study demonstrates that integrating cutting edge genome wide association (GWA), genome wide epistasis (GWE), and gene expression studies is a powerful strategy to identify novel iron tolerance QTL and candidate loci from diverse germplasm. Crops, unlike model species, have undergone selection for thousands of years, constraining and/or enhancing stress responses. Leveraging genomics-enabled approaches to study these adaptations is essential for future crop improvement.

A novel Arabidopsis pathosystem reveals cooperation of multiple hormonal response-pathways in host resistance against the global crop destroyer Macrophomina phaseolina

Dubbed as a "global destroyer of crops", the soil-borne fungus Macrophomina phaseolina (Mp) infects more than 500 plant species including many economically important cash crops. Host defenses against infection by this pathogen are poorly understood. We established interactions between Mp and Arabidopsis thaliana (Arabidopsis) as a model system to quantitatively assess host factors affecting the outcome of Mp infections. Using agar plate-based infection assays with different Arabidopsis genotypes, we found signaling mechanisms dependent on the plant hormones ethylene, jasmonic acid and salicylic acid to control host defense against this pathogen. By profiling host transcripts in Mp-infected roots of the wild-type Arabidopsis accession Col-0 and ein2/jar1, an ethylene/jasmonic acid-signaling deficient mutant that exhibits enhanced susceptibility to this pathogen, we identified hundreds of genes potentially contributing to a diverse array of defense responses, which seem coordinated by complex interplay between multiple hormonal response-pathways. Our results establish Mp/Arabidopsis interactions as a useful model pathosystem, allowing for application of the vast genomics-related resources of this versatile model plant to the systematic investigation of previously understudied host defenses against a major crop plant pathogen.

Plant disease identification using explainable 3D deep learning on hyperspectral images

BACKGROUND

Hyperspectral imaging is emerging as a promising approach for plant disease identification. The large and possibly redundant information contained in hyperspectral data cubes makes deep learning based identification of plant diseases a natural fit. Here, we deploy a novel 3D deep convolutional neural network (DCNN) that directly assimilates the hyperspectral data. Furthermore, we interrogate the learnt model to produce physiologically meaningful explanations. We focus on an economically important disease, charcoal rot, which is a soil borne fungal disease that affects the yield of soybean crops worldwide.

RESULTS

Based on hyperspectral imaging of inoculated and mock-inoculated stem images, our 3D DCNN has a classification accuracy of 95.73% and an infected class F1 score of 0.87. Using the concept of a saliency map, we visualize the most sensitive pixel locations, and show that the spatial regions with visible disease symptoms are overwhelmingly chosen by the model for classification. We also find that the most sensitive wavelengths used by the model for classification are in the near infrared region (NIR), which is also the commonly used spectral range for determining the vegetative health of a plant.

CONCLUSION

The use of an explainable deep learning model not only provides high accuracy, but also provides physiological insight into model predictions, thus generating confidence in model predictions. These explained predictions lend themselves for eventual use in precision agriculture and research application using automated phenotyping platforms.

Genome-wide associations and epistatic interactions for internode number, plant height, seed weight and seed yield in soybean

BACKGROUND

Breeding programs benefit from information about marker-trait associations for many traits, whether the goal is to place those traits under active selection or to maintain them through background selection. Association studies are also important for identifying accessions bearing potentially useful alleles by characterizing marker-trait associations and allelic states across germplasm collections. This study reports the results of a genome-wide association study and evaluation of epistatic interactions for four agronomic and seed-related traits in soybean.

RESULTS

Using 419 diverse soybean accessions, together with genotyping data from the SoySNP50K Illumina Infinium BeadChip, we identified marker-trait associations for internode number (IN), plant height (PH), seed weight (SW), and seed yield per plant (SYP). We conducted a genome-wide epistatic study (GWES), identifying candidate genes that show evidence of SNP-SNP interactions. Although these candidate genes will require further experimental validation, several appear to be involved in developmental processes related to the respective traits. For IN and PH, these include the Dt1 determinacy locus (a soybean meristematic transcription factor), as well as a pectinesterase gene and a squamosa promoter binding gene that in other plants are involved in cell elongation and the vegetative-to-reproductive transition, respectively. For SW, candidate genes include an ortholog of the AP2 gene, which in other species is involved in maintaining seed size, embryo size, seed weight and seed yield. Another SW candidate gene is a histidine phosphotransfer protein - orthologs of which are involved in cytokinin-mediated seed weight regulating pathways. The SYP association loci overlap with regions reported in previous QTL studies to be involved in seed yield.

CONCLUSIONS

This study further confirms the utility of GWAS and GWES approaches for identifying marker-trait associations and interactions within a diverse germplasm collection.

Association Analysis of Charcoal Rot Disease Resistance in Soybean

In this research, the relationships among the 31 microsatellite markers with charcoal rot disease resistance related indices in 130 different soybean cultivars and lines were evaluated using association analysis based on the general linear model (GLM) and the mixed linear model (MLM) by the Structure and Tassel software. The results of microsatellite markers showed that the genetic structure of the studied population has three subpopulations (K=3) which the results of bar plat also confirmed it. In association analysis based on GLM and MLM models, 31 and 35 loci showed significant relationships with the evaluated traits, respectively, and confirmed considerable variation of the studied traits. The identified markers related to some of the studied traits were the same which can probably be due to pleiotropic effects or tight linkage among the genomic regions controlling these traits. Some of these relationships were including, the relationship between Sat_252 marker with amount of charcoal rot disease, Satt359, Satt190 and Sat_169 markers with number of microsclerota in stem, amount of charcoal rot disease and severity of charcoal rot disease, Sat_416 marker with number of microsclerota in stem and amount of charcoal rot disease and the Satt460 marker with number of microsclerota in stem and severity of charcoal rot disease. The results of this research and the linked microsatellite markers with the charcoal rot disease-related characteristics can be used to identify the suitable parents and to improve the soybean population in future breeding programs.

Hyperspectral band selection using genetic algorithm and support vector machines for early identification of charcoal rot disease in soybean stems

BACKGROUND

Charcoal rot is a fungal disease that thrives in warm dry conditions and affects the yield of soybeans and other important agronomic crops worldwide. There is a need for robust, automatic and consistent early detection and quantification of disease symptoms which are important in breeding programs for the development of improved cultivars and in crop production for the implementation of disease control measures for yield protection. Current methods of plant disease phenotyping are predominantly visual and hence are slow and prone to human error and variation. There has been increasing interest in hyperspectral imaging applications for early detection of disease symptoms. However, the high dimensionality of hyperspectral data makes it very important to have an efficient analysis pipeline in place for the identification of disease so that effective crop management decisions can be made. The focus of this work is to determine the minimal number of most effective hyperspectral wavebands that can distinguish between healthy and diseased soybean stem specimens early on in the growing season for proper management of the disease. 111 hyperspectral data cubes representing healthy and infected stems were captured at 3, 6, 9, 12, and 15 days after inoculation. We utilized inoculated and control specimens from 4 different genotypes. Each hyperspectral image was captured at 240 different wavelengths in the range of 383-1032 nm. We formulated the identification of best waveband combination from 240 wavebands as an optimization problem. We used a combination of genetic algorithm as an optimizer and support vector machines as a classifier for the identification of maximally-effective waveband combination.

RESULTS

A binary classification between healthy and infected soybean stem samples using the selected six waveband combination (475.56, 548.91, 652.14, 516.31, 720.05, 915.64 nm) obtained a classification accuracy of 97% for the infected class. Furthermore, we achieved a classification accuracy of 90.91% for test samples from 3 days after inoculation using the selected six waveband combination.

CONCLUSIONS

The results demonstrated that these carefully-chosen wavebands are more informative than RGB images alone and enable early identification of charcoal rot infection in soybean. The selected wavebands could be used in a multispectral camera for remote identification of charcoal rot infection in soybean.

Harpin-inducible defense signaling components impair infection by the ascomycete Macrophomina phaseolina

Soybean (Glycine max) infection by the charcoal rot (CR) ascomycete Macrophomina phaseolina is enhanced by the soybean cyst nematode (SCN) Heterodera glycines. We hypothesized that G. max genetic lines impairing infection by M. phaseolina would also limit H. glycines parasitism, leading to resistance. As a part of this M. phaseolina resistance process, the genetic line would express defense genes already proven to impair nematode parasitism. Using G. max[DT97-4290/PI 642055], exhibiting partial resistance to M. phaseolina, experiments show the genetic line also impairs H. glycines parasitism. Furthermore, comparative studies show G. max[DT97-4290/PI 642055] exhibits induced expression of the effector triggered immunity (ETI) gene NON-RACE SPECIFIC DISEASE RESISTANCE 1/HARPIN INDUCED1 (NDR1/HIN1) that functions in defense to H. glycines as compared to the H. glycines and M. phaseolina susceptible line G. max[Williams 82/PI 518671]. Other defense genes that are induced in G. max[DT97-4290/PI 642055] include the pathogen associated molecular pattern (PAMP) triggered immunity (PTI) genes ENHANCED DISEASE SUSCEPTIBILITY1 (EDS1), NONEXPRESSOR OF PR1 (NPR1) and TGA2. These observations link G. max defense processes that impede H. glycines parasitism to also potentially function toward impairing M. phaseolina pathogenicity. Testing this hypothesis, G. max[Williams 82/PI 518671] genetically engineered to experimentally induce GmNDR1-1, EDS1-2, NPR1-2 and TGA2-1 expression leads to impaired M. phaseolina pathogenicity. In contrast, G. max[DT97-4290/PI 642055] engineered to experimentally suppress the expression of GmNDR1-1, EDS1-2, NPR1-2 and TGA2-1 by RNA interference (RNAi) enhances M. phaseolina pathogenicity. The results show components of PTI and ETI impair both nematode and M. phaseolina pathogenicity.