Soybean diseases continue to be a major limitation to sustainable soybean production in the US. It is estimated that the average annual yield losses due to soybean diseases in the United States are approximately 11%, which translates to more than $4 billion in revenue loss per year. In order to protect soybeans from damages from the destructive pathogens, it is important to identify new sources of disease (R) resistance genes and deploy desirable R genes into elite soybean cultivars. This project uses a technique called Ren-Seq (Resistance Gene Enriched Sequencing), which can specifically capture, enrich, and sequence resistance genes, primarily NBS-LRR genes, to accelerate disease resistance gene discovery. This approach, combined with genetic mapping and gene expression data, allows i) assembling all NBS-LRR genes without a need to sequence the entire genome; ii) finding molecular markers that allow fine mapping of disease resistance genes; iii) pinpointing candidate R genes; iv) designing R gene-based molecular markers for precise R gene selection in breeding – all at affordable costs. We proposed five specific objectives to achoive the overall goal defined in this project.

Objective 1. Development of a high-quality RenSeq platform for the soybean research community. Objective 2. Sequencing and assembly of NBS-LRR gene clusters in major soybean lines carrying resistance to prevalent soybean pathogens in the Midwest region. Objective 3. Analysis of R gene expression and responses to various soybean pathogens. Objective 4. Evaluation of resistance to various pathogens and mapping of major R genes and QTL. Objective 5. Development of candidate R-gene-based molecular markers for precision breeding.

1) Assembled and mapped NBS-LRR gene clusters from 96 (or 48) or soybean cultivars carrying resistance to the targeted soybean diseases; construction of a pan-NLRome.
2) Chromosomal locations and candidate genes for 6 major disease resistance QTLs or qualitative loci. Detailed spectra of resistance of these QTL or qualitative loci
3) Genome-wide NBS-LRR gene expression patterns in 6-12 varieties in response to infection of targeted pathogens in soybean lines carrying major disease resistance QTL or genes.
4) A set of 2-3 candidate R genes of NBS-LRR type underlying specific resistances to different pathogens/strains and DNA markers for precise selection of these R genes.

Updated April 28, 2025:
This semi-annual report outlines the progress made for the FY25 project, which commenced on October 1, 2024. The FY25 project marks the 3rd year of a three-year project aiming to explore, apply, and optimize RenSeq technology for accelerated identification of candidate R genes conferring resistance to various soybean pathogens that are prevalent in the Midwest region, and to expedite the development of disease-resistant soybean cultivars through precise R gene selection. We proposed five specific objectives to achieve these goals, some of which are consequential and others ongoing. Objectives 1 and 2 were fully achieved in FY 23 and FY24. In this report, we focus on progresses made on Objectives 3-5, which are continuous and proposed to be completed by the end of the whole project.

Objective 3: Analysis of R Gene Expression and Responses to Various Soybean Pathogens:

We have expanded gene expression analysis by including more soybean varieties with major QTLs conferring resistance to soybean pathogens including Phytophthora sojae and Phytophthora sojae, Phytophthora sansomeana, and frogeye leaf spot. These QTLs have been mapped to typical NLR (or R)-gene clusters and are likely to each be underlain by an NLR gene. Candidate Rps and Rpsan genes showing responses to respective pathogens have been pinpointed based on gene expression data. Some of these candidate genes have been further challenged by multiple pathogen races/isolates. Currently we are mapping the RNA-seq data to 26 reference soybean genomes representing genetic diversity as well as the assembled genomes from the donor lines of the resistance QTLs. We hope to be able to pinpoint the candidate genes for Rpsan1, Rps12, 13, 14, 15 and 16 through efforts from the Ma, Bhattacharyya, Wang, and Lin labs. A major QTL underlying resistance to Fusarium graminearum has been identified by Dr. Cai lab. Nevertheless, this QTL was not located in an NLR-gene cluster and thus we have decided to identify non-NLR genes responsive to infection with the pathogen, hoping to be able to find candidate gene (s) responsible for the resistance or genes involved in genetic pathways underlying the resistance. Dr. Lorenz lab initiated a gene expression experiment using Minsoy and Noir1 to help guide us towards candidate genes in a previously mapped QTL region on chromosome 7. Four biological replicates of each soybean genotype in a white mold inoculation treatment versus control were set up. The plants are currently growing and awaiting inoculation, followed by tissued collection for RNA extraction and analysis. PI Ma continues coordinating the efforts on analyses of gene expression and identification of candidate genes.

Objective 4: Evaluation of Resistance to Various Pathogens and Mapping of Major R Genes and QTL:

These are continuous efforts being made by all participating labs in this project. Different labs started evaluation of resistance in parental lines, development of QTL mapping populations, and QTL mapping and fine mapping at different times; nevertheless, all have been mapping satisfactory progresses.

- Co-PIs Dechun Wang at Michigan State University and Feng Lin at University of Missouri have fine-mapped Rpsan1 and identified candidate genes for Rpssan1 using RNA-seq data. To pinpoint Rpsan1, larger mapping population composed of ~1,300 lines has veen developed in the field in the 2024 field season and ~70 markers were developed for finer mapping of the candidate gene. Dr. Wang lab has also developed a mapping population for identification of gene(s) conferring resistance to frogeye leaf spot (Cercospora sojina). - Co-PD Feng Lin developed F4-derived mapping populations each composed of >180 progeny lines for dissecting Stink Bug resistance and Cercospora Leaf Blight resistance, and has started gene mapping in 2025. In addition, Dr. Lin lab found that PI 594527 shows resistance to both P. sojae and P. sansomeana and made numerous attempts to cross this line with several breeding lines, but was only successful with only one breeding lines due to the late maturity group of this PI line (MG IX).

- Co-PI Madan Bhattacharyya at Iowa State has made significant progress on mapping novel Rps genes. The two Rps genes, Rps12 and Rps13 were mapped to the Rps4/6 region located in the southern arm of Chromosome 18. The Rps12 gene was mapped to a locus, close to Rps 4, 6 and 13 loci. It is not established whether the Rps 4, 6 and 13 genes are allelic or tightly linked genes. To determine if Rps6 and Rps13 are allelic, we have been investigating the segregants generated from the cross between L89-1581 (Rps6) and PI399036 (Rps12Rps13). We studied 1,074 segregants for the recombination events between two indel markers that include the Rps6/12/13 region; and identified 358 recombinants. We identified 73 genotypes with single breakpoint and 33 recombinants with double breakpoints. We observed 182 recombinants with more than two break points which most likely originated from experimental artifacts. We are currently revisiting the SNP panel to understand the reason behind such an anomaly. We have reported earlier the development of the Rps6 contig by generating long read sequences through the Oxford Nanopore Technologies. This contig is expected to shed light on the structural variation in the Rps6/12/13 region. We observed considerable variation in seed yield (seed number/plant) among the heterozygous plants and among the recombinant individuals. We have gained evidence suggesting that recombination in the Rps6/12/13 region affects seed yield due to novel gene actions.

- Dr. Aaron Lorenz has made four crosses for mapping of wild mold resistance QTLs and five crosses for mapping of Brown Stem Rot resistance QTLs during this reporting period. Additionally, Dr. Lorenz lab screened our latest advanced breeding lines for resistance to two races of brown stem rot and identified several advanced breeding lines show some strong resistance to both races. These lines can be used as future breeding parents to create new cultivars, and new genetic mapping resources.

- Co-PI Guohong Cai at USDA-ARS has identified major QTL underlying Fusarium graminearum resistance and evaluated the levels of resistance of the patental lines and some of the progeny lines.

- Co-PI Carrie Miranda has mapping populations for white mold and brown stem rot, and obtained F3 seeds. It is anticipated to receive F5 seeds in the fall of 2025 and then start phenotyping in collaboration with the NDSU soybean pathologist immediately.

Objective 5: Development of Candidate R-Gene-Based Molecular Markers for Precision Breeding
This is an ongoing and continuous effort at different stages of breeding for various diseases in different states. Past efforts focused on known genes. Our goal is to integrate novel, more effective R genes into elite soybean varieties in public breeding programs in these collaborating states. Lorenz lab has created and advanced four new breeding populations with the Rps6 gene, known to confer good resistance to most of the isolates in Minnesota and are developing resistant soybean lines with markers linked to this gene. Despite the effectiveness of this gene in resistance to Phytophthora, it is seldomly used in commercial breeding and mostly unavailable in current commercial cultivars. The four new breeding populations developed by the Lorenz lab were advanced to F2 and F4 populations in the winter nursery, and will be planted for another generation of advancement this coming summer. In addition, integration of Rps11 in elite soybean breeding lines has been initiated by all participating breeding programs. The females used for mapping population development by the Miranda lab are high yield North Dakota lines, and it is thus very likely that highly-yielding and resistant progeny lines will be developed during the gene discovery process.

Publications:
C Detranaltes, C Quigley, Q Song, J Ma, G Cai, 2025. A Novel Quantitative Trait Locus (QTL) Reduces Fusarium graminearum Infection in Glycine max Seedlings. Phytopathology.

Updated November 18, 2025:
This report outlines the progress made for the FY25 project, which started on October 1, 2024, and has been no-cost extended to March 31, 2026. The FY25 project is the 3rd year of a three-year project, aiming to explore, apply, and optimize RenSeq [disease resistance (R) gene enrichment sequencing] technology for accelerated identification of candidate genes conferring resistance to a variety of soybean pathogens prevalent in the Midwest region. This project is expected to provide novel resources of disease resistances and expedite the development of disease-resistant soybean cultivars through R gene-based precision selection. We proposed five specific objectives to achieve our research goals, some of which are consequential and others ongoing. As we mentioned in the mid-year report, Objectives 1 and 2 were fully achieved in previous years, while Objectives 3-5 are continuous and will be fully completed by the end of the whole project. Below summarizes the updates we have had on the objectives 3-5 since the mid-year report. Bhattacharyya and Ma are mainly working on resistance to Phytophthora sojae. Wang and Lin labs are mainly focusing on resistance to Phytophthora sansomeana and frogeye leaf spot. Cai lab mainly focuses on resistance to frogeye leaf spot and Fusarium graminearum. Lorenz and Miranda labs are mainly working on resistance to wild mold. In addition, Ma lab focuses on validation of some R genes for a particular resistance. All labs have made great efforts to advance genetic materials for QTL mapping and breeding lines in the field in 2025. PI Ma continues coordinating the efforts on analyses of gene expression and identification of candidate genes.

Objective 3: Analysis of R Gene Expression and Responses to Various Soybean Pathogens:

After analyzing gene expression in soybean varieties conferring resistance to soybean pathogens Phytophthora sojae and Phytophthora sansomeana, frogeye leaf spot, we have been conducting similar analysis in soybean varieties carrying resistance to Fusarium graminearum and wild mold. The QTLs in these varieties have been anchored to R gene clusters on specific chromosomal regions, and combination of this information with R gene expression analysis have pinpointed several genes as candidates for disease resistance to Phytophthora sojae and Phytophthora sansomeana. Genes conferring resistance to Fusarium graminearum and wild mold are likely to be controlled by non-typical R genes.

Our team has been re-evaluating these varieties with corresponding pathogens and producing new gene expression data to further examine the candidate genes for Rpsan1, Rps12, Rps13, Rps14, Rps15 and Rps16. We are in the process of gene expression analysis that may be able to detect candidate genes in the major QTL conferring quantitative resistance to Fusarium graminearum. Minsoy and Noir1, were used for gene expression analysis for wild mold resistance, with four biological replicates of each soybean genotype in a white mold inoculation treatment versus control. The plants inoculated with the wild mold pathogen were collected for RNA isolation, and the RNA samples have been processed for RNA-sequencing. We anticipate getting new gene expression data in three weeks from now.

Objective 4: Evaluation of Resistance to Various Pathogens and Mapping of Major R Genes and QTL:

All PIs have been making continuous effects on evaluation of novel resistances to specific pathogens, construction of new populations for genetics analysis, and/or mapping of major R genes or QTLs.

Wang lab at Michigan State University and Lin Lab at University of Missouri have mapped candidate genes for Rpssan1 in a chromosome region in the previous years and developed a large mapping population as well as a set of molecular markers for finer-scale mapping of Rpssan1. In addition, Wang and Lin labs have developed a mapping population for identification of gene(s) conferring resistance to frogeye leaf spot. Lin further advanced F4-derived mapping populations for an additional generation in the field for dissecting Stink Bug resistance and Cercospora Leaf Blight resistance and has made progress on initial QTL mapping. In addition, Dr. Lin lab found that PI 594527 shows resistance to both P. sojae and P. sansomeana and obtained seeds from a cross between this line and an elite breeding line developed in his program.

Bhattacharyya lab at Iowa State has fine mapped Rps12 and Rps13 to chromosome 18, loosely linked to Rps 4, 6 and 13 loci, and conducted allelic test to determine whether these genes are distinct loci or different alleles of a same gene locus. Hundreds of recombinant lines have been genotyped with a panel of SNPs from progeny derived from crosses between varieties carrying these genes. Parental lines have been sequenced using a long-read sequencing platform provided by the Oxford Nanopore Technologies. Our analysis has revealed considerable variation in the productivity of individual plants, as well as interactions among these genes, which affect seed yield per plant. Ma lab continued evaluation of the novel Rps gene progeny lines and selection of early maturity lines for introgression of the novel Rps genes into representative breeding lines from each program.

Lorenz lab at Minnesota continued the construction of mapping populations for wild mold resistance QTLs and for Brown Stem Rot resistance QTL during this past soybean growing season, and continued evaluation of these lines carrying the resistance QTLs with additional pathogen isolates. Several advanced breeding lines showed strong resistance to these newly texted races and were used in breeding at Minnesota.

Cai lab at USDA-ARS have identified major QTL underlying Fusarium graminearum resistance and published the work in a peer-reviewed journal. Cai lab has also been testing the novel Rps genes using newly identified isolates in Indiana state.

Miranda lab at NDSU continued advancing mapping population for resistances to white mold and brown stem rot and received F5 seeds in the fall of 2025 for mapping.

Objective 5: Development of Candidate R-Gene-Based Molecular Markers for Precision Breeding
In this reporting period, Ma lab has advanced progeny lines carrying the novel Rps genes including Rps11, Rps14 and Rps15 but show early maturity, so that these lines can be used by all breeders in this project for introgression of these genes into their breeding lines. Markers for other disease resistance will be designed once candidate genes for a particular resistance are further validated. All labs have leveraged the funding from this project to enhance the gene discovery pipelines and/or breeding programs.

Updated May 3, 2026:
This is the final report of the FY25 project, the 3rd year of a three-year project, entitled SoyRenSeq: a novel approach for disease resistance gene discovery and application for soybean improvement. The central goals of this collaborative, multi-state, and multi-disciplinary project are to explore, apply, and optimize the RenSeq technology for accelerated identification of candidate disease resistance genes (so-called R genes) responsible for resistance to various soybean pathogens prevalent in the Mid-west region, and for accelerated development of disease-resistant soybean cultivars by precise R gene selection. Five specific objectives were proposed to achieve our whole project goals through FY23-FY25: 1) Development of a high-quality RenSeq platform for the soybean research community; Sequencing and assembly of NBS-LRR gene clusters in major soybean lines carrying resistance to prevalent soybean pathogens in the Midwest region; 3) Analysis of R gene expression and responses to various soybean pathogens; 4) Evaluation of resistance to various pathogens and mapping of major R genes and QTL; and 5) Development of candidate R-gene-based molecular markers for precision breeding. Objectives 1 and 2 were fully achieved in FY23 and FY24, while Objectives 3-5 were continuous and completed by the end of the whole project. This FY25 project was extended to March 31, 2026; thus, two semi-annual reports had been provided previously. Given that the extended period of this FY25 project overlaps with the first half year of the FY26 project, there were some common experiments conducted to achieve research goals defined in both projects. In this final report, we intended to keep concise in describing research activities conducted during the FY25 period, but present more detailed project results, deliverables, and key performance indicators through the activities made to achieve objectives 3-5 in the FY25 project, etc.

Activities to achieve objective 3 mainly focused on analyses of changes in expression levels of candidate disease resistance (R) genes in response to various pathogens. The expression level of gene refers to the relative abundance of its final products for a specific trait. In general, a gene responsible for resistance to a particular pathogen exhibit altered levels of expression upon infection by that pathogen. In other words, a structurally defined R genes showing changed expression level upon a pathogen infection is considered as a strong candidate for disease resistance. We performed this type of analyses, using a technique call qRT-PCR, to detect candidate genes for resistance to several pathogens, including Phytophthora sojae (PIs Ma and Bhattacharyya) and Phytophthora sansomeana (co-PIs Wang/Lin) causing Phytophthora root and stem rots, Fusarium graminearum (co-PI Cai) causing Fusarium root rot and seedling blight, as well as Sclerotinia sclerotiorum (co-PI Lorenz) causing white mold. Additionally, Lorenz lab have collected a set of plant tissues from plants inoculated and un-inoculated with Sclerotinia sclerotiorum, which allows genome-wide detection, using a technology called RNA-sequencing, of all genes whose expression levels respond to the pathogen to gain new insights into this important, but not-yet-well-understood disease - white mold. Lorenz and Ma lab plan to continue this effort through the FY26 SoyRenSeq II project. Ma, Wang, and Bhattacharyya labs further examined the expression patterns of candidate genes for Rpsan1, Rps12, Rps13, Rps14, Rps15 and Rps16, laying the foundation for design DNA markers for precise selection of these resistance genes.
Major deliverables from objective 3 include 1) Enhanced understanding of soybean plants’ responses to several destructive soybean pathogens that haven’t been well characterized previously; 2) Identified strong candidate R genes for resistance to those pathogens.

Activities to achieve objective 4 mainly focused on evaluation or re-evaluation of soybean resistance to several pathogens and genetic approach to further delimit the candidate disease resistance genes or QTL to smaller chromosomal regions. Co-PI Wang at Michigan State University and co-PI Lin at University of Missouri continued genetic mapping of candidate genes for Rpsan1 with a newly developed a large mapping population using a set of molecular markers for finer-scale mapping of Rpsan1. Wang and Lin labs also developed a mapping population for identification of gene(s) conferring resistance to frogeye leaf spot. Lin lab made crosses of Rps11 and Rps14 donor lines with five breeding lines chosen from his breeding program, separately. Lin further advanced F4-derived mapping populations for an additional generation in the field for dissecting Stink Bug resistance and Cercospora Leaf Blight resistance and has made progress on initial QTL mapping. Moreover, Lin lab found that PI 594527 shows resistance to both P. sojae and P. sansomeana and obtained seeds from a cross between this line and a breeding line in his program. In general, soybean genes conferring resistance to P. sojae does not carry resistance to P. sansomeana; thus, the identified dual resistances carried by PI 594527 provided a unique opportunity for further dissection of the dual resistances for both pathogens. Bhattacharyya lab fine mapped Rps12 and Rps13 to chromosome 18, loosely linked to Rps 4, 6 and 13 loci, and conducted allelic test to determine whether these genes are distinct loci or different alleles of a same gene locus. Hundreds of recombinant lines have been genotyped with a panel of SNPs from progeny derived from crosses between varieties carrying these genes. Parental lines have been sequenced using a long-read sequencing platform provided by the Oxford Nanopore Technologies. The analysis has revealed considerable variation in the productivity of individual plants, as well as interactions among these genes, which affect seed yield per plant. Lorenz lab continued development of genetic mapping population for wild mold resistance QTLs and for Brown Stem Rot resistance QTL during this past soybean growing season, and continued evaluation of these lines carrying the resistance QTLs with additional pathogen isolates. Several advanced breeding lines showed strong resistance to these newly texted races and were used in breeding at Minnesota. Ma lab coordinating with Lin lab assessed a gene-editing line and found it gas gained resistance to P. sansomeana. Ma lab coordinating with Cai lab assessed a gene-editing line and found it gas gained resistance to P. sansomeana. Cai lab at USDA-ARS identified major QTL underlying Fusarium graminearum resistance and published the work in a peer-reviewed journal. Additionally, Cai lab assessed gene-editing lines created by Ma lab for frogeye spot. Miranda lab at NDSU continued advancing mapping population for resistances to white mold and brown stem rot and received F5 seeds in the fall of 2025 for mapping.

Major deliverables from objective 4 include 1) Fine-mapped key resistance loci (Rpsan1, Rps12, Rps13) using large mapping populations, dense SNP markers, allelic tests, and long-read sequencing to resolve locus relationships and narrow candidate regions; 2) Developed and advanced multiple mapping populations for resistance to frogeye leaf spot, white mold, brown stem rot, wild mold, stink bug, and Cercospora leaf blight, with initial QTLs identified; 3) Identified novel resistance sources and genetic interactions, including dual resistance to P. sojae and P. sansomeana and yield-related interactions among resistance loci; 4) Validated resistance in gene-edited lines (notably for P. sansomeana) and evaluated edited materials for additional diseases such as frogeye leaf spot; 5) Discovered and published major QTL for F. graminearum resistance and identified advanced breeding lines with strong resistance to emerging pathogen races.

Activities to achieve objective 5 have been continued efforts over the years in these major breeding programs over the years. In this project, we particularly focused on newly identified and more effective genes and/or QTLs for resistance to the major pathogens identified in this project. Lorenz and Bhattacharyya labs have developed markers for Rps6. Ma and Bhattacharyya labs have developed DNA markers for Rps11, Rps 12, Rps13, and Rps15. In addition, Ma lab has been leveraging gene-expression data from the candidate gene for a particular pathogen to test potential linkage between gene-based markers and disease resistance gene/QTL. All labs have leveraged the funding from this project to enhance the gene discovery pipelines and/or breeding programs.

Major deliverables from objective 4 include 1) Created DNA markers for Rps6, Rps11, Rps12, Rps13, and Rps15 resistance genes; Identified and prioritized new, highly effective genes and quantitative trait loci (QTLs) for major pathogen resistance; 3 Leveraged gene-expression data from candidate genes.

Benefits to soybean producers: Soybean diseases cause approximately 11% annual yield losses across the US, making disease-resistant cultivars the most economical, environmentally friendly solution for producers. This project accelerates discovery of key resistance (R) genes and development of precise molecular markers that enable breeders to stack multiple R genes into elite soybean lines for broad-spectrum, durable protection against threats like sudden death syndrome, Phytophthora root rot, frogeye leaf spot, and others, and ultimately benefit soybean producers through reduced application fungicides and increased soybean yields. All labs trained either graduate students or postdoctoral scientists, as well as undergraduate students through this project.

Publications:
Detranaltes, C., Quigley, C., Song, Q., Ma, J. and Cai, G., 2025. Identification of a Quantitative Trait Locus on Chromosome 15 Conferring Resistance to Pythium irregulare in Soybean. PhytoFrontiers™, pp.PHYTOFR-05.
Detranaltes, C., Quigley, C., Song, Q., Ma, J. and Cai, G., 2025. A Novel Quantitative Trait Locus Reduces Fusarium graminearum Infection in Glycine max Seedlings. Phytopathology®, 115(6), pp.666-675.
Xu, Z., Chen, K., Medina-Culma, C., Lee, Y., Girma, G., Lorenz, A., Kurek, A., Cannon, S.B., An, Y. and Beavis, W., 2025. Synergetic Gene Networks Controlling Soybean Sudden Death Syndrome. CANVAS 2025.
Dangal, N.K., Ernat, E.M., Adee, E.A., Betts, A.K., Bish, M., Bissonnette, K.M., Bradley, C., Byamukama, E., Byrne, A.M., Chilvers, M.I. and Faske, T.R., … Wang, D.,m Wiggs, S.H., Yabwalo, D., and Muller, D.S. 2025. Soybean Seed Treatment Evaluation under Various Levels of Sudden Death Syndrome and Populations of Soybean Cyst Nematode. Plant Disease, (ja).

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This project focused on helping soybeans better resist major diseases by identifying and refining the genes that protect plants from infection and using that knowledge to improve breeding. Researchers studied how certain “resistance genes” behave when plants are attacked by pathogens to identify candidate genes that potentially can be used for protecting the plant. The team examined soybean responses to several damaging diseases, including root rots, seedling blight, and white mold, and also used broader genome-wide approaches to discover new genes involved in defense. At the same time, they created and analyzed large plant populations to narrow down where these resistance traits are located in the genome, making it easier to pinpoint the exact genes responsible. This work included developing new breeding populations, identifying regions linked to resistance for multiple diseases, and discovering unique cases such as a soybean line that can resist two different pathogens at once—something rarely seen and especially valuable for future breeding. The team also explored how different resistance genes interact with each other and how they may affect yield, which is important for ensuring that disease-resistant plants remain productive. Advanced tools, including gene editing and long-read DNA sequencing, were used to identify candidate genes and better understand genetic variation. Several gene-edited lines showed improved resistance, demonstrating the potential of precise genetic approaches. In addition, the researchers developed DNA markers, simple genetic “tags”, for key resistance genes so breeders can quickly identify and combine multiple protective traits into new soybean varieties. Altogether, the project delivered a clearer understanding of how soybeans defend themselves, identified strong candidate resistance genes, refined their genomic locations, and provided practical tools for breeding programs. These advances are expected to help develop soybean varieties with broader and more durable resistance to disease, reducing reliance on chemical treatments and improving yields for farmers. The project also supported training for students and early-career scientists, contributing to the next generation of agricultural research.

The utilization of soybean cultivars with durable resistance will reduce the use of harmful chemicals, which will create a higher profit margin for soybean farmers and a healthier environment overall. This project also provide excellent opportunity to train the next-generation researchers whose future endeavors would directly or indirectly contribute to farm profitability.