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 R genes conferring resistances 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 will help us achieve these goals: 1) Develop high-quality RenSeq platform for the soybean research community; 2) Sequence and assemble NBS-LRR gene clusters in major soybean lines carrying resistance to prevalent soybean pathogens in the Midwest region; 3) Analyze R gene expression and responses to various soybean pathogens; 4) Evaluate resistance to various pathogens and mapping of major R genes and QTL; Develop candidate R-gene-based molecular markers for precision breeding.

Objective 1. Development of a high-quality RenSeq platform for the soybean research community. It has been well known that the Williams 82 soybean reference genome includes only a fraction of genes within the natural soybean population. This is particularly true for the NBS-LRR genes. To ensure the SoyRenSeq platform to be developed in this project has desirable power in capturing NBS-LRR gene clusters in any soybean varieties, we will first extract all NBS-LRR gene clusters from the 26 representative wild and cultivated soybean genomes sequenced by long-read sequencing approach. Then we will identify the redundant and NBS-LRR gene unique cluster sequences. Finally, we will use the complete set of non-redundant NBS-LRR gene cluster sequences to design a set of biotinylated RNA baits through coordination with Arbor Bioscience.

Objective 2. Sequencing and assembly of NBS-LRR gene clusters in major soybean lines carrying resistance to prevalent soybean pathogens in the Midwest region. We will use Soy_myBait1.0 to enrich NBS-LRR gene cluster sequences from soybean lines each carrying resistance to a specific pathogen as well as soybean lines routinely used as susceptible parents for mapping population development. We anticipate most of the disease resistances targeted in this project are controlled by NBS-LRR genes and can be captured by SoyRenSeq, but some, particularly the resistances showing quantitative variation, are likely controlled by non-NBS-LRR genes. Nevertheless, the data generated from all the resistant lines as well as the susceptible lines would be valuable for understanding the origin and dynamic variation of NBS-LRR genes and for pinpointing candidate R genes in NBS-LRR gene clusters underlying race-specific resistances. The NBS-LRR gene cluster sequences will be selected for fragments larger than 3 kilobase pairs, and the resulting DNA samples will be multiplexed and sequenced using PacBio Sequel SMRT sequencing platform. The sequences generated by SMRT sequencing will be assembled, annotated, and then anchored to chromosomal regions.

Objective 3. Analysis of R gene expression and responses to various soybean pathogens. Plant R genes are generally responsive to pathogen infection and can be detected by profiling of gene expression – the process by which the information encoded in a gene is used to make RNA molecules (called transcripts) that code for proteins. We will detect genome-wide gene expression changes in responses to each specific pathogen using two RNA sequencing methods. We will use SoyRenBaits1.0 to enrich full-length NBS-LRR transcripts and then conduct Iso-Seq. To capture R genes that do not belong to the NBS-LRR gene family, we will conduct short-read RNA-seq. Finally, the expression of strong candidate R genes will be further measured by real-time quantitative PCR, a low-cost technique used to detect COVID-19.

Objective 4. Evaluation of resistance to various pathogens and mapping of major R genes and QTL. Our investigators in the six states each will tackle a single or multiple soybean diseases targeted in respective research programs. Briefly, PI Ma and co-PI Cai in Indiana will identify candidate genes for RpsUN1 and RpsUN2, and candidate genes for resistance against Fusarium graminearum, Pythium ultimum and Pythium irregulare, as well as a novel Rbs gene for brown stem resistance, Rcs3 for frogeye leaf spot resistance, and Rbs3 for brown stem rot resistance. Co-PI Bhattacharyya in Iowa will identify candidate genes for Rps6, Rps12, Rps13, and two additional novel Rps genes. Co-PIs Wang and Lin in Michigan will primarily focus on identification of candidates for Rpsan1 and a novel Rcs gene from PI 532464 for frogeye leaf spot resistance. Co-PIs Lorenz in Minnesota and Miranda in North Dakota will work on identification of QTL for white mold resistance and brown stem rot resistance. For resistance to a particular disease with chromosomal locations defined in NBS-LRR gene clusters, we may be able to directly pinpoint candidate genes by the SoyRenSeq approach. For resistance to a particular disease with a mapping population available, we will conduct fine mapping. For resistance to a particular disease without a mapping population or previous knowledge about chromosomal location, we will construct a mapping population. Due to the short duration of the project, we may only be able to validate 1-2 R genes, if pinpointed in the early stage of the project, through genetic transformation, although PI Ma’s lab has full capability for soybean transformation.

Objective 5. Development of candidate R-gene-based molecular markers for precision breeding. Once candidate R genes for specific pathogens are identified, we will design R- gene-based molecular markers and then validate their effectiveness by using the segregating mapping population. Such markers will be used for selection of the R genes in the breeding programs led by the soybean breeders in our team.

Assembled and mapped NBS-LRR gene cluster sequences from 48 soybean cultivars carrying resistance to the targeted soybean diseases.

Biparental populations, initial mapping, or fine mapping of R genes.

Genome-wide NBS-LRR gene expression patterns in 12 varieties (24 samples) in response to infection of targeted pathogens in soybean lines carrying major disease resistance QTL.

A few candidate R genes of NBS-LRR type underlying specific resistances to Phytophthora, frogeye leaf spot, or brown stem rot etc.

Update:
Objective 1. Development of a high-quality RenSeq platform for the soybean research community.
Progress made: This objective has been achieved. We designed myBaits Custom 60-80K kit based on NLR gene sequences from 27 high reference-quality soybean genomes used for construct the soybean pangenome as well as the latest version of the Williams 82 soybean reference genome. The ~80k baits are non-redundant and cover all NLR genes in the 30 genomes. As these genomes are highly diverse and serve as the backbone for the pan-genome and over 2,000 soybean accessions re-sequenced, theoretically, this set of NLR baits for NLR enrichment, followed by PacBio Sequel SMRT sequencing would capture not only NLRs in any soybean genomes, but also the intergenic regions in the NLR gene clusters, allowing assembly and mapping of all NLR genes for candidate R gene analysis.

Objective 2. Sequencing and assembly of NBS-LRR gene clusters in major soybean lines carrying resistance to prevalent soybean pathogens in the Midwest region.
Progress-made: We have used myBaits Custom 60-80K kit to enrich NLR genes in 96 soybean varieties being investigated by our project team across the Midwest region, using fundings from both FY23 (extended to March 31,2024) and FY24. These varieties include donor lines for both known genes/QTLs and unknown genes/QTLs for various soybean disease resistances such as resistance to aphis; resistance to brown stem rot; resistance to Cercospora leaf blight; Resistance to Frogeye leaf spot; Resistance to Fusarium graminarum; Resistance to Phytophthora sansomeana; Resistance to Phytophthora sojae; Resistance to Soybeaan Rust; Resistance to Stem Canker; Resistance to white mold etc. We also included several typical susceptible lines as controls for sequence comparison. We will start to analyze the RenSeq data from these varieties in the second half year of the FY24 period. The sequences generated by SMRT sequencing will be assembled, annotated, and then mapped to chromosomal regions in the context of the specific NLR gene clusters as well as the soybean pangenome.

Objective 3. Analysis of R gene expression and responses to various soybean pathogens.
Progress made: We have performed RNA-seq for a few soybean varieties resistant to phytophthora sojae to test the effectiveness for finding NLR genes responsive to the pathogen. Once the effectiveness is revealed/validated, we will choose representative varieties from the 96 RenSeq varieties for resistance to each specific pathogen for discovery of candidate genes responsive the respective pathogens. For RNA-seq data analysis, the assembled NLR sequences from specific soybean varieties will be used for evaluation of NLR gene expression in the same varieties. This couldn’t be done without NLR sequences are generated.

Objective 4. Evaluation of resistance to various pathogens and mapping of major R genes and QTL.
Progress made: Our collaborators in the 5 states have been performing QTL mapping to complement the RenSeq analysis for R gene discovery, marker development, and integration of resistance QTLs to elite varieties. Briefly, As attached in four separate word documents, Co-PIs Dechun Wang and Feng Lin at Michigan State University have developed mapping population to map Rpsan1, conferring resistance to P. sansomeana. Co-PI Madan Bhattacharyya at Iowa State has made significant progress on mapping of novel Rps genes. Dr. Aaron Lorenz has identified sources of resistance, collected seeds, and planned crosses for the summer of 2024. Co-PI Guohong Cai at USDA-ARS has made progress on QTL mapping on F. graminearum resistance. Co-PI Carrie Miranda has started to evaluate a set of soybean accessions for major disease resistances in NDSU. The efforts from all the co-PIs are being coordinated with the PI towards productive performance.

Objective 5. Development of candidate R-gene-based molecular markers for precision breeding.
Progress made: This is continuing efforts at different stages of breeding for different diseases in different states. The past efforts were made 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.

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Updated November 11, 2024:
This report outlines the progress of the FY24 SoyRenSeq project, which commenced on October 1, 2023, and received a no-cost extension until March 31, 2025. The project's primary goals are to explore, apply, and optimize RenSeq technology for accelerated identification of candidate R genes conferring resistance to various soybean pathogens 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. Below, we report on the progress made in each objective since the semi-annual report.

Objective 1: Development of a High-Quality RenSeq Platform for the Soybean Research Community
This objective has been fully achieved. We designed a myBaits Custom 60-80K kit based on NLR gene sequences from 27 high reference-quality soybean genomes used to construct the soybean pangenome, as well as the latest version of the Williams 82 soybean reference genome. The ~80k baits are non-redundant and cover all NLR genes in the 30 genomes. As these genomes are highly diverse and serve as the backbone for the pan-genome and over 2,000 re-sequenced soybean accessions, this set of NLR baits for NLR enrichment, followed by PacBio Sequel SMRT sequencing, theoretically captures not only NLRs in any soybean genome but also the intergenic regions in the NLR gene clusters. This allows for the assembly and mapping of all NLR genes for candidate R gene analysis. Recent data assembly and analysis indicate that nearly all NLR genes are captured using our SoyRenSeq platform.

Objective 2: Sequencing and Assembly of NBS-LRR Gene Clusters in Major Soybean Lines
We have used the myBaits Custom 60-80K kit to enrich NLR genes in 96 soybean varieties being investigated by our project team across the Midwest region, using funding from both FY23 (extended to March 31, 2024) and FY24. These varieties include donor lines for both known and unknown genes/QTLs for various soybean disease resistances, such as resistance to aphids, brown stem rot, Cercospora leaf blight, frogeye leaf spot, Fusarium graminearum, Phytophthora sansomeana, Phytophthora sojae, soybean rust, stem canker, and white mold. We also included several typical susceptible lines as controls for sequence comparison.

Assemblies of NLR genes from all 96 samples have been completed, and all NLR genes in the assembled contigs have been annotated. Based on comparisons with a few lines whose genomes have been assembled at the reference genome level, we conclude that nearly all NLR genes have been successfully captured by SoyRenSeq followed by PacBio sequencing. The assembled contigs from each of the 96 genomes with NLR genes are anchored to a corresponding reference genome chosen from the 27 soybean varieties used to build the soybean pangenome. Additionally, the contigs with previously mapped disease resistance loci have been identified, bringing us one step closer to pinpointing candidate gene(s) for each of the resistance loci.

Objective 3: Analysis of R Gene Expression and Responses to Various Soybean Pathogens
We have previously performed RNA-seq for a few soybean varieties resistant to Phytophthora sojae to test the effectiveness of finding NLR genes responsive to the pathogen. Our data demonstrated that 8-12 hours after inoculation of soybean plants with this pathogen, the Rps genes are upregulated at the highest levels. We have conducted several rounds of evaluation of a set of soybean lines possessing known Rps genes with several Phytophthora sojae strains, and the phenotypes are stable and as expected. We are ready to inoculate the soybean varieties with known Rps genes for RNA-sequencing analysis.

This will enable us to identify candidate genes in the assembled NLR sequences for each of the Rps loci previously mapped and those mapped through this project, including Rpsan1 conferring resistance to Phytophthora sansomeana (identified by co-PIs Dechun Wang and Feng Lin at the University of Michigan), and Rps12, 13, 15, and 16 (identified by co-PI Madan Bhattacharyya at Iowa State University). Recently, co-PI Guohong Cai and the PI have found a novel QTL underlying resistance to Fusarium graminearum. During the extended period, we will expand these tests using lines carrying resistance to additional pathogens.

Objective 4: Evaluation of Resistance to Various Pathogens and Mapping of Major R Genes and QTL
Our collaborators in the five states have been performing QTL mapping to complement the RenSeq analysis for R gene discovery, marker development, and integration of resistance QTLs into elite varieties, and have made satisfactory progress:
- Co-PIs Dechun Wang at Michigan State University have developed a large mapping population to fine-map Rpsan1 and have already identified a few candidate genes.
- Co-PI Madan Bhattacharyya at Iowa State has made significant progress on mapping novel Rps genes, including Rps12, 13, 15, and 16.
- Dr. Aaron Lorenz has identified sources of resistance and made crosses for the 2024 soybean growing season.
- Co-PI Guohong Cai at USDA-ARS has identified QTL underlying Fusarium graminearum resistance.
- Co-PI Carrie Miranda has started developing mapping populations for mapping major disease resistances at NDSU and candidate gene analysis.
- Co-PD Feng Lin at the University of Missouri has made crosses and developed mapping populations for dissecting Stink Bug resistance and Cercospora Leaf Blight resistance. These crosses were sent to the winter nursery in Puerto Rico for generation advancement until F4 derived populations, and we expect to have ~184 RILs for each population for gene mapping in early 2025.
- Co-PI Carrie Miranda has initiated some crosses between North Dakota materials and resistant lines in the greenhouse this year. The first F1 seeds were harvested and are being sent to our Costa Rica winter nursery this week. These lines will be advanced in Costa Rica until they reach the F5 stage and are returned to North Dakota for field testing.

Objective 5: Development of Candidate R-Gene-Based Molecular Markers for Precision Breeding
This is an ongoing 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.

View uploaded report

It is an urgent need to explore, apply, and optimize this game-changing technique for rapid discovery of R genes conferring resistance to prevalent soybean pathogens across the Mid-west region and for efficient deployment of new disease resistance genes into elite soybean cultivars towards more sustainable soybean protection and increased soybean profitability to the Midwestern soybean growers.