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.

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.

Deliverables in year 1:
• A SoyRenSeq platform for NBS-LRR gene capture and enrichment.
• Assembled and mapped NBS-LRR gene cluster sequences from 24 soybean cultivars carrying resistance to the targeted soybean diseases.
• Biparental soybean populations at different generations for mapping or fine mapping of R genes.
• Genome-wide NBS-LRR gene expression patterns in response to infection of targeted pathogens.
• A few candidate R genes of NBS-LRR type underlying specific resistances to Phytophthora, frogeye leaf spot, or brown stem rot.

Update:
In this period of the project, we focused on Objective 1, Development of a high-quality RenSeq platform for the soybean research community. We have re-annotated all NBS-LRR genes in ~30 high-quality genomes of diverse varieties including elite cultivars, landraces, and wild soybean accessions. We also conducted comparative genomics analysis for the NBS-LRR gene clusters to understand how NBS-LRR genes evolve over time. We found dramatic copy number and structural variations of NBS-LRR genes among different varieties. These analyses enhanced our understanding about the challenges and strategies for typical disease resistance(R) gene discovery, mapping, and isolation, we well as the importance of design of functional R gene-based molecular markers for marker-assisted selection of R genes in breeding. All the NBS-LRR gene sequences from the ~30 genomes have been extracted for design of a comprehensive set of baits for RenSeq.

Although subcontractors have just received funds to work on this project, they have made some progresses on screening and characterization of new sources of disease resistances and development of R gene mapping population as defined in Objective 4. Nevertheless, we anticipate a need for a 6-months no-cost extension. This would help the subcontractors to complete their research components defined in this project in year 1.

Update:
In the FY23 period (i.e., Year 1 of the 3-year project), our team has made satisfactory progresses on the proposed Objectives 1, 2, and 4, which are highlighted below. Objectives 3 and 5 were proposed to start in FY24 and FY25, thus there are no progresses have been made.

Objective 1. Development of a high-quality RenSeq platform for the soybean research community.

Progress made: This objective has been fully achieved. We have re-annotated all NBS-LRR (or NLR) genes from the 26 representative genomes used to establish the soybean pangenomes, as well as the reference genomes of Williams 82, ZH13, and a wild soybean accession. We annotated approximately 30-40 new NBS-LRR genes in each of these genomes, totaling 800-900 new NBS-LRR genes, which were not previously annotated but annotated through this project. Based on the entire set of NLR genes in these genomes, a set of RNA baits, composed of ~80,000 unique RNA sequences have been designed in coordination with Arbor Bioscience. These baits have been mapped back to the pangenomes and show 99,9% coverage of all NLR genes. So this set of baits would be able to enrich all NLRs in any soybean varieties. The NLR gene annotation has been deposited in a spreadsheet. The annotation, together with the bait information, will be available to the research community without any restriction.

Deliverables: Improved NLR gene annotation in the soybean pangenomes; A SoyRenSeq platform for NBS-LRR gene capture and enrichment.


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: A subset of resistant soybean lines from the co-PIs and the community have been collected, evaluated, and chosen for RenSeq in FY23. We spent much more time than originally anticipated coordinating with Arbor Bioscience for bait design, resulting in the set of SoyRenSeq baits that can maximally and specifically enrich NLRs from any soybean cultivars with lowest costs. We have signed a contract with Arbor Bioscience for processing 96 soybean varieties, from NLR enrichment and PacBio long-read sequencing. The FY23 budget will cover RenSeq of 48 samples and the FY24 budget will cover RenSeq of other 48 samples. The FY23 project has been extended to 03/31/24 without request for additional funds. All the 96 samples will be Ren-sequenced and assembled by the extended end date of the FY23 project.

Deliverables: a set 96 soybean cultivars carrying resistance to the targeted soybean diseases chosen for Ren-sequencing.


Objective 4. Evaluation of resistance to various pathogens and mapping of major R genes and QTL.

Progress made: Our team has made satisfactory progresses on this objective, ranging from cultivar evaluation for specific resistances, mapping population development, to genetic mapping of genes/QTLs underlying specific resistances. In particular, individual co-PIs have their respective foci on specific pathogens that are predominant in their states. In addition, co-PIs have been independently developing mapping populations for dissecting the genetic basis of the resistances, but will coordinate as a team to use the RenSeq approach to identify and clone major QTLs underlying resistances to specific pathogens.

Deliverables: Biparental populations, inheritance pattern of resistances, and initial mapping results.

Overall the project went well, and the non-cost extension will ensure that all objectives are fully achieved.

Updated May 9, 2024:
This is the final report of the 1st year (FY23) project, which started on October 01, 2022 and ended on March 31, 2024, after a 6-month non-cost extension period. Thus, this FY23 overlapped for 6 months with the 2nd year (FY24) project, which started on October 01, 2023. Some of the 1st and 2nd years’ samples for RenSeq were combined together to reduce the cost per sample. Consequently, the 1st year-end report unavoidably has some overlaps with the semi-annual report of the 2nd year project, which was submitted in early April 2024.

Objective 1. Development of a high-quality RenSeq platform for the soybean research community.
This objective was fully achieved in FY23. We designed myBaits Custom 60-80K kit based on all NLR genes re-annotated in 27 high quality (reference-level) soybean genomes used for constructing the cultivated and wild soybean pangenome as well as the latest version of the Williams 82 soybean reference genome assembled using PacBio long-read sequences. A poster focusing on the NLR gene reannotation and analysis was presented in the Purdue Center for Plant Biology and is attached in this report. The ~80k baits are non-redundant and cover all NLR genes in these genomes. As these genomes are highly diverse and served as the backbone for the pan-genome and as a representative subset of over 2,000 soybean genomes re-sequenced, we anticipate this set of baits 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 analyses.

Objective 2. Sequencing and assembly of NBS-LRR gene clusters in major soybean lines carrying resistance to prevalent soybean pathogens in the Midwest region.
To reduce the cost per sample for RenSeq, we combined 96 soybean varieties for RenSeq NLR gene enrichment with the 60-80K myBaits. These 96 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 Soybean Rust; Resistance to Stem Canker; Resistance to white mold etc. We also included several typical susceptible lines as controls for sequence comparison. The RenSeq data from these 96 samples have been generated and are ready for assembly, mapping to chromosomal regions in the context of the specific NLR gene clusters in the 96 individual genomes. As proposed, this objective will be fully achieved by the end of the FY24 project.

Objective 3. Analysis of R gene expression and responses to various soybean pathogens.
We adjusted the priority of the whole project by having more soybean varieties carrying a various resistances processed for RenSeq at a reduced rate of sequencing costs per sample, as a result, the analyses of R gene expression and responses to pathogens were shifted to the FY24 period. Nevertheless, 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 to 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. As we initially proposed, this objective will be fully achieved by the end of the FY25 project, so the progresses made in FY23 were a good start and on track.

Objective 4. Evaluation of resistance to various pathogens and mapping of major R genes and QTL.
This objective involves many different soybean varieties and various soybean pathogens, and different collaborators were at different stages of QTL mapping, marker development, and integration of resistance QTLs to elite varieties, and the efforts are continuous until the end of the FY25 project. Briefly, Co-PIs Dechun Wang and Feng Lin (who joined University of Missouri in January 2024) at Michigan State University/University of Missouri have developed mapping population to map Rpsan1 that confers resistance to P. sansomeana. A manuscript on mapping of Rpsan1 has been published in a peer-reviewed journal (Lin et al., Theor Appl Genet. 2024, 22;137(3):55). Co-PI Madan Bhattacharyya at Iowa State has made significant progress on mapping of novel Rps genes. More specifically, they had fine mapped Rps12 and Rps13. 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 and had one manuscript published in a peer-reviewed journal (Detranaltes et al., 2023, Agronomy, 13 (9), 2376) and has a second manuscript nearly ready for submission. 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. More recently, a QTL conferring resistance to leafhopper has been identified with partial support from this project (Wang et al. 2024, Nature Genetics)

Objective 5. Development of candidate R-gene-based molecular markers for precision breeding.
Markers linked to a few disease-resistant QTLs including Rpsan1, Rps12 and Rps13 have been developed, but R gene-based markers will not be developed until specific R genes are pinpointed by a combination of mapping, RenSeq, and gene expression analysis. This objective was proposed to start in the FY24 project, so there is no data to report in FY23.

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The central goals of this multi-state and multi-disciplinary project were 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. We proposed five specific objectives towards achievement of these goals. Some objectives are consequential, and some are continuous. The major results from this project include: i) a comprehensive NBS-LRR gene dataset and the SoyRenSeq platform for NBS-LRR gene capture and enrichment; ii) SoyRenSeq data from 96 varieties (24 were proposed in FY23) as a valuable resource for this project team and the research community for R gene discovery; iii). genome-wide NBS-LRR gene expression patterns from a few resistant varieties in response to infection of Phytophthora sojae; iv) phenotypic data for disease resistance of soybean varieties adapted to a diverse environment in the north central region; v) biparental soybean populations at different generations for mapping or fine mapping of R genes; vi) QTLs mapped to chromosomes of resistant lines and markers for effective R gene selection in breeding. Markers linked to a few disease-resistant QTLs including Rpsan1, Rps12 and Rps13 have been developed. In addition, this project has resulted in three publications in scientific journals.

This project will explore, apply, and optimize the game-changing RenSeq and new sequencing technologies 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.