Association mapping of a locus that confers Southern stem canker resistance in soybean
Bibliographic record
Abstract
Abstract Background Southern stem canker (SSC), caused by Diaporthe aspalathi (E. Jansen, Castl. & Crous) is an important soybean disease, which has been responsible for severe losses in the past. The main strategy to control this fungus is through the introgression of resistance genes. So far, five main loci have been associated with resistance to Southern stem canker. However, there is a lack of information about useful allelic variation at these loci. In this work, a genome-wide association study (GWAS) was performed to identify allelic variation associated with resistance against Diaporthe aspalathi and to provide molecular markers useful in breeding programs. Results We characterized the response to Southern stem canker infection in a panel of 295 accessions from different regions of the world including important Brazilian elite cultivars. Using a GBS approach, the panel was genotyped and we identified marker loci associated with Diaporthe aspalathi resistance using GWAS analysis. We identified 19 SNPs associated with Southern stem canker resistance, all on chromosome 14. The peak SNP showed an extremely high degree of association (p-value = 6.35E-27) and explained a high level of the phenotypic variance (R2 = 70%). This strongly suggests that a single major gene is responsible for resistance to D. aspalathi present inn most of the lines comprising this panel. We also identified in resequenced soybean materials other SNPs in the region identified by GWAS in the same LD block that clearly differentiate resistance and susceptible accessions. The peak SNP was selected and used to develop a cost-effective molecular marker assay, which was validated in a subset of the initial panel. In an accuracy test, this SNP assay demonstrated 98% of selection efficiency. Conclusions Our results suggest a relevant importance of this locus in SSC resistance in soybean cultivars and accessions from different countries and the SNP marker assay developed in this study can be directly applied in MAS studies in breeding programs to select resistance materials against this pathogen and support its introgression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".