Detection of candidate gene networks involved in resistance to Sclerotinia sclerotiorum in soybean
Bibliographic record
Abstract
Quantitative trait locus (QTL) mapping often yields associations with dissimilar loci/genes as a consequence of diverse factors. One trait for which very limited agreement between mapping studies has been observed is resistance to white mold in soybean. To explore whether different approaches applied to a single data set could lead to more consistent results, haplotype-trait association and epistasis interaction effects were explored as a complement to a more conventional marker-trait analysis. At least 10 genomic regions were significantly associated with Sclerotinia sclerotiorum resistance in soybean, which have not been previously reported. At a significance level of α = 0.05, haplotype-trait association showed that the most prominent signal originated from a haplotype with 4-SNP (single nucleotide polymorphism) on chromosome 17, and single SNP-trait analysis located a nucleotide polymorphism at position rs34387780 on chromosome 3. All of the peak-SNPs (p-value < 0.05) of each chromosome also appeared in their respective haplotypes. Samples with extreme phenotypes were singled-out for association studies, 25-30% from each end of the phenotypic spectrum appeared in the present investigation to be the most appropriate sample size. Some key genes were identified by epistasis interaction analysis. By combining information on the nearest positional genes indicated that most loci have not been previously reported. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggest potential candidate genes underlying callose deposition in the cell wall and mitogen-activated protein kinase (MAPK) signaling pathway-plant, as well as plant-pathogen interaction pathway, were activated. Integration of multi-method genome-wide association study (GWAS) revealed novel genomic regions and promising candidate genes in novel regions, which include Glyma.01g048500, Glyma.03g129100, Glyma.17g072200, and the Dishevelled (Dvl) family of proteins on chromosomes 1, 3, 17, and 20, respectively.
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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".