High-density SNP mapping reveals closely linked QTL for resistance to Stagonospora nodorum blotch (SNB) in flag leaf and glume of hexaploid wheat
Bibliographic record
Abstract
The genetic control of adult plant resistance to Stagonospora nodorum blotch (SNB) is complex, consisting of genes with minor effects interacting in an additive manner. Earlier studies detected quantitative trait loci (QTL) for flag leaf resistance in successive years on chromosomes 1B, 2A, 2D, and 5B using SSR- and DArT-based genetic maps of progeny from the crosses EGA Blanco/Millewa, 6HRWSN125/WAWHT2074, and P92201D5/P91193D1. Similarly, QTL for glume resistance detected in successive years and multiple environments were identified on chromosomes 2D and 4B from genetic maps of P92201D5/P91193D1 and 6HRWSN125/WAWHT2074, respectively. The SSR- and DArT-based genetic maps had an average distance of 6.5, 7.8, and 9.7 cM between marker loci for populations EGA/Millewa, P92201D5/P91193D1, and 6HRWSN125/WAWHT2074, respectively. This study used single nucleotide polymorphism (SNP) markers from the iSelect Infinium 90K genotyping array to fine-map genomic regions harbouring QTL for flag leaf and glume SNB resistance, reducing the average distance between markers to 2.9, 3.3, and 3.4 cM for populations P92201D5/P91193D1, EGA/Millewa, and 6HRWSN125/WAWHT2074, respectively. Increasing the marker density of the genetic maps with SNPs did not identify any new QTL for SNB resistance but discriminated previously identified co-located QTL into separate but closely linked QTL.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".