The 3Ns Chromosome of <i>Psathyrostachys huashanica</i> Carries the Gene(s) Underlying Wheat Stripe Rust Resistance
Bibliographic record
Abstract
Stripe rust (Puccinia striiformis tritici (Pst)) is one of the most destructive diseases of wheat in the world. Exploiting and utilizing stripe rust resistance genes of wild species has become an essential strategy for resistance breeding. Psathyrostachyshuashanica Keng ex Kuo is a wild species in Triticeae that has been used for wheat improvement because of its high resistance or immunity to stripe rust. In this study, 9 wheat-P. huashanica addition lines were characterized by Giemsa C-banding, genomic in situ hybridization (GISH), and disease resistance evaluation. Giemsa C-banding and GISH demonstrated that lines 163-5, 165-1, 183-5, 240-3, and 240-4 are P. huashanica 3Ns chromosome monosomic addition lines; lines 183-1 and 183-20 are P. huashanica 3Ns chromosome disomic addition lines; line 165-20 is a P. huashanica 3Ns and 4Ns chromosomes double disomic addition line, and line 219-1 is a P. huashanica 1Ns and 3Ns/5A chromosomes double disomic addition-substitution line. All these addition lines with P. huashanica 3Ns chromosome(s) expressed high resistance or immunity to stripe rust. By comparing the series of wheat-P. huashanica chromosome addition lines, we concluded that the P. huashanica 3Ns chromosome carries the gene(s) for resistance or immunity to stripe rust. These addition lines can be used as a donor source of novel stripe rust resistance to wheat breeding programs.
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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) | 0.002 | 0.001 |
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".