Development of barley introgression lines carrying the leaf rust resistance genes <i>Rph1</i> to <i>Rph15</i>
Bibliographic record
Abstract
Abstract In many production areas, barley ( Hordeum vulgare L.) is attacked by the leaf rust pathogen ( Puccinia hordei Otth), a basidiomycetous fungus that reduces both its yield and quality. Many leaf rust resistance genes, known as reaction to P. hordei ( Rph ) genes, have been described in barley. To differentiate genetic variants for virulence in pathogen populations, plant pathologists use differentials (i.e., sets of host lines carrying different resistance genes). The sources of Rph1–15 were derived from cultivars, landraces, and wild barley ( H . vulgare ssp. spontaneum K. Koch) accessions with diverse geographic origins and agromorphological traits. Ideal differential sets comprise single‐gene lines backcrossed to a single adapted accession that is susceptible to all known races of a pathogen. In this study, sources of Rph1–15 and other Rph gene donors were backcrossed to the susceptible barley cultivar Bowman and then genotyped to characterize the chromosomal positions and sizes of introgressions. Overall, 95 Bowman introgression lines for leaf rust resistance were developed and characterized for their rust phenotypes and genotypes. A single line was selected to represent each of the 15 Rph genes for use as the new barley leaf rust differential set. The existence of possible new resistance genes in the studied germplasm was postulated. The new Bowman Rph1–15 differential lines will facilitate the efficient virulence phenotyping of P. hordei and serve as valuable genetic stocks for Rph gene stacking and cloning in barley.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".