Understanding the expression and interaction of <i>Rph</i> genes conferring seedling and adult plant resistance to <i>Puccinia hordei</i> in barley
Bibliographic record
Abstract
Leaf rust caused by Puccinia hordei is a major disease of barley and is best managed by deploying effective resistance genes. The effect of post-inoculation temperature [18 ± 2°C (low), 22 ± 2°C (mid), or 26 ± 2°C (high)] on the expression of a selection of known all stage resistance (ASR) Rph genes and their interaction in combination with the adult plant resistance (APR) gene Rph20 were investigated in barley. Rph1.a and Rph2.b expressed best at higher temperatures whereas Rph4.d lost its effectiveness at higher temperatures when tested with pathotype (pt) 200 P− (avirulent on these genes). The expression of the genes Rph3.c, Rph5.e, Rph6.f, Rph12 (9.z), Rph13.x and Rph15.ad was not affected by post-inoculation temperature. The interaction between Rph14.ab and pt 5457 P+ gave the lowest infection type at low post-inoculation temperature. Among a selection of lines carrying Rph20 (‘Flagship’), Rph23 (‘Yerong’) and Rph24 (‘ND24260ʹ), higher levels of resistance were observed in seedlings of ‘Flagship’ (Rph20) at lower temperatures, while seedlings of ‘Yerong’ (Rph23) and ‘ND24260ʹ (Rph24) showed high infection types at all three temperatures with pt 5457 P+. When RphASR genes were combined with the APR gene Rph20 an enhanced level of seedling resistance was observed in the six combinations: Rph1.a+Rph20, Rph2.b+Rph20, Rph4.d+Rph20, Rph9.i+Rph20, Rph5.e+Rph20 and Rph15.ad+Rph20. Seedlings carrying the Rph5.e+Rph20 combination remained resistant when challenged with the Rph5.e-virulent pt 220 P+ + Rph13, suggesting a residual effect of Rph5.e when present in combination with Rph20. This is the first study to demonstrate that several ASR Rph genes interact with the APR gene Rph20 in an additive manner, emphasizing the importance of deploying genes in combination rather than individually to achieve durable resistance.
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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) | 0.001 | 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".