The barley stem rust-resistance gene <i>Rpg1</i> is a novel disease-resistance gene with homology to receptor kinases
Bibliographic record
Abstract
Stem rust caused by Puccinia graminis f. sp. tritici was among the most devastating diseases of barley in the northern Great Plains of the U.S. and Canada before the deployment of the stem rust-resistance gene Rpg1 in 1942. Since then, Rpg1 has provided durable protection against stem rust losses in widely grown barley cultivars (cvs.). Extensive efforts to clone Rpg1 by synteny with rice provided excellent flanking markers but failed to yield the gene because it does not seem to exist in rice. Here we report the map-based cloning and characterization of Rpg1. A high-resolution genetic map constructed with 8,518 gametes and a 330-kb bacterial artificial chromosome contig physical map positioned the gene between two crossovers approximately 0.21 centimorgan and 110 kb apart. The region including Rpg1 was searched for potential candidate genes by sequencing low-copy probes. Two receptor kinase-like genes were identified. The candidate gene alleles were sequenced from resistant and susceptible cvs. Only one of the candidate genes showed a pattern of apparently functional gene structure in the resistant cvs. and defective gene structure in the susceptible cvs. identifying it as the Rpg1 gene. Rpg1 encodes a receptor kinase-like protein with two tandem protein kinase domains, a novel structure for a plant disease-resistance gene. Thus, it may represent a new class of plant resistance genes.
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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 | 0.001 |
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".