Single amino acid change alters specificity of the multi-allelic wheat stem rust resistance locus SR9
Bibliographic record
Abstract
Most rust resistance genes thus far isolated from wheat have a very limited number of functional alleles. Here, we report the isolation of most of the alleles at wheat stem rust resistance gene locus SR9. The seven previously reported resistance alleles (Sr9a, Sr9b, Sr9d, Sr9e, Sr9f, Sr9g, and Sr9h) are characterised using a synergistic strategy. Loss-of-function mutants and/or transgenic complementation are used to confirm Sr9b, two haplotypes of Sr9e (Sr9e_h1 and Sr9e_h2), Sr9g, and Sr9h. Each allele encodes a highly related nucleotide-binding site leucine-rich repeat (NB-LRR) type immune receptor, containing an unusual long LRR domain, that confers resistance to a unique spectrum of isolates of the wheat stem rust pathogen. The only SR9 protein effective against stem rust pathogen race TTKSK (Ug99), SR9H, differs from SR9B by a single amino acid. SR9B and SR9G resistance proteins are also distinguished by only a single amino acid. The SR9 allelic series found in the B subgenome are orthologs of wheat stem rust resistance gene Sr21 located in the A subgenome with around 85% identity in protein sequences. Together, our results show that functional diversification of allelic variants at the SR9 locus involves single and multiple amino acid changes that recognize isolates of wheat stem rust.
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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".