A single amino acid change can alter the specificity of the multi-allelic wheat stem rust resistance locus SR9
Bibliographic record
Abstract
Abstract Most resistance genes thus far isolated from wheat have a very limited number of functional alleles, with the exception of the powdery mildew PM3 resistance locus. Here we report the isolation of most of the alleles at wheat stem rust resistance gene locus SR9 , representing the largest multi-allelic rust resistance locus in common wheat. The seven previously reported resistance alleles ( Sr9a , Sr9b , Sr9d , Sr9e , Sr9f , Sr9g , and Sr9h ) at the locus were characterised using a synergistic strategy. Loss-of-function mutants and/or transgenic complementation were used to confirm Sr9b , two haplotypes of Sr9e ( Sr9e_h1 , Sr9e_h2 ), Sr9g , and Sr9h . Each allele encodes a highly related nucleotide-binding site leucine-rich repeat (NB-LRR) type immune receptor, containing a previously unreported motif at their N termini and 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, differed from SR9B by a single amino acid. SR9B and SR9G resistance proteins were 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".