Isolation of <i>Pikps</i>, an allele of <i>Pik</i>, from the <i>aus</i> rice cultivar Shoni
Bibliographic record
Abstract
Blast disease caused by the filamentous fungus Pyricularia oryzae (syn. Magnaporthe oryzae) is one of the most destructive diseases of rice (Oryza sativa L.) around the globe. An aus cultivar, Shoni, showed resistance against at least four Japanese P. oryzae isolates. To understand Shoni's resistance against the P. oryzae isolate Naga69-150, genetic analysis was carried out using recombinant inbred lines developed by a cross between Shoni and the japonica cultivar Hitomebore, which is susceptible to Naga69-150. The result indicated that the resistance was controlled by a single locus, which was named Pi-Shoni. A QTL analysis identified Pi-Shoni as being located in the telomeric region of chromosome 11. A candidate gene approach in the region indicated that Pi-Shoni corresponds to the previously cloned Pik locus, and we named this allele Pikps. Loss of gene function mediated by RNA interference demonstrated that a head-to-head-orientated pair of NBS-LRR receptor genes (Pikps-1 and Pikps-2) are required for the Pikps-mediated resistance. Amino acid sequence comparison showed that Pikps-1 is 99% identical to Pikp-1, while Pikps-2 is identical to Pikp-2. Pikps-1 had one amino acid substitution (Pro351Ser) in the NBS domain as compared to Pikp-1. The recognition specificity of Pikps against known AVR-Pik alleles is identical to that of Pikp.
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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) | 0.001 | 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 | 0.001 |
| 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".