A major suppressor of cell death,<i>slm1</i>, modifies the expression of the maize (<i>Zea mays</i>L.) lesion mimic mutation<i>les23</i>
Bibliographic record
Abstract
Disease lesion mimics provide an excellent biological system to study the genetic basis of cell death in plants. Many lesion mimics show variation in phenotype expression in different genetic backgrounds. Our goal was to identify quantitative trait loci (QTL) modifying lesion mimic expression thereby identifying genetic modifiers of cell death. A recessive lesion mimic, les23, in a severe-expressing line was crossed to the maize inbred line Mo20W, a lesion-suppressing line, and an F(2) population was developed for QTL analysis. In addition to locating les23 to the short arm of chromosome 2, this analysis detected significant loci for modification of lesion expression. One highly significant locus was found on the long arm of chromosome 2. The Mo20W allele at this QTL significantly delayed initiation of the lesion phenotype and decreased the final lesion severity. Other QTL with lesser effect affected severity of lesion expression without affecting lesion initiation date. Our results demonstrate that dramatic change in lesion phenotype can be controlled by a single major QTL. The presumed function of this QTL in normal plants is to regulate some aspect of the cell death pathway underlying the les23 phenotype.
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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 | 0.000 |
| 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".