Molecular mapping of <i>Or</i>, a gene inducing beta-carotene accumulation in cauliflower (<i>Brassica oleracea</i> L. var. <i>botrytis</i>)
Bibliographic record
Abstract
The cauliflower (Brassica oleracea L. var. botrytis) Or gene is a semi-dominant, single-locus mutation that induces the accumulation of high levels of beta-carotene in various tissues of the plant, turning them orange. As part of a map-based cloning strategy, molecular mapping of the Or gene in the cauliflower genome was undertaken in a mapping population consisting of 195 F2 individuals. By using amplified fragment length polymorphism (AFLP) in conjunction with bulked segregant analysis, we identified 10 AFLP markers closely linked to the Or gene. Four of the most closely linked flanking markers were converted into restriction fragment length polymorphism (RFLP) markers. Mapping of these markers in the mapping population placed two of them at 0.5 cM from the Or locus on one side, while another marker flanked the Or gene at 1.6 cM on the other side. Three of these markers were also successfully converted into sequence-characterized amplified region (SCAR) markers. These PCR-based markers will be useful for a large-scale application in facilitating the positional cloning of the Or gene.
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 | 0.001 | 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".