Mapping of quantitative trait loci for high level of self-incompatibility in<i>Brassica rapa</i>L.
Bibliographic record
Abstract
The level of self-incompatibility (SI) is important to the purity of F1 seeds produced using the SI system of Brassica vegetables. To analyze the genetic basis of the level of SI, we generated an F2 population derived from a cross between a turnip inbred line showing a high level of SI and a Chinese cabbage inbred line showing a low level, and evaluated the level of SI under insect pollination in two years. We constructed a detailed linkage map of Brassica rapa from the F2 progeny, consisting of SSR, SNP, indel, and CAPS loci segregating into 10 linkage groups covering approximately 700 cM. Five quantitative trait loci (QTL) for high-level SI were identified. The phenotypic variation explained by the QTL ranged between 7.2% and 23.8%. Two QTL were detected in both years. Mapping of SI-related genes revealed that these QTL were co-localized with SLG on R07 and MLPK on R03. This is the first report of QTL for high-level SI evaluated under insect pollination in a Brassica vegetable. Our results could be useful for the marker-assisted selection of parental lines with a stable SI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".