Fine mapping of the yellow seed locus in <i>Brassica juncea</i> L.
Bibliographic record
Abstract
The yellow mustard plant in Northern Shaanxi is a precious germplasm, and the yellow seed trait is controlled by a single recessive gene. In this report, amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) techniques were used to identify markers linked to the brown seed locus in an F(2) population consisting of 1258 plants. After screening 256 AFLP primer combinations and 456 pairs of SSR primers, we found 14 AFLP and 2 SSR markers that were closely linked to the brown seed locus. Among these markers, the SSR marker CB1022 showed codominant inheritance. By integrating markers previously found to be linked to the brown seed locus into the genetic map of the F(2) population, 23 markers were linked to the brown seed locus. The two closest markers, EA02MC08 and P03MC08, were located on either side of the brown seed locus at a distance of 0.3 and 0.5 cM, respectively. To use the markers for the breeding of yellow-seeded mustard plants, two AFLP markers (EA06MC11 and EA08MC13) were converted into sequence-characterized amplified region (SCAR) markers, SC1 and SC2, with the latter as the codominant marker. The two SSR markers were subsequently mapped to the A9/N9 linkage group of Brassica napus L. by comparing common SSR markers with the published genetic map of B. napus. A BLAST analysis indicated that the sequences of seven markers showed good colinearity with those of Arabidopsis chromosome 3 and that the homolog of the brown seed locus might exist between At3g14120 and At3g29615 on this same chromosome. To develop closer markers, we could make use of the sequence information of this region to design primers for future studies. Regardless, the close markers obtained in the present study will lay a solid foundation for cloning the yellow seed gene using a map-based cloning strategy.
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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) | 0.000 | 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 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".