Development of molecular markers for marker assisted selection for seed quality traits in oilseed rape
Bibliographic record
Abstract
Molecular markers for seed quality traits including erucic acid content genes, seed coat color genes in Brassica napus and seed coat color genes in B. rapa were developed. A single base change in the Bn-FAE1.1 gene in the A genome and a two-base deletion in the Bn-FAE1.2 gene in the C genome produce the nearly zero content of erucic acid observed in canola. The single base change was detected as single nucleotide polymorphic (SNP) marker with an ABI SNaPshot kit. A multiplexing primer set was designed by adding a polyT to the 5´ primer end to increase SNP detection throughput through sample pooling. The two-base deletion in the C genome gene was detected as a sequence characterized amplified region (SCAR) marker in an ABI 3100 Genetic analyzer. To increase the throughput, one genome specific primer was labeled with four fluorescence dyes and combined with 20 different primers to produce PCR products with different fragment sizes. These multiplexed high throughput molecular markers have been successfully implemented in our canola/rapeseed breeding programs. Trigenic inheritance was observed for seed coat color in B. napus. Three Sequenced Related Amplified Polymorphism (SRAP) markers very closely linked to the three different seed coat color genes were developed. Chromosome-walking technology was used to convert the SRAP marker into a SCAR marker and a SNP marker. Subsequently, the first seed coat color gene (Bn1) marker was converted into a SCAR marker, and the second seed coat color gene (Bn2) marker was converted into a SNP marker. Digenic inheritance was observed for seed coat color genes in B. rapa. A SRAP marker was identified as being tightly linked to the major seed coat color gene (Br1). The SRAP marker was sequenced and extended sequences were obtained using chromosome-walking technology. The flanking sequences of the SRAP marker contained 24 SNPs and a 12-bp deletion position that allowed the marker to be converted into a co-dominant SNP marker and a co-dominant SCAR marker, respectively. The SCAR marker was detected in the ABI 3100 genetic analyzer with four fluorescently labeled M13 primers integrated with different SCAR primers, which permitted pooling of PCR samples for high throughput detection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".