QTL mapping for seed density per silique in Brassica napus
Bibliographic record
Abstract
Seed density per silique (SDPS) and valid silique length (VSL) are two important yield-influencing traits in rapeseed. SDPS has a direct or indirect effect on rapeseed yield through its effect on seed per silique. In this study, a quantitative trait locus (QTL) for SDPS was detected on chromosome A09 using the QTL-seq approach and confirmed via linkage analysis in the mapping population obtained from 4263 × 3001 cross. Furthermore, one major QTL for SDPS (qSD.A9-1) was mapped to a 401.8 kb genomic interval between SSR markers Nys9A190 and Nys9A531. In the same genomic region, a QTL (qSL.A9) linked to VSL was also detected. The phenotypic variation of qSD.A9-1 and qSL.A9 was 53.1% and 47.6%, respectively. Results of the additive and dominant effects demonstrated that the expression of genes controlling SDPS and VSL were derived from a different parent in this population. Subsequently, we identified 56 genes that included 45 specific genes with exonic (splicing) variants. Further analysis identified specific genes containing mutations that may be related to seed density as well as silique length. These genes could be used for further studies to understand the details of these traits of rapeseed.
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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 | 0.001 | 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".