Fine mapping of the major QTL for seed coat color in Brassica rapa var. Yellow Sarson by use of NIL populations and transcriptome sequencing for identification of the candidate genes
Bibliographic record
Abstract
Yellow seed is a desirable trait in Brassica oilseed crops. The B. rapa var. Yellow Sarson carry unique yellow seed color genes which are not only important for the development of yellow-seeded oilseed B. rapa cultivars but this variant can also be used to develop yellow-seeded B. napus. In this study, we developed near-isogenic lines (NILs) of Yellow Sarson for the major seed coat color QTL SCA9-2 of the chromosome A9 and used the NILs to fine map this QTL region and to identify the candidate genes through linkage mapping and transcriptome sequencing of the developing seeds. From the 18.4 to 22.79 Mb region of SCA9-2, six SSR markers showing 0.63 to 5.65% recombination were developed through linkage analysis and physical mapping. A total of 55 differentially expressed genes (DEGs) were identified in the SCA9-2 region through transcriptome analysis; these included three transcription factors, Bra028039 (NAC), Bra023223 (C2H2 type zinc finger), Bra032362 (TIFY), and several other genes which encode unknown or nucleic acid binding protein; these genes might be the candidates and involved in the regulation of seed coat color in the materials used in this study. Several biosynthetic pathways, including the flavonoid, phenylpropanoid and suberin biosynthetic pathways were significantly enriched through GO and KEGG enrichment analysis of the DEGs. This is the first comprehensive study to understand the yellow seed trait of Yellow Sarson through employing linkage mapping and global transcriptome analysis approaches.
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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) | 0.001 | 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".