Quantitative Trait Loci Mapping and Candidate Gene Identification for Seed Glucosinolates in <i>Brassica rapa</i> L.
Bibliographic record
Abstract
Glucosinolates (GSLs) are sulfur‐ and nitrogen‐rich plant secondary metabolites biosynthesized in plant species belonging to the order Brassicales. In this study, using recombinant inbred lines (RILs) developed from a cross between Chinese cabbage [Brassica rapa L. subsp. chinensis (L.) Hanelt and subsp. pekinensis (Lour.) Hanelt] and yellow sarson [B. rapa L. subsp. trilocularis (Roxb.) Hanelt], eight gene‐specific and gene‐flanking markers for GSLs and 148 simple‐sequence repeat (SSR) markers were assembled on the previous ultradense genetic map of B. rapa. Quantitative trait loci (QTL) mapping for GSLs was performed using this genetic map, and gene‐specific markers were used to identify the loci involved in the biosynthesis of GSLs. Over a dozen QTL for progoitrin, gluconapin, glucoalyssin, glucobrassicanapin, 4‐hydroxyglucobrassicin, total aliphatic glucosinolate, and total GSL were identified in seeds. A candidate locus of Br‐GSL‐ELONG gene on linkage group A03 was identified to cosegregate with 5C aliphatic GSLs (glucoalyssin, glucobrassicanapin, and sum of 5C) in B. rapa. This locus was also colocalized with the QTL controlling seed gluconapin and sum of 4C GSL (gluconapin, progoitrin). The results suggest that the Br‐GSL‐ELONG locus on linkage group A03 might have multifunctional properties for 4C and 5C aliphatic GSL biosynthesis in Brassica species. Glucosinolate biosynthesis gene‐specific molecular markers developed in this study can be used to manipulate GSLs in other Brassica species including rapeseed (B. napus L.) and Brassica vegetables.
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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".