Deciphering the transcriptional regulatory networks that control size, color, and oil content in Brassica rapa seeds
Bibliographic record
Abstract
Abstract Background Brassica rapa is an important oilseed and vegetable crop species and is the A subgenome donor of two important oilseed Brassica crops, Brassica napus and Brassica juncea . Although seed size (SZ), seed color (SC), and oil content (OC) substantially affect seed yield and quality, the mechanisms regulating these traits in Brassica crops remain unclear. Results We collected seeds from a pair of B. rapa accessions with significantly different SZ, SC, and OC at seven seed developmental stages (every 7 days from 7 to 49 days after pollination), and identified 28,954 differentially expressed genes (DEGs) from seven pairwise comparisons between accessions at each developmental stage. K -means clustering identified a group of cell cycle-related genes closely connected to variation in SZ of B. rapa . A weighted correlation analysis using the WGCNA package in R revealed two important co-expression modules comprising genes whose expression was positively correlated with SZ increase and negatively correlated with seed yellowness, respectively. Upregulated expression of cell cycle-related genes in one module was important for the G 2 /M cell cycle transition, and the transcription factor Bra.A05TSO1 seemed to positively stimulate the expression of two CYCB1;2 genes to promote seed development. In the second module, a conserved complex regulated by the transcription factor TT8 appear to determine SC through downregulation of TT8 and its target genes TT3 , TT18 , and ANR . In the third module, WRI1 and FUS3 were conserved to increase the seed OC, and Bra.A03GRF5 was revealed as a key transcription factor on lipid biosynthesis. Further, upregulation of genes involved in triacylglycerol biosynthesis and storage in the seed oil body may increase OC. We further validated the accuracy of the transcriptome data by quantitative real-time PCR of 15 DEGs. Finally, we used our results to construct detailed models to clarify the regulatory mechanisms underlying variations in SZ, SC, and OC in B. rapa . Conclusions This study provides insight into the regulatory mechanisms underlying the variations of SZ, SC, and OC in plants based on transcriptome comparison. The findings hold great promise for improving seed yield, quality and OC through genetic engineering of critical genes in future molecular breeding.
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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".