Genome-Wide Identification of Flowering-Time Genes in Brassica Species and Reveals a Correlation between Selective Pressure and Expression Patterns of Vernalization-Pathway Genes in Brassica napus
Bibliographic record
Abstract
Flowering time is a key agronomic trait, directly influencing crop yield and quality. Many flowering-time genes have been identified and characterized in the model plant Arabidopsis thaliana; however, these genes remain uncharacterized in many agronomically important Brassica crops. In this study, we identified 1064, 510, and 524 putative orthologs of A. thaliana flowering-time genes from Brassica napus, Brassica rapa, and Brassica oleracea, respectively, and found that genes involved in the aging and ambient temperature pathways were fewer than those in other flowering pathways. Flowering-time genes were distributed mostly on chromosome C03 in B. napus and B. oleracea, and on chromosome A09 in B. rapa. Calculation of non-synonymous (Ka)/synonymous substitution (Ks) ratios suggested that flowering-time genes in vernalization pathways experienced higher selection pressure than those in other pathways. Expression analysis showed that most vernalization-pathway genes were expressed in flowering organs. Approximately 40% of these genes were highly expressed in the anther, whereas flowering-time integrator genes were expressed in a highly organ-specific manner. Evolutionary selection pressures were negatively correlated with the breadth and expression levels of vernalization-pathway genes. These findings provide an integrated framework of flowering-time genes in these three Brassica crops and provide a foundation for deciphering the relationship between gene expression patterns and their evolutionary selection pressures in Brassica napus.
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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 | 0.001 |
| 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) | 0.000 | 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".