Analysis of the <i>2OG‐Fe (II) oxygenase</i> family reveals new insights associated with flowering regulation in <i>Saccharum spontaneum</i>
Bibliographic record
Abstract
Abstract Plant flowering is a crucial phenomenon affecting crop yield and crossbreeding. Saccharum spontaneum is the closest wild relative sugarcane species widely used in sugarcane genetic improvement. However, the molecular interactions among the components of the flowering regulatory network of S. spontaneum are still unclear. In this study, we conducted a transcriptome sequencing approach to analyze the expressed genes on four developmental stages of panicle samples in S. spontaneum. The weighted gene co‐expression network analysis (WGCNA) results suggested that genes from the MEred (p = 3 × 10−4) module were significantly enriched in pathways of ABC transporters, photosynthesis, and circadian rhythm‐plant. Thus, 23 genes associated with flower development‐related genes were screened, including 7 AGL24, 1 FLC, 3 VIN3, 3 GA20ox, and 9 ELF3. In the gibberellic acid (GA) synthesis pathway, GA20ox, GA3ox, and GA2ox were the three enzymes that catalyzed later reactions of GA biosynthesis and belong to the 2‐oxoglutarate Fe (II) oxygenase (2OG) superfamily. Flavonoid synthesis was promoted by 2‐oxoglutarate Fe (II) oxygenase genes, a flowering hormone, which catalyzed and oxidized naringenin to dihydrokaempferol, an important precursor of florigen. Genome‐wide analysis revealed that 122 Ss2OG genes were identified in S. spontaneum, of which 99 genes were enriched in the panicle transcriptome. Furthermore, a quantitative reverse transcription polymerase chain reaction analysis showed that Ss2OG‐FeII_Oxy90, Ss2OG‐FeII_Oxy47, and Ss2OG‐FeII_Oxy89 could introduce the flower development, while Ss2OG‐FeII_Oxy34, Ss2OG‐FeII_Oxy37, and Ss2OG‐FeII_Oxy50 inhibited it. These findings provide new clues and resources for exploring the molecular mechanism of flowering regulation in S. spontaneum and promoting sugarcane 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".