Gibberellin signaling regulates pectin biosynthesis in Arabidopsis
Bibliographic record
Abstract
Pectin is an abundant polysaccharide with essential roles in various biological processes. Despite considerable advances in understanding the regulatory mechanisms of pectin biosynthesis, the influence of phytohormones on this process remains unclear. Here we report that gibberellins (GA) promotes pectin biosynthesis in Arabidopsis. The DELLA proteins, as GA signaling repressors, interact with TRANSPARENT TESTA GLABRA2 (TTG2) and components of the MYB-bHLH-WD40 (MBW) complex, the key regulators of pectin biosynthesis, to repress their transcriptional regulatory activities. Furthermore, the MBW proteins and TTG2 physically interact and synergistically activate the downstream target GLABRA2, whereas this interaction and collaboration are competitively attenuated by DELLAs. Genetic analyses validate that GA-mediated pectin biosynthesis relies on functional TTG2 and MBW proteins. Moreover, the pectin biosynthesis mediated by the GA-DELLA-MBW-TTG2 module contributes to GA-regulated seedling growth. Our findings reveal the significance of the GA-DELLA-MBW-TTG2 signaling cascade in the regulation of pectin biosynthesis and plant development. Pectin, as a major component of plant cell walls, has essential roles in various biological processes. Here the authors show that gibberellins signal via DELLA proteins to regulate pectin biosynthesis by attenuating the activity of the TTG2 and MBW complexes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".