The ectopic expression of Arabidopsis glucosyltransferase UGT74D1 affects leaf positioning through modulating indole-3-acetic acid homeostasis
Bibliographic record
Abstract
Leaf angle is an important agronomic trait affecting photosynthesis efficiency and crop yield. Although the mechanisms involved in the leaf angle control are intensively studied in monocots, factors contribute to the leaf angle in dicots are largely unknown. In this article, we explored the physiological roles of an Arabidopsis glucosyltransferase, UGT74D1, which have been proved to be indole-3-acetic acid (IAA) glucosyltransferase in vitro. We found that UGT74D1 possessed the enzymatic activity toward IAA glucosylation in vivo and its expression was induced by auxins. The ectopically expressed UGT74D1 obviously reduced the leaf angle with an altered IAA level, auxin distribution and cell size in leaf tissues. The expression of several key genes involved in the leaf shaping and leaf positioning, including PHYTOCHROME KINASE SUBSTRATE (PKS) genes and TEOSINTE BRANCHED1, CYCLOIDEA, and PCF (TCP) genes, were dramatically changed by ectopic expression of UGT74D1. In addition, clear transcription changes of YUCCA genes and other auxin related genes can be observed in overexpression lines. Taken together, our data indicate that glucosyltransferase UGT74D1 could affect leaf positioning through modulating auxin homeostasis and regulating transcription of PKS and TCP genes, suggesting a potential new role of UGT74D1 in regulation of leaf angle in dicot Arabidopsis.
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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".