<i>At</i>MYB41 acts as a dual‐function transcription factor that regulates the formation of lipids in an organ‐ and development‐dependent manner
Bibliographic record
Abstract
Abstract The plant cuticle controls non‐stomatal water loss and can serve as a barrier against biotic agents, whereas the heteropolymer suberin and its associated waxes are deposited constitutively at specific cell wall locations. While several transcription factors controlling cuticle formation have been identified, those involved in the transcriptional regulation of suberin biosynthesis remain poorly characterized. The major goal of this study was to further analyse the function of the R2R3‐Myeloblastosis (MYB) transcription factor At MYB41 in formation of the cuticle, suberin, and suberin‐associated waxes throughout plant development. For functional analysis, the organ‐specific expression pattern of AtMYB41 was analysed and Atmyb41 ge alleles were generated using the CRISPR/Cas9 system. These were investigated for root growth and water permeability upon stress. In addition, the fatty acid, wax, cutin, and suberin monomer composition of different organs was evaluated by gas chromatography. The characterization of Atmyb41 ge mutants revealed that At MYB41 negatively regulates the production of cuticular lipids and fatty acid biosynthesis in leaves and seeds, respectively. Remarkably, biochemical analyses indicate that At MYB41 also positively regulates the formation of cuticular waxes in stems of Arabidopsis thaliana . Overall, these results suggest that the At MYB41 acts as a negative regulator of cuticle and fatty acid biosynthesis in leaves and seeds, respectively, but also as a positive regulator of wax production in A. thaliana stems.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".