MdMyb93 is a regulator of suberin deposition in russeted apple fruit skins
Bibliographic record
Abstract
A comparison of the transcriptomes of russeted vs nonrusseted apple skins previously highlighted a tight relationship between a gene encoding an MYB-type transcription factor, MdMYB93, and some key suberin biosynthetic genes. The present work assesses the role of this transcription factor in the suberization process. A phylogenetic analysis of MdMYB93 and Arabidopsis thaliana MYBs was performed and the function of MdMYB93 was further investigated using Agrobacterium-mediated transient overexpression in Nicotiana benthamiana leaves. An RNA-Seq analysis was performed to highlight the MdMYB93-regulated genes. Ultraperformance liquid chromatography-triple time-of-flight (UPLC-TripleTOF) and GC-MS were used to investigate alterations in phenylpropanoid, soluble-free lipid and lipid polyester contents. A massive accumulation of suberin and its biosynthetic precursors in MdMYB93 agroinfiltrated leaves was accompanied by a remobilization of phenylpropanoids and an increased amount of lignin precursors. Gene expression profiling displayed a concomitant alteration of lipid and phenylpropanoid metabolism, cell wall development, and extracellular transport, with a large number of induced transcripts predicted to be involved in suberin deposition. The present work supports a major role of MdMYB93 in the regulation of suberin deposition in russeted apple skins, from the synthesis of monomeric precursors, their transport, polymerization, and final deposition as suberin in primary cell wall.
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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".