<scp>MYB</scp>103 is required for <i><scp>FERULATE</scp>‐5‐<scp>HYDROXYLASE</scp></i> expression and syringyl lignin biosynthesis in <scp>A</scp>rabidopsis stems
Bibliographic record
Abstract
The transcription factor MYB103 was previously identified as a member of the transcriptional network regulating secondary wall biosynthesis in xylem tissues of Arabidopsis, and was proposed to act on cellulose biosynthesis. It is a direct transcriptional target of the transcription factor SECONDARY WALL ASSOCIATED NAC DOMAIN PROTEIN 1 (SND1), and 35S-driven dominant repression or over-expression of MYB103 modifies secondary wall thickness. We identified two myb103 T-DNA insertion mutants and chemically characterized their lignocellulose by pyrolysis/GC/MS, 2D NMR, FT-IR microspectroscopy and wet chemistry. The mutants developed normally but exhibited a 70-75% decrease in syringyl (S) lignin. The level of guaiacyl (G) lignin was co-ordinately increased, so that total Klason lignin was not affected. The transcript abundance of FERULATE-5-HYDROXYLASE (F5H), the key gene in biosynthesis of S lignin, was strongly decreased in the myb103 mutants, and the metabolomes of the myb103 mutant and an F5H null mutant were very similar. Other than modification of the lignin S to G ratio, there were only very minor changes in the composition of secondary cell-wall polymers in the inflorescence stem. In conclusion, we demonstrate that F5H expression and hence biosynthesis of S lignin are dependent on MYB103.
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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 | 0.001 |
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".