MUCILAGE-RELATED10 Produces Galactoglucomannan That Maintains Pectin and Cellulose Architecture in Arabidopsis Seed Mucilage
Bibliographic record
Abstract
Plants invest a lot of their resources into the production of an extracellular matrix built of polysaccharides. While the composition of the cell wall is relatively well characterized, the functions of the individual polymers and the enzymes that catalyze their biosynthesis remain poorly understood. We exploited the Arabidopsis (Arabidopsis thaliana) seed coat epidermis (SCE) to study cell wall synthesis. SCE cells produce mucilage, a specialized secondary wall that is rich in pectin, at a precise stage of development. A coexpression search for MUCILAGE-RELATED (MUCI) genes identified MUCI10 as a key determinant of mucilage properties. MUCI10 is closely related to a fenugreek (Trigonella foenumgraecum) enzyme that has in vitro galactomannan α-1,6-galactosyltransferase activity. Our detailed analysis of the muci10 mutants demonstrates that mucilage contains highly branched galactoglucomannan (GGM) rather than unbranched glucomannan. MUCI10 likely decorates glucomannan, synthesized by CELLULOSE SYNTHASE-LIKE A2, with galactose residues in vivo. The degree of galactosylation is essential for the synthesis of the GGM backbone, the structure of cellulose, mucilage density, as well as the adherence of pectin. We propose that GGM scaffolds control mucilage architecture along with cellulosic rays and show that Arabidopsis SCE cells represent an excellent model in which to study the synthesis and function of GGM. Arabidopsis natural varieties with defects similar to muci10 mutants may reveal additional genes involved in GGM synthesis. Since GGM is the most abundant hemicellulose in the secondary walls of gymnosperms, understanding its biosynthesis may facilitate improvements in the production of valuable commodities from softwoods.
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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".