Cellulose synthesis via the FEI2 RLK/SOS5 pathway and CELLULOSE SYNTHASE 5 is required for the structure of seed coat mucilage in Arabidopsis
Bibliographic record
Abstract
The seeds of Arabidopsis thaliana and many other plants are surrounded by a pectinaceous mucilage that aids in seed hydration and germination. Mucilage is synthesized during seed development within maternally derived seed coat mucilage secretory cells (MSCs), and is released to surround the seed upon imbibition. The FEI1/FEI2 receptor-like kinases and the SOS5 extracellular GPI-anchored protein were shown previously to act on a pathway that regulates the synthesis of cellulose in Arabidopsis roots. Here, we demonstrate that both FEI2 and SOS5 also play a role in the synthesis of seed mucilage. Disruption of FEI2 or SOS5 leads to a reduction in the rays of cellulose observed across the seed mucilage inner layer, which alters the structure of the mucilage in response to hydration. Mutations in CESA5, which disrupts an isoform of cellulose synthase involved in primary cell wall synthesis, result in a similar seed mucilage phenotype. The data indicate that CESA5-derived cellulose plays an important role in the synthesis and structure of seed coat mucilage and that the FEI2/SOS5 pathway plays a role in the regulation of cellulose synthesis in MSCs. Moreover, these results establish a novel structural role for cellulose in anchoring the pectic component of seed coat mucilage to the seed surface.
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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 | 0.000 |
| 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".