Seed hemicelluloses tailor mucilage properties and salt tolerance
Bibliographic record
Abstract
Summary While Arabidopsis seed coat epidermal cells have become an excellent genetic system to study the biosynthesis and structural roles of various cell wall polymers, the physiological function of the secreted mucilaginous polysaccharides remains ambiguous. Seed mucilage is shaped by two distinct classes of highly substituted hemicelluloses along with cellulose and structural proteins, but their interplay has not been explored. We deciphered the functions of four distinct classes of cell wall polymers by generating a series of double mutants with defects in heteromannan, xylan, cellulose, or the arabinogalactan protein SALT‐OVERLY SENSITIVE 5 (SOS5), and evaluating their impact on mucilage architecture and seed germination during salt stress. We discovered that muci10 seeds, lacking heteromannan branches, had elevated tolerance to salt stress, while heteromannan elongation mutants exhibited reduced germination in calcium chloride (CaCl 2 ). By contrast, xylan made by MUCILAGE‐RELATED21 ( MUCI21 ) was found to be required for the adherence of mucilage pectin to microfibrils made by CELLULOSE SYNTHASE5 (CESA5) as well as to a SOS5‐mediated network. Our results indicate that the substitution of xylan and glucomannan in seeds can fine‐tune mucilage adherence and salt tolerance, respectively. The study of germinating seeds can thus provide insights into the synthesis, modification and function of complex glycans.
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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".