MUM ENHANCERS are important for seed coat mucilage production and mucilage secretory cell differentiation in Arabidopsis thaliana
Bibliographic record
Abstract
Pollination triggers not only embryo development but also the differentiation of the ovule integuments to form a specialized seed coat. The mucilage secretory cells of the Arabidopsis thaliana seed coat undergo a complex differentiation process in which cell growth is followed by the synthesis and secretion of pectinaceous mucilage. A number of genes have been identified affecting mucilage secretory cell differentiation, including MUCILAGE-MODIFIED4 (MUM4). mum4 mutants produce a reduced amount of mucilage and cloning of MUM4 revealed that it encodes a UDP-L-rhamnose synthase that is developmentally up-regulated to provide rhamnose for mucilage pectin synthesis. To identify additional genes acting in mucilage synthesis and secretion, a screen for enhancers of the mum4 phenotype was performed. Eight mum enhancers (men) have been identified, two of which result from defects in known mucilage secretory cell genes (MUM2 and MYB61). Our results show that, in a mum4 background, mutations in MEN1, MEN4, and MEN5 lead to further reductions in mucilage compared to mum4 single mutants, suggesting that they are involved in mucilage synthesis or secretion. Conversely, mutations in MEN2 and MEN6 appear to affect mucilage release rather than quantity. With the exception of men4, whose single mutant exhibits reduced mucilage, none of these genes have a single mutant phenotype, suggesting that they would not have been identified outside the compromised mum4 background.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".