The Accumulation of Oleosins Determines the Size of Seed Oilbodies in <i>Arabidopsis</i>
Bibliographic record
Abstract
We investigated the role of the oilbody proteins in developing and germinating Arabidopsis thaliana seeds. Seed oilbodies are simple organelles comprising a matrix of triacylglycerol surrounded by a phospholipid monolayer embedded and covered with unique proteins called oleosins. Indirect observations have suggested that oleosins maintain oilbodies as small single units preventing their coalescence during seed desiccation. To understand the role of oleosins during seed development or germination, we created lines of Arabidopsis in which a major oleosin is ablated or severely attenuated. This was achieved using RNA interference techniques and through the use of a T-DNA insertional event, which appears to interrupt the major (18 kD) seed oleosin gene of Arabidopsis and results in ablation of expression. Oleosin suppression resulted in an aberrant phenotype of embryo cells that contain unusually large oilbodies that are not normally observed in seeds. Changes in the size of oilbodies caused disruption of storage organelles, altering accumulation of lipids and proteins and causing delay in germination. The aberrant phenotypes were reversed by reintroducing a recombinant oleosin. Based on this direct evidence, we have shown that oleosins are important proteins in seed tissue for controlling oilbody structure and lipid accumulation.
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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".