Diacylglycerol acyltransferase: A key mediator of plant triacylglycerol synthesis
Bibliographic record
Abstract
Many plants deposit TAG in seeds and fruits as the major form of storage lipid. TAG production is of tremendous socioeconomic value in food, nutraceutical, and industrial applications, and thus numerous conventional and molecular genetic strategies have been explored in attempts to increase TAG content and modify the FA composition of plant seed oils. Much research has focused on the acyl-CoA-dependent reaction catalyzed by diacylglycerol acyltransferase (DGAT), which is an integral endoplasmic reticulum protein and has also been shown to be present in oil bodies and plastids. DGAT enzymes exhibit diverse biochemical properties among different plant species, many of which are summarized here. In addition to catalyzing a critical step in TAG biosynthesis, there is evidence that DGAT has roles in lipid metabolism associated with germination and leaf senescence. TAG can also be formed in plants via two different acyl-CoA-independent pathways, catalyzed by phospholipid: diacylglycerol acyltransferase and diacylglycerol transacylase. The current understanding of the terminal step in TAG formation in plants and the development of molecular genetic approaches aimed at altering TAG yield and FA composition of TAG are discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.007 |
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".