Properties and biochemistry of phosphatidylcholine: diacylglycerol cholinephosphotransferase
Bibliographic record
Abstract
Plant oils, primarily composed of triacylglycerols (TAGs), are essential for both food and industrial applications. TAGs consist of three fatty acids esterified to a glycerol backbone, and their value and functionality are largely determined by their fatty acid composition. Hence, enhancing the fatty acid profile of plant oils is a primary focus for improving their economic and practical potential. Phosphatidylcholine: Diacylglycerol Cholinephosphotransferase (PDCT), encoded by the REDUCED OLEATE DESATURATION1 (ROD1) gene in Arabidopsis thaliana, catalyzes the interconversion between phosphatidylcholine, the site of fatty acid modification, and diacylglycerol, the precursor of TAG assembly. PDCT plays a key role in determining the fatty acid composition and quality of oils, making it an attractive target for engineering crops with tailored oil profiles. This review systematically examines the biochemical, genetic, and molecular biology research on PDCT over the past decades, focusing on its phylogeny, physiological roles, regulation, biochemical characterization, structural features, and biotechnological applications. We also analyze the predicted structure of PDCT, which suggests a domain-swapped homodimer configuration based on AlphaFold3 modeling, and we discuss potential catalytic mechanisms. Finally, we highlight key open questions in the field and propose future research directions.
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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) | 0.000 | 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 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".