Tung Tree DGAT1 and DGAT2 Have Nonredundant Functions in Triacylglycerol Biosynthesis and Are Localized to Different Subdomains of the Endoplasmic Reticulum
Bibliographic record
Abstract
Seeds of the tung tree (Vernicia fordii) produce large quantities of triacylglycerols (TAGs) containing approximately 80% eleostearic acid, an unusual conjugated fatty acid. We present a comparative analysis of the genetic, functional, and cellular properties of tung type 1 and type 2 diacylglycerol acyltransferases (DGAT1 and DGAT2), two unrelated enzymes that catalyze the committed step in TAG biosynthesis. We show that both enzymes are encoded by single genes and that DGAT1 is expressed at similar levels in various organs, whereas DGAT2 is strongly induced in developing seeds at the onset of oil biosynthesis. Expression of DGAT1 and DGAT2 in yeast produced different types and proportions of TAGs containing eleostearic acid, with DGAT2 possessing an enhanced propensity for the synthesis of trieleostearin, the main component of tung oil. Both DGAT1 and DGAT2 are located in distinct, dynamic regions of the endoplasmic reticulum (ER), and surprisingly, these regions do not overlap. Furthermore, although both DGAT1 and DGAT2 contain a similar C-terminal pentapeptide ER retrieval motif, this motif alone is not sufficient for their localization to specific regions of the ER. These data suggest that DGAT1 and DGAT2 have nonredundant functions in plants and that the production of storage oils, including those containing unusual fatty acids, occurs in distinct ER subdomains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".