Transgenic increases in seed oil content are associated with the differential expression of novel Brassica-specific transcripts
Bibliographic record
Abstract
BACKGROUND: Seed oil accumulates primarily as triacylglycerol (TAG). While the biochemical pathway for TAG biosynthesis is known, its regulation remains unclear. Previous research identified microsomal diacylglycerol acyltransferase 1 (DGAT1, EC 2.3.1.20) as controlling a rate-limiting step in the TAG biosynthesis pathway. Of note, overexpression of DGAT1 results in substantial increases in oil content and seed size. To further analyze the global consequences of manipulating DGAT1 levels during seed development, a concerted transcriptome and metabolome analysis of transgenic B. napus prototypes was performed. RESULTS: Using a targeted Brassica cDNA microarray, about 200 genes were differentially expressed in two independent transgenic lines analyzed. Interestingly, 24-33% of the targets showing significant changes have no matching gene in Arabidopsis although these represent only 5% of the targets on the microarray. Further analysis of some of these novel transcripts indicated that several are inducible by ABA in microspore-derived embryos. Of the 200 Arabidopsis genes implicated in lipid biology present on the microarray, 36 were found to be differentially regulated in DGAT transgenic lines. Furthermore, kinetic reverse transcriptase Polymerase Chain Reaction (k-PCR) analysis revealed up-regulation of genes encoding enzymes of the Kennedy pathway involved in assembly of TAGs. Hormone profiling indicated that levels of auxins and cytokinins varied between transgenic lines and untransformed controls, while differences in the pool sizes of ABA and catabolites were only observed at later stages of development. CONCLUSION: Our results indicate that the increased TAG accumulation observed in transgenic DGAT1 plants is associated with modest transcriptional and hormonal changes during seed development that are not limited to the TAG biosynthesis pathway. These might be associated with feedback or feed-forward effects due to altered levels of DGAT1 activity. The fact that a large fraction of significant amplicons have no matching genes in Arabidopsis compromised our ability to draw concrete inferences from the data at this stage, but has led to the identification of novel genes of potential interest.
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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".