Molecular modification of triacylglycerol accumulation by over-expression of<i>DGAT1</i>to produce canola with increased seed oil content under field conditionsThis paper is one of a selection of papers published in a Special Issue from the National Research Council of Canada – Plant Biotechnology Institute.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The final step in the Kennedy pathway for seed oil synthesis is catalyzed by an acyl-CoA-dependent diacylglycerol acyltransferase, DGAT1 (EC. 2.3.1.20). We have cloned DGAT1 genes from both Arabidopsis thaliana (L.) Heynh ecotype Columbia and Brassica napus ‘Jet Neuf’ and over-expressed them in canola under the control of the seed-specific promoter, napin. DGAT1 from A. thaliana was inserted into B. napus ‘Quantum,’ whereas DGAT1 from B. napus was introduced into the B. napus double haploid breeding line DH12075. Both sets of transgenic plants exhibited increased seed oil content in both greenhouse and in field trial settings, ranging from 2.5% to 7% of dried mass on an absolute basis. The ‘Quantum’ transgenic lines were field-tested in plots at Watrous, Saskatchewan, in 2006 and 2007. Larger scale field trials of the DH12075 transgenics were carried out in 2007 at Ellerslie and Vegreville, Alberta. This is the first study wholly dedicated to DGAT1 over-expression and the resultant oil-content increases in transgenic canola under field conditions. Collectively, the field trial results strongly support the hypothesis that the level of DGAT1 activity during seed development in an oilseed crop can have a substantial effect on the flow of carbon into seed oil. Therefore, the over-expression of DGAT1 is a positive strategy for increasing oil content and cultivar performance in canola.
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.
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 | 0.001 | 0.001 |
| 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 it