Development and characterization of marker‐free and transgene insertion site‐defined transgenic wheat with improved grain storability and fatty acid content
Bibliographic record
Abstract
Development of marker-free and transgene insertion site-defined (MFTID) transgenic plants is essential for safe application of transgenic crops. However, MFTID plants have not been reported for wheat (Triticum aestivum). Here, we prepared a RNAi cassette for suppressing lipoxygenase (LOX) gene expression in wheat grains using a double right border T-DNA vector. The resultant construct was introduced into wheat genome via Agrobacterium-mediated transformation, with four homozygous marker-free transgenic lines (namely GLRW-1, -3, -5 and -8) developed. Aided by the newly published wheat genome sequence, the T-DNA insertion sites in GLRW-3 and GLRW-8 were elucidated at base-pair resolution. While the T-DNA in GLRW-3 inserted in an intergenic region, that of GLRW-8 inactivated an endogenous gene, which was thus excluded from further analysis. Compared to wild -type (WT) control, GLRW-1, -3 and -5 showed decreased LOX gene expression, lower LOX activity and less lipid peroxidation in the grains; they also exhibited significantly higher germination rates and better seedling growth after artificial ageing treatment. Interestingly, the three GLRW lines also had substantially increased contents of several fatty acids (e.g., linoleic acid and linolenic acid) in their grain and flour samples than WT control. Collectively, our data suggest that suppression of grain LOX activity can be employed to improve the storability and fatty acid content of wheat seeds and that the MFTID line GLRW-3 is likely of commercial value. Our approach may also be useful for developing the MFTID transgenic lines of other crops with enhanced grain storability and fatty acid content.
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) | 0.000 | 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".