Improved T-DNA vector for Tagging Plant Promoters via High-Throughput Luciferase Screening
Bibliographic record
Abstract
Transferred DNA (T-DNA) tagging is a powerful tool for tagging and in planta characterization of plant genes on a genome-wide scale. An improved promoter tagging vector is described here, which contains the codon-optimized luciferase (luc+) reporter gene 31 bp from the right border of the T-DNA. Compared to the wild-type luciferase gene, this construct provides significantly increased reporter gene expression and a 40 times higher tagging frequency. The utility of the construct is demonstrated in banana, a tropical monocot species, by screening embryogenic cell colonies and regenerated plants with an ultrasensitive charged-coupled device (CCD) camera. The improved vector resulted in a luciferase activation frequency of 2.5% in 19,000 cell colonies screened. Detailed molecular analysis of flanking DNA sequences in a tagged line revealed insertion of the luciferase tag in a novel gene with near-constitutive expression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".