A novel gene silencing vector for plant genomics and biotechnology
Bibliographic record
Abstract
Gene silencing is a process of suppressing activity of specific genes by producing “interfering” RNA encoded by foreign genes. This process serves as the principle of genetic modification in plants and animals, which is an important tool in genomics and biotechnology, allowing scientists to manipulate organisms to better meet human demands. New approaches of gene silencing may enable improvements on current practices of genetic modification, and broaden the application and impact of gene silencing in biotechnology. Recently, a novel vector design consisting of the transcription of short gene fragments lacking transcription termination signals was demonstrated to be effective in partial silencing of two separate genes in the model plant, Arabidopsis thaliana. To test the efficacy of this unterminated transgene technique on a broader range of genes in A. thaliana, a DNA vector to clone gene fragments was required. The objective of the present study was to design a silencing vector for rapid cloning of gene fragments and test its utility on new genes. Here, we report the successful construction of a simple transgene vector, pSJN15A, for cloning gene fragments, then plant transformation upon Agrobacterium infection. The pSJN15A vector was designed for direct cloning of gene fragments obtained by polymerase chain reaction. Transcription of gene fragments is directed by read-through activity of a hygromycin resistance gene promoter. The pSJN15A vector was used to develop silencing vectors against four new Arabidopsis genes. Thus, pSJN15A serves as an important DNA resource for testing the efficacy of silencing mediated by the transcription of gene fragments in various dicotyledonous plant species.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".