Transient down‐regulation of the <scp>RNA</scp> silencing machinery increases efficiency of <i><scp>A</scp>grobacterium</i>‐mediated transformation of <scp>A</scp>rabidopsis
Bibliographic record
Abstract
Agrobacterium tumefaciens is a plant pathogen that is widely used in plant transformation. As the process of transgenesis includes the delivery of single-stranded T-DNA molecule, we hypothesized that transformation rate may negatively correlate with the efficiency of the RNA-silencing machinery. Using mutants compromised in either the transcriptional or post-transcriptional gene-silencing pathways, two inhibitors of stable transformation were revealed-AGO2 and NRPD1a. Furthermore, an immunoprecipitation experiment has shown that NRPD1, a subunit of Pol IV, directly interacts with Agrobacterium T-DNA in planta. Using the Tobacco rattle virus (TRV)--based virus-induced gene silencing (VIGS) technique, we demonstrated that the transient down-regulation of the expression of either AGO2 or NRPD1a genes in reproductive organs of Arabidopsis, leads to an increase in transformation rate. We observed a 6.0- and 3.5-fold increase in transformation rate upon transient downregulation of either AGO2 or NRPD1a genes, respectively. This is the first report demonstrating the increase in the plant transformation rate via VIGS-mediated transient down-regulation of the components of epigenetic machinery in reproductive tissue.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".