Bibliographic record
Abstract
Epigenetic effects such as gene silencing and variable expression are unintended consequences of plant transformation, a problem that is present in the transformation of all plant species. There is not yet a reliable way to prevent epigenetic silencing; however, the probability of epigenetic effects may be reduced by choosing an appropriate method of transgene introduction into a plant cell. Most methods used in plant biotechnology, such as direct gene transfer and particle bombardment, result in the introduction of multiple DNA molecules and, as a consequence, multi-copy multi-locus insertion patterns. These multiple insertions may lead to variations in transgene expression, epigenetic silencing being the most extreme. In contrast, Agrobacterium-mediated plant transformation procedures rarely cause such unintended effects. In this chapter, we present advantages and disadvantages of the Agrobacterium-mediated plant transformation method as well as protocols for transformation of Arabidopsis generative tissues and tobacco seedlings as the most classical techniques in these model plants, i.e., vacuum infiltration of explants and floral dip methods. Moreover, epigenetic effects of transgenes such as silencing related to the position and insertion effects as well as effects of the regeneration procedure causing somaclonal variation will be briefly discussed.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.029 |
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".