Site‐specific <scp>T</scp> – <scp>DNA</scp> integration in <i> <scp>A</scp> rabidopsis thaliana </i> mediated by the combined action of <scp>CRE</scp> recombinase and ϕ <scp>C</scp> 31 integrase
Bibliographic record
Abstract
Random T-DNA integration into the plant host genome can be problematic for a variety of reasons, including potentially variable transgene expression as a result of different integration positions and multiple T-DNA copies, the risk of mutating the host genome and the difficulty of stacking well-defined traits. Therefore, recombination systems have been proposed to integrate the T-DNA at a pre-selected site in the host genome. Here, we demonstrate the capacity of the ϕC31 integrase (INT) for efficient targeted T-DNA integration. Moreover, we show that the iterative site-specific integration system (ISSI), which combines the activities of the CRE recombinase and INT, enables the targeting of genes to a pre-selected site with the concomitant removal of the resident selectable marker. To begin, plants expressing both the CRE and INT recombinase and containing the target attP site were constructed. These plants were supertransformed with a T-DNA vector harboring the loxP site, the attB sites, a selectable marker and an expression cassette encoding a reporter protein. Three out of the 35 transformants obtained (9%) showed transgenerational site-specific integration (SSI) of this T-DNA and removal of the resident selectable marker, as demonstrated by PCR, Southern blot and segregation analysis. In conclusion, our results show the applicability of the ISSI system for precise and targeted Agrobacterium-mediated integration, allowing the serial integration of transgenic DNA sequences in plants.
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) | 0.001 | 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 | 0.001 |
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".