Potential molecular consequences of transgene integration: The R6/2 mouse example
Bibliographic record
Abstract
Integration of exogenous DNA into a host genome represents an important route to generate animal and cellular models for exploration into human disease and therapeutic development. In most models, little is known concerning structural integrity of the transgene, precise site of integration, or its impact on the host genome. We previously used whole-genome and targeted sequencing approaches to reconstruct transgene structure and integration sites in models of Huntington's disease, revealing complex structural rearrangements that can result from transgenesis. Here, we demonstrate in the R6/2 mouse, a widely used Huntington's disease model, that integration of a rearranged transgene with coincident deletion of 5,444 bp of host genome within the gene Gm12695 has striking molecular consequences. Gm12695, the function of which is unknown, is normally expressed at negligible levels in mouse brain, but transgene integration has resulted in cortical expression of a partial fragment (exons 8-11) 3' to the transgene integration site in R6/2. This transcript shows significant expression among the extensive network of differentially expressed genes associated with this model, including synaptic transmission, cell signalling and transcription. These data illustrate the value of sequence-level resolution of transgene insertions and transcription analysis to inform phenotypic characterization of transgenic models utilized in therapeutic research.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".