An antisense promoter in mouse L1 retrotransposon open reading frame-1 initiates expression of diverse fusion transcripts and limits retrotransposition
Bibliographic record
Abstract
Between 6 and 30% of human and mouse transcripts are initiated from transposable elements. However, the promoters driving such transcriptional activity are mostly unknown. We experimentally characterized an antisense (AS) promoter in mouse L1 retrotransposons for the first time, oriented antiparallel to the coding strand of L1 open reading frame-1. We found that AS transcription is mediated by RNA polymerase II. Rapid amplification of cDNA ends cloning mapped transcription start sites adjacent to the AS promoter. We identified >100 novel fusion transcripts, of which many were conserved across divergent mouse lineages, suggesting conservation of potential functions. To evaluate whether AS L1 transcription could regulate L1 retrotransposition, we replaced portions of native open reading frame-1 in donor elements by synonymously recoded sequences. The resulting L1 elements lacked AS promoter activity and retrotransposed more frequently than endogenous L1s. Overexpression of AS L1 transcripts also reduced L1 retrotransposition. This suppression of retrotransposition was largely independent of Dicer. Our experiments shed new light on how AS fusion transcripts are initiated from endogenous L1 elements across the mouse genome. Such AS transcription can contribute substantially both to natural transcriptional variation and to endogenous regulation of L1 retrotransposition.
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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 | 0.000 | 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".