Structure and Expression of Mobile ETnII Retroelements and Their Coding-Competent MusD Relatives in the Mouse
Bibliographic record
Abstract
ETnII elements are mobile members of the repetitive early transposon family of mouse long terminal repeat (LTR) retroelements and have caused a number of mutations by inserting into genes. ETnII sequences lack retroviral genes, but the recent discovery of related MusD retroviral elements with regions similar to gag, pro, and pol suggests that MusD provides the proteins necessary for ETnII transposition in trans. For this study, we analyzed all ETnII elements in the draft sequence of the C57BL/6J genome and classified them into three subtypes (alpha, beta, and gamma) based on structural differences. We then used database searches and quantitative real-time PCR to determine the copy number and expression of ETnII and MusD elements in various mouse strains. In 7.5-day-old embryos of a mouse strain in which two mutations due to ETnII-beta insertions have been identified (SELH/Bc), we detected a three- to sixfold higher level of ETnII-beta and MusD transcripts than in control strains (C57BL/6J and LM/Bc). The increased ETnII transcription level can in part be attributed to a higher number of ETnII-beta elements, but 70% of the MusD transcripts appear to have been derived from one or a few MusD elements that are not detectable in C57BL/6J mice. This element belongs to a young MusD subgroup with intact open reading frames and identical LTRs, suggesting that the overexpressed element(s) in SELH/Bc mice might provide the proteins for the retrotransposition of ETnII and MusD elements. We also show that ETnII is expressed up to 30-fold more than MusD, which could explain why only ETnII, but not MusD, elements have been positively identified as new insertions.
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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 | 0.001 | 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 | 0.000 |
| 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".