HENMT1 restricts endogenous retrovirus activity by methylation of 3’-tRNA fragments
Bibliographic record
Abstract
ABSTRACT Long terminal repeat (LTR) retroelements such as endogenous retroviruses (ERVs) utilize host tRNA as a primer for reverse transcription, and are thus susceptible to silencing by small RNAs derived from the 3′-end of mature tRNAs (3′-tRFs). Rigorous quantification reveals that 3’-tRF amounts are not directly proportional to tRNA levels, instead, 3’-tRFs of specific isodecoder tRNAs are highly enriched in a pattern conserved between mouse and human. We found that 3’-tRFs are 2’-O methylated by the small RNA methyltransferase HENMT1 protecting them from degradation and promoting ERV silencing. In the absence of HENMT1, 3’-tRFs are subjected to non-templated tailing by the terminal nucleotidyltransferases TUT4 and TENT2 that regulate small RNA turnover. Due to the perfect sequence complementarity of 3’-tRFs to endogenous retroviral sequences, they have thousands of targets in mammalian genomes. We conducted a massively parallel reporter assay using Mus musculus particle type D , a highly active murine ERV, to determine target site rules for 3’-tRFs. Our results suggest that HENMT1 not only stabilizes germline integrity but also serves transposon control by 3’-tRFs in the soma.
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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 | 0.000 | 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 | 0.000 |
| 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".