Comparative Transcriptomics Reveals an Extracellular Worm Argonaute as an Ancestral Regulator of LTR Retrotransposons
Bibliographic record
Abstract
Safeguarding the genome from non-self-elements is essential for development, reproduction, and aging. One of the major threats to genomic integrity is transposable elements (TEs), which can be post-transcriptionally silenced through small RNAs (sRNAs) and argonaute proteins. Recent work suggests TE-derived sRNAs may also act as virulence factors in host-pathogen interactions. During infection, the intestinal parasite Heligmosomoides bakeri secretes a single argonaute protein (exWAGO) and a wide variety of TE-derived sRNAs. Although exWAGO is highly expressed, conserved, and secreted by parasitic nematodes, its function and sRNA guide preference remain unclear. Using comparative transcriptomics of the sRNAs bound to exWAGO within parasites of rodents, livestock, and humans, and its orthologs in C. elegans, we found that exWAGO is capable of loading sRNAs produced from all classes of TEs in addition to some protein-coding and noncoding transcripts. However, our results suggest that the ancestral endogenous function of exWAGO was likely linked to LTR retrotransposon regulation. To understand how this relates to potential extracellular functions of exWAGO, we also examined the sRNAs bound to exWAGO secreted by H. bakeri in both vesicular and nonvesicular forms. Extracellular exWAGO preferentially loads sRNA guides derived from nonautonomous and fragmented LTRs, suggesting the existence of adaptable reservoirs of regulatory sRNAs with potential roles in cross-species RNA communication. Together, our results show that exWAGO is part of an evolutionarily conserved pathway for LTR retrotransposon regulation, while preferentially utilizing degenerated elements as sources of secreted sRNAs.
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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 | 0.000 |
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".