RNA viruses that exploit self-cleaving ribozymes for translation initiation
Bibliographic record
Abstract
Abstract Small self-cleaving ribozymes are catalytic RNAs originally discovered in viroid-like agents, which are replicating circular RNAs (circRNAs) postulated as relics of a prebiotic RNA world. In the last decade, however, small ribozymes have also been detected across the tree of life, from bacterial to human genomes, and more recently, in unusual circRNA viruses. Here we report the conserved occurrence of diverse small ribozymes within the linear genomes of typical double- and single-stranded RNA virus families from fungi and plants. Type I hammerhead ribozyme motifs occur in the 5’-UTR regions of chrysovirids and fusarivirids, displaying self-cleaving activity in vitro and in vivo . Similar hammerhead, as well as hepatitis delta and twister ribozymes, are also found in diverse megabirna-, hypo-, fusagra-, toti-or tombus-like viruses among others. The ribozymes occur not only as isolated motifs within UTRs but also as tandem pairs that encompass small RNA segments (186-399 nt) resembling Zetavirus-like sequences. In vivo characterization of the 5’-UTR with a ribozyme from a chrysovirid revealed that the RNA-cleaving activity is essential for protein translation initiation in fungi. Analogous experiments in plants with diverse ribozyme motifs indicated that just the presence of a self-cleaving activity can induce cap-independent translation. We conclude that RNA self-cleaving activity, historically linked to the rolling circle replication of viroid-like circRNAs, appears to be co-opted by linear RNA viruses for translational roles.
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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".