A Multicomponent RNA-Based Control System Regulates Subgenomic mRNA Transcription in a Tombusvirus
Bibliographic record
Abstract
During infections, positive-strand RNA tombusviruses transcribe two subgenomic (sg) mRNAs that allow for the expression of a subset of their genes. This process is thought to involve an unconventional mechanism involving the premature termination of the virally encoded RNA-dependent RNA polymerase while it is copying the virus genome. The 3' truncated minus strands generated by termination are then used as templates for sg mRNA transcription. In addition to requiring an extensive network of long-distance RNA-RNA interactions (H.-X. Lin and K. A. White, EMBO J. 23:3365-3374, 2004), the transcription of tombusvirus sg mRNAs also involves several additional RNA structures. In vivo analysis of these diverse RNA elements revealed that they function at distinct steps in the process by facilitating the formation or stabilization of the long-distance interactions, modulating minus-strand template production, or promoting the initiation of sg mRNA transcription. All of the RNA elements characterized could be readily incorporated into a premature termination model for sg mRNA transcription. Overall, the analyses revealed a complex system that displays a high level of structural integration and functional coordination. This multicomponent RNA-based control system may serve as a useful paradigm for understanding related transcriptional processes in other positive-sense RNA viruses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".