Higher-Order RNA Structural Requirements and Small-Molecule Induction of Tombusvirus Subgenomic mRNA Transcription
Bibliographic record
Abstract
Subgenomic (sg) mRNAs are small viral messages that are synthesized by polycistronic positive-strand RNA viruses to allow for the translation of certain viral proteins. Tombusviruses synthesize two such sg mRNAs via a premature termination mechanism. This transcriptional process involves the viral RNA-dependent RNA polymerase terminating minus-strand RNA synthesis prematurely at internal RNA signals during copying of the viral genome. The 3'-truncated minus-strand RNAs generated by the termination events then serve as templates for sg mRNA transcription. A higher-order RNA structure in the viral genome, located just upstream from the termination site, is a critical component of the RNA-based polymerase attenuation signal. Here, we have analyzed the role of this RNA structure in mediating efficient sg mRNA2 transcription. Our results include the following: (i) we define the minimum overall thermodynamic stability required for an operational higher-order RNA attenuation structure; (ii) we show that the distribution of stability within an attenuation structure affects its function; (iii) we establish that an RNA quadruplex structure can act as an effective attenuation structure; (iv) we prove that the higher-order RNA structure forms and functions in the plus strand; (v) we provide evidence that a specific attenuation structure-binding protein factor is not required for transcription; (vi) we demonstrate that sg mRNA transcription can be controlled artificially through small-molecule activation using RNA aptamer technology. These findings provide important new insights into the premature termination mechanism and present a novel approach to regulate the transcriptional process.
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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".