Atypical RNA Elements Modulate Translational Readthrough in Tobacco Necrosis Virus D
Bibliographic record
Abstract
ABSTRACT Tobacco necrosis virus, strain D (TNV-D), is a positive-strand RNA virus in the genus Betanecrovirus and family Tombusviridae . The production of its RNA-dependent RNA polymerase, p82, is achieved by translational readthrough. This process is stimulated by an RNA structure that is positioned immediately downstream of the recoding site, termed the readthrough stem-loop (RTSL), and a sequence in the 3′ untranslated region of the TNV-D genome, called the distal readthrough element (DRTE). Notably, a base pairing interaction between the RTSL and the DRTE, spanning ∼3,000 nucleotides, is required for enhancement of readthrough. Here, some of the structural features of the RTSL, as well as RNA sequences and structures that flank either the RTSL or DRTE, were investigated for their involvement in translational readthrough and virus infectivity. The results revealed that (i) the RTSL-DRTE interaction cannot be functionally replaced by stabilizing the RTSL structure, (ii) a novel tertiary RNA structure positioned just 3′ to the RTSL is required for optimal translational readthrough and virus infectivity, and (iii) these same activities also rely on an RNA stem-loop located immediately upstream of the DRTE. Functional counterparts for the RTSL-proximal structure may also be present in other tombusvirids. The identification of additional distinct RNA structures that modulate readthrough suggests that regulation of this process by genomic features may be more complex than previously appreciated. Possible roles for these novel RNA elements are discussed. IMPORTANCE The analysis of factors that affect recoding events in viruses is leading to an ever more complex picture of this important process. In this study, two new atypical RNA elements were shown to contribute to efficient translational readthrough of the TNV-D polymerase and to mediate robust viral genome accumulation in infections. One of the structures, located close to the recoding site, could have functional equivalents in related genera, while the other structure, positioned 3′ proximally in the viral genome, is likely limited to betanecroviruses. Irrespective of their prevalence, the identification of these novel RNA elements adds to the current repertoire of viral genome-based modulators of translational readthrough and provides a notable example of the complexity of regulation of this 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".