Data from: miR-122, small RNA annealing and sequence mutations alter the predicted structure of the Hepatitis C virus 5′ UTR RNA to stabilize and promote viral RNA accumulation
Bibliographic record
Abstract
Annealing of the liver-specific microRNA, miR-122, to the Hepatitis C virus (HCV) 5′ UTR is required for efficient virus replication. By using siRNAs to pressure escape mutations, 30 replication-competent HCV genomes having nucleotide changes in the conserved 5′ untranslated region (UTR) were identified. In silico analysis predicted that miR-122 annealing induces canonical HCV genomic 5′ UTR RNA folding, and mutant 5′ UTR sequences that promoted miR-122-independent HCV replication favored the formation of the canonical RNA structure, even in the absence of miR-122. Additionally, some mutant viruses adapted to use the siRNA as a miR-122-mimic. We further demonstrate that small RNAs that anneal with perfect complementarity to the 5′ UTR stabilize and promote HCV genome accumulation. Thus, HCV genome stabilization and life-cycle promotion does not require the specific annealing pattern demonstrated for miR-122 nor 5′ end annealing or 3′ overhanging nucleotides. Replication promotion by perfect-match siRNAs was observed in Ago2 knockout cells revealing that other Ago isoforms can support HCV replication. At last, we present a model for miR-122 promotion of the HCV life cycle in which miRNA annealing to the 5′ UTR, in conjunction with any Ago isoform, modifies the 5′ UTR structure to stabilize the viral genome and promote HCV RNA accumulation.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.043 |
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".