Internal translation initiation from HIV-1 transcripts is conferred by a common RNA structure
Bibliographic record
Abstract
Alternative splicing of the human immunodeficiency virus 1 (HIV-1) RNA transcripts produces mRNAs encoding nine different viral proteins. The leader of each contains a common non-coding exon at the 5' end. Previous studies showed that the leaders from the common exon-containing transcripts gag, nef, vif, vpr and vpu can direct protein synthesis through internal ribosome entry sites (IRESs) with varying efficiencies. Here we explored whether the common exon acts as an IRES element in the context of all the 5' leaders or if each harbors a distinct IRES. We also explored the relationship between the IRESs and initiation codon selection. We find that the common exon adopts a similar conformation in every leader we explored and that the sequence and structure is required for IRES activity. We also find that each leader uses a scanning mechanism for start codon identification. Together, our data point to a model in which the common exon on HIV-1 transcripts acts as the ribosome landing pad, recruiting preinitiation complexes upstream of the initiation codon, followed by scanning to each transcript's initiator AUG.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".