Efficacy, accumulation, and transcriptional profile of anti-HIV shRNAs expressed from human U6, 7SK, and H1 promoters
Bibliographic record
Abstract
The expression of short hairpin RNAs (shRNAs) in cells has many potential therapeutic applications, including as a functional cure for HIV. The RNA polymerase III promoters H1, 7SK, and U6 have all been used to express shRNAs. However, there have been no direct and simultaneous comparisons of shRNA potency, expression level, and transcriptional profile between the promoters. We show that the 7SK and U6 promoters result in higher shRNA levels and potency compared to the H1 promoter but that in transduced T lymphocytes, higher expression levels can also lead to growth defects. We present evidence that Dicer cleavage of shRNAs is measured from the first base pair in the shRNA stem, rather than from the 5' end as previously shown for structurally related microRNAs. As a result, guide-strand identity was unaffected by variations in 5' transcription start sites among the different promoters, making expression levels the main determinant of shRNA potency. While all promoters generated shRNAs with variable start sites, the U6 promoter was the most accurate in using its intended +1 position. Our results have implications for the development of therapeutic small RNAs for gene therapy and for our understanding of how shRNAs are processed in cells.
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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 | 0.000 |
| 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 | 0.001 |
| 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".