Toward optimization of AgoshRNA moleculesthat use a non-canonical RNAi pathway: Variations in the top and bottom base pairs
Bibliographic record
Abstract
Short hairpin RNAs (shRNAs) are widely used for gene knockdown by inducing the RNA interference (RNAi) mechanism. The shRNA precursor is processed by Dicer into small interfering RNAs (siRNAs) and subsequently programs the RNAi-induced silencing complex (RISC) to find a complementary target mRNA (mRNA) for post-transcriptional gene silencing. Recent evidence indicates that shRNAs with a relatively short basepaired stem bypass Dicer to be processed directly by the Ago2 nuclease of the RISC complex. We named this design AgoshRNA as these molecules depend on Ago2 both for processing and subsequent silencing activity. This alternative AgoshRNA processing route yields only a single active RNA strand, an important feature to restrict off-target effects induced by the passenger strand of regular shRNAs. It is therefore important to understand this novel AgoshRNA processing route in mechanistic detail such that one can design the most effective and selective RNA reagents. We performed a systematic analysis of the optimal base pair (bp) composition at the top and bottom of AgoshRNA molecules. In this study, we document the importance of the 5' end nucleotide (nt) and a bottom mismatch. The optimized AgoshRNA design exhibits improved RNAi activity across cell types. These results have important implications for the future design of more specific RNAi therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".