Mechanistic insights on the Dicer-independent AGO2-mediated processing of AgoshRNAs
Bibliographic record
Abstract
Short hairpin RNAs (shRNAs) are widely used for gene knockdown by inducing the RNA interference (RNAi) mechanism, both for research and therapeutic purposes. The shRNA precursor is processed by the RNase III-like enzyme Dicer into biologically active small interfering RNA (siRNA). This effector molecule subsequently targets a complementary mRNA for destruction via the Argonaute 2 (AGO2) complex. The cellular role of Dicer concerns the processing of pre-miRNAs into mature microRNA (miRNA). Recently, a non-canonical pathway was reported for the biogenesis of miR-451, which bypasses Dicer and is processed instead by the slicer activity of AGO2, followed by the regular AGO2-mediated mRNA targeting step. Interestingly, shRNA designs that are characterized by a relatively short basepaired stem also bypass Dicer to be processed by AGO2. We named this design AgoshRNA as these molecules depend on AGO2 both for processing and silencing activity. In this study, we investigated diverse mechanistic aspects of this new class of AgoshRNA molecules. We probed the requirements for AGO2-mediated processing of AgoshRNAs by modification of the proposed cleavage site in the hairpin. We demonstrate by deep sequencing that AGO2-processed AgoshRNAs produce RNA effector molecules with more discrete ends than the products of the regular shRNA design. Furthermore, we tested whether trimming and tailing occurs upon AGO2-mediated processing of AgoshRNAs, similar to what has been described for miR-451. Finally, we tested the prediction that AgoshRNA activity, unlike that of regular shRNAs, is maintained in Dicer-deficient cell types. These mechanistic insights could aid in the design of optimised AgoshRNA tools and 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".