Re-analysis of genome wide data on mammalian microRNA-mediated suppression of gene expression
Bibliographic record
Abstract
microRNAs are short endogenously expressed RNAs that regulate gene expression post-transcriptionally. Although both mRNA degradation and suppression of mRNA translation can mediate reduced protein levels following microRNA targeting of an mRNA, their relative contributions have remained elusive. A recent genome-wide study in mammals employing RNA-sequencing to measure microRNA effects on mRNA translation and stability concluded that 84-89% of microRNA-induced suppression of gene expression is due to degradation of target mRNAs. We re-analyzed this data set and applied a number of analysis modifications which revealed that the contribution of mRNA translation was likely underestimated for some mRNA subsets. Moreover, in contrast to the original analysis, our analysis indicated that suppression of mRNA translation precedes mRNA degradation upon microRNA targeting. Our findings thereby enhance our understanding of microRNA mediated genome wide suppression of gene expression in mammals.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".