Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells
Bibliographic record
Abstract
Recently, a handful of intergenic long noncoding RNAs (lncRNAs) have been shown to compete with mRNAs for binding to miRNAs and to contribute to development and disease. Beyond these reports, little is yet known of the extent and functional consequences of miRNA-mediated regulation of mRNA levels by lncRNAs. To gain further insight into lncRNA-mRNA miRNA-mediated crosstalk, we reanalyzed transcriptome-wide changes induced by the targeted knockdown of over 100 lncRNA transcripts in mouse embryonic stem cells (mESCs). We predicted that, on average, almost one-fifth of the transcript level changes induced by lncRNAs are dependent on miRNAs that are highly abundant in mESCs. We validated these findings experimentally by temporally profiling transcriptome-wide changes in gene expression following the loss of miRNA biogenesis in mESCs. Following the depletion of miRNAs, we found that >50% of lncRNAs and their miRNA-dependent mRNA targets were up-regulated coordinately, consistent with their interaction being miRNA-mediated. These lncRNAs are preferentially located in the cytoplasm, and the response elements for miRNAs they share with their targets have been preserved in mammals by purifying selection. Lastly, miRNA-dependent mRNA targets of each lncRNA tended to share common biological functions. Post-transcriptional miRNA-mediated crosstalk between lncRNAs and mRNA, in mESCs, is thus surprisingly prevalent, conserved in mammals, and likely to contribute to critical developmental processes.
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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 | 0.000 |
| 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) | 0.001 | 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".