Depletion of <i>Kcnq1ot1</i> non-coding RNA does not affect imprinting maintenance in stem cells
Bibliographic record
Abstract
To understand the complex regulation of genomic imprinting it is important to determine how early embryos establish imprinted gene expression across large chromosomal domains. Long non-coding RNAs (ncRNAs) have been associated with the regulation of imprinting domains, yet their function remains undefined. Here, we investigated the mouse Kcnq1ot1 ncRNA and its role in imprinted gene regulation during preimplantation development by utilizing mouse embryonic and extra-embryonic stem cell models. Our findings demonstrate that the Kcnq1ot1 ncRNA extends 471 kb from the transcription start site. This is significant as it raises the possibility that transcription through downstream genes might play a role in their silencing, including Th, which we demonstrate possesses maternal-specific expression during early development. To distinguish between a functional role for the transcript and properties inherent to transcription of long ncRNAs, we employed RNA interference-based technology to deplete Kcnq1ot1 transcripts. We hypothesized that post-transcriptional depletion of Kcnq1ot1 ncRNA would lead to activation of normally maternal-specific protein-coding genes on the paternal chromosome. Post-transcriptional short hairpin RNA-mediated depletion in embryonic stem, trophoblast stem and extra-embryonic endoderm stem cells had no observable effect on the imprinted expression of genes within the domain, or on Kcnq1ot1 imprinting center DNA methylation, although a significant decrease in Kcnq1ot1 RNA signal volume in the nucleus was observed. These data support the argument that it is the act of transcription that plays a role in imprint maintenance during early development rather than a post-transcriptional role for the RNA itself.
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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 | 0.001 |
| 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".