Genetic screening of long non-coding RNAs in human embryonic stem cells reveals novel regulators of pluripotency
Bibliographic record
Abstract
The human genome encodes thousands of long non-coding RNAs (lncRNAs), transcripts of over 200 nucleotides that lack protein-coding potential. lncRNAs are emerging as key players in diverse cellular processes, particularly in tissue-specific contexts, yet their functionality remained poorly understood. Here, we performed a CRISPR interference (CRISPRi) screen in human embryonic stem cells (hESCs), identifying over 100 essential and about 150 growth-restricting lncRNAs. We show that growth-modifying lncRNAs display distinctive properties, including unique expression signatures, genomic structure, evolutionary conservation, chromosomal distribution, and potential involvement in teratoma formation. Notably, we uncovered two primate-conserved, uncharacterized, essential lncRNAs that regulate neighboring pluripotency transcription factors: lncOCT4, which positively regulates OCT4 and induces p53-mediated apoptosis upon knockdown, and lncVRTN, which acts as a putative negative regulator of VRTN, affecting cell fate determination. These findings shed light on the contribution of lncRNAs to the human-specific pluripotency network and provide insights into lncRNA-mediated regulation of hESC growth and differentiation.
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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 | 0.001 | 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".