Essential Gene Profiles for Human Pluripotent Stem Cells Identify Uncharacterized Genes and Substrate Dependencies
Bibliographic record
Abstract
Human pluripotent stem cells (hPSCs) provide an invaluable tool for modeling diseases and hold promise for regenerative medicine. For understanding pluripotency and lineage differentiation mechanisms, a critical first step involves systematically cataloging essential genes (EGs) that are indispensable for hPSC fitness, defined as cell reproduction in this study. To map essential genetic determinants of hPSC fitness, we performed genome-scale loss-of-function screens in an inducible Cas9 H1 hPSC line cultured on feeder cells and laminin to identify EGs. Among these, we found FOXH1 and VENTX, genes that encode transcription factors previously implicated in stem cell biology, as well as an uncharacterized gene, C22orf43/DRICH1. hPSC EGs are substantially different from other human model cell lines, and EGs in hPSCs are highly context dependent with respect to different growth substrates. Our CRISPR screens establish parameters for genome-wide screens in hPSCs, which will facilitate the characterization of unappreciated genetic regulators of hPSC biology.
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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 | 0.001 | 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) | 0.002 | 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".