Genome-Wide Interrogation of Mammalian Stem Cell Fate Determinants by Nested Chromosome Deletions
Bibliographic record
Abstract
Understanding the function of important DNA elements in mammalian stem cell genomes would be enhanced by the availability of deletion collections in which segmental haploidies are precisely characterized. Using a modified Cre-loxP-based system, we now report the creation and characterization of a collection of ∼1,300 independent embryonic stem cell (ESC) clones enriched for nested chromosomal deletions. Mapping experiments indicate that this collection spans over 25% of the mouse genome with good representative coverage of protein-coding genes, regulatory RNAs, and other non-coding sequences. This collection of clones was screened for in vitro defects in differentiation of ESC into embryoid bodies (EB). Several putative novel haploinsufficient regions, critical for EB development, were identified. Functional characterization of one of these regions, through BAC complementation, identified the ribosomal gene Rps14 as a novel haploinsufficient determinant of embryoid body formation. This new library of chromosomal deletions in ESC (DelES: http://bioinfo.iric.ca/deles) will serve as a unique resource for elucidation of novel protein-coding and non-coding regulators of ESC activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".