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Record W2001319731 · doi:10.1073/pnas.1418845112

Haploinsufficiency screen highlights two distinct groups of ribosomal protein genes essential for embryonic stem cell fate

2015· article· en· W2001319731 on OpenAlexafffund
Simon Fortier, Tara MacRae, Mélanie Bilodeau, Tobias Sargeant, Guy Sauvageau

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsHaploinsufficiencyEmbryonic stem cellBiologyGeneStem cellGeneticsRibosomal proteinPhenotypeRibosomeRNA

Abstract

fetched live from OpenAlex

In a functional genomics screen of mouse embryonic stem cells (ESCs) with nested hemizygous chromosomal deletions, we reveal that ribosomal protein (RP) genes are the most significant haploinsufficient determinants for embryoid body (EB) formation. Hemizygocity for three RP genes (Rps5, Rps14, or Rps28), distinguished by the proximity of their corresponding protein to the ribosome's mRNA exit site, is associated with the most profound phenotype. This EB phenotype was fully rescued by BAC or cDNA complementation but not by the reduction of p53 levels, although such reduction was effective with most other RP-deleted clones corresponding to non-mRNA exit-site proteins. RNA-sequencing studies further revealed that undifferentiated ESCs hemizygous for Rps5 showed reduced expression levels of several mesoderm-specific genes as compared with wild-type counterparts. Together, these results reveal that RP gene dosage limits the differentiation, not the self-renewal, of mouse ESCs. They also highlight two separate mechanisms underlying this process, one of which is p53 independent.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.308
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2015
Admission routes2
Has abstractyes

Explore more

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