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Record W4220661883 · doi:10.1016/j.celrep.2022.110573

Genome-wide analysis of haploinsufficiency in human embryonic stem cells

2022· article· en· W4220661883 on OpenAlexfundno aff
Roni Sarel-Gallily, Tamar Golan‐Lev, Atilgan Yilmaz, Ido Sagi, Nissim Benvenisty

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science FoundationRosetrees Trust
KeywordsHaploinsufficiencyBiologyEmbryonic stem cellGeneticsPhenotypeGeneTelomereCell biology

Abstract

fetched live from OpenAlex

Haploinsufficiency describes a phenomenon where one functioning allele is insufficient for a normal phenotype, underlying several human diseases. The effect of haploinsufficiency on human embryonic stem cells (hESC) has not been thoroughly studied. To establish a genome-wide loss-of-function screening for heterozygous mutations, we fuse normal haploid hESCs with a library of mutant haploid hESCs. We identify over 600 genes with a negative effect on hESC growth in a haploinsufficient manner and characterize them as genes showing less tolerance to mutations, conservation during evolution, and depletion from telomeres and X chromosome. Interestingly, a large fraction of these genes is associated with extracellular matrix and plasma membrane and enriched for genes within WNT and TGF-β pathways. We thus identify haploinsufficiency-related genes that show growth retardation in early embryonic cells, suggesting dosage-dependent phenotypes in hESCs. Overall, we construct a unique model for studying haploinsufficiency and identified important dosage-dependent pathways involved in hESC growth and survival.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2022
Admission routes1
Has abstractyes

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