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Record W3211568008 · doi:10.1038/s41467-021-26949-7

Identifying regulators of parental imprinting by CRISPR/Cas9 screening in haploid human embryonic stem cells

2021· article· en· W3211568008 on OpenAlexfundno aff
Shiran Bar, Dan Vershkov, Gal Keshet, Elyad Lezmi, Naama Meller, Atilgan Yilmaz, Ofra Yanuka, Malka Nissim‐Rafinia, Eran Meshorer, Talia Eldar‐Geva, Nissim Benvenisty

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science FoundationRosetrees Trust
KeywordsGenomic imprintingBiologyImprinting (psychology)CRISPRGeneticsDNA methylationEpigeneticsDifferentially methylated regionsEmbryonic stem cellHistoneGeneGene expression

Abstract

fetched live from OpenAlex

In mammals, imprinted genes are regulated by differentially methylated regions (DMRs) that are inherited from germ cells, leading to monoallelic expression in accordance with parent-of-origin. Yet, it is largely unknown how imprinted DMRs are maintained in human embryos despite global DNA demethylation following fertilization. Here, we explored the mechanisms involved in imprinting regulation by employing human parthenogenetic embryonic stem cells (hpESCs), which lack paternal alleles. We show that although global loss of DNA methylation in hpESCs affects most imprinted DMRs, many paternally-expressed genes (PEGs) remain repressed. To search for factors regulating PEGs, we performed a genome-wide CRISPR/Cas9 screen in haploid hpESCs. This revealed ATF7IP as an essential repressor of a set of PEGs, which we further show is also required for silencing sperm-specific genes. Our study reinforces an important role for histone modifications in regulating imprinted genes and suggests a link between parental imprinting and germ cell identity.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.323
Teacher spread0.298 · 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

Citations23
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNature Communications→Same topicEpigenetics and DNA Methylation→French-language works237,207→