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Record W2587651673 · doi:10.1016/j.celrep.2017.01.034

Chromatin States in Mouse Sperm Correlate with Embryonic and Adult Regulatory Landscapes

2017· article· en· W2587651673 on OpenAlexafffund
Yoon Hee Jung, Michael E.G. Sauria, Xiaowen Lyu, Manjinder S. Cheema, Juan Ausió, James Taylor, Victor G. Corces

Bibliographic record

VenueCell Reports · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsUniversity of Victoria
FundersNational Human Genome Research InstituteNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsCTCFCohesinBiologyEnhancerSpermChromatinEmbryonic stem cellCell biologyHistoneGeneticsGermlineGenomeGeneTranscription factor

Abstract

fetched live from OpenAlex

The mammalian sperm genome is thought to lack substantial information for the regulation of future expression after fertilization. Here, we show that most promoters in mouse sperm are flanked by well-positioned nucleosomes marked by active histone modifications. Analysis of these modifications suggests that many enhancers and super-enhancers functional in embryonic and adult tissues are already specified in sperm. The sperm genome is bound by CTCF and cohesin at sites that are also present in round spermatids and embryonic stem cells (ESCs). These sites mediate interactions that organize the sperm genome into domains and compartments that overlap extensively with those found in mESCs. These results suggest that sperm carry a rich source of regulatory information, encoded in part by its three-dimensional folding specified by CTCF and cohesin. This information may contribute to future expression during embryonic and adult life, suggesting mechanisms by which environmental effects on the paternal germline are transmitted transgenerationally.

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: Observational · Consensus signal: none
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 head0.003
GPT teacher head0.189
Teacher spread0.186 · 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 designObservational
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

Citations304
Published2017
Admission routes2
Has abstractyes

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