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Record W3135340662 · doi:10.1101/2021.03.03.433635

Contribution of epigenetic changes to escape from X-chromosome inactivation

2021· preprint· en· W3135340662 on OpenAlexafffund
Bradley P. Balaton, Carolyn J. Brown

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchGenome British Columbia
KeywordsX-inactivationEpigeneticsDNA methylationBiologyGeneticsHeterochromatinChromatinGeneHistoneX chromosomeGene expression

Abstract

fetched live from OpenAlex

Abstract Background X-chromosome inactivation (XCI) is the epigenetic inactivation of one of two X chromosomes in XX eutherian mammals. The facultatively heterochromatic inactive X chromosome acquires many chromatin changes including DNA methylation and histone modifications. Despite these changes, some genes escape or variably escape from inactivation, and to the extent that they have been studied, epigenetic marks correlate with expression. Results We downloaded data from the International Human Epigenome Consortium and compared previous XCI status calls to DNA methylation, H3K4me1, H3K4me3, H3K9me3, H3K27ac, H3K27me3 and H3K36me3. At genes subject to XCI we found heterochromatic marks enriched, and euchromatic marks depleted on the inactive X when compared to the active X. Similar results were seen for genes escaping XCI although with diminished effect with H3K27me3 being most enriched. Using sample-specific XCI status calls made using allelic expression or DNA methylation we also compared differences between samples with opposite XCI statuses at variably escaping genes. We found some marks significantly differed with XCI status, but which marks were significant was not consistent between genes. We trained a model to predict XCI status from these epigenetic marks and obtained over 75% accuracy for genes escaping and over 90% for genes subject to XCI. This model allowed us to make novel XCI status calls for genes without allelic differences or CpG islands required for other XCI status calling methods. Using these calls to examine a domain of variably escaping genes, we saw XCI status vary at the level of individual genes and not at the domain level. Conclusion Here we show that epigenetic marks differ between genes that are escaping and those subject to XCI, and that genes escaping XCI still differ between the active and inactive Xs. We show epigenetic differences at variably escaping genes, between samples escaping and those subject to XCI. Lastly we show gene-level regulation of variably escaping genes within a domain.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicGenetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities→French-language works237,207→