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Record W4361222884 · doi:10.1016/j.dib.2023.109097

Dataset on DNA methylation and gene expression changes induced by 5-aza-2′-deoxycytidine in Syrian golden hamster fetal cell cultures

2023· article· en· W4361222884 on OpenAlexafffund
Matthew J. Meier, Cathy Cummings‐Lorbetskie, Andrea Rowan‐Carroll, Daniel Desaulniers

Bibliographic record

VenueData in Brief · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsHealth Canada
FundersHealth Canada
KeywordsDeoxycytidineGolden hamsterDNA methylationMethylationGeneDNAMolecular biologyBiologyGeneticsGene expressionFetusCell cultureHamsterPregnancyCancer

Abstract

fetched live from OpenAlex

The Syrian hamster (SH) is an animal model used in virology, toxicology, and carcinogenesis, where a better understanding of epigenetic mechanisms is required. Finding genetic loci regulated by DNA methylation may assist in the development of DNA methylation-based in vitro assays for the identification of carcinogens. This dataset informs on the regulation of gene expression by DNA methylation. Primary cultures of SH male fetal cells (sex determined by differences in kdm5 loci on the X and Y chromosome) were exposed for 7 days to the carcinogen benzo[a]pyrene (20 µM) from which a morphologically transformed colony was collected and reseeded. The colony bypassed senescence and sustained growth. After 210 days of culture, the cells were collected and divided in 16 aliquots to create 4 experimental groups to test the effects of the DNA methylation inhibitor 5-aza-2′-deoxycytidine (5adC). The experiment was initiated 24 h after cell seeding in 10 cm plates. The groups are naïve cells (N), cells exposed for 48 h to either 0.05% DMSO as vehicle (V), or to 5adC at 1 µM and 5 µM. DNA and RNA libraries were sequenced on an Illumina NextSeq 500. Gene expression was analysed by RNAseq and differentially methylated DNA regions (DMRs: clusters of 200 base pairs (bp), read depth >20, q< 0.05, methylation difference >|25%|) were identified by reduce representation bisulfite sequencing (RRBS). Global genome DNA methylation was similar between the N (mean±SD, 47.3%±0.02) and V groups (47.3%±0.01). Although 5adC reduced methylation, the reduction was larger in the 1 µM (39.2%±0.002) than in the 5 µM group (44.3%±0.01). 5adC induced a total of 612 and 190 DMRs by 1 µM and 5 µM, among which 79 and 23 were in the promoter regions (±3,000 bp from the transcription start site), respectively. 5adC induced a total of 1,170 and 1,797 differentially expressed genes (DEGs) by 1 µM and 5 µM, respectively. The 5 µM treatment induced statistically significant toxicity (% cell viability: group N 97%±8, V 98.8%±1.3, 1 µM 97.3%±0.5, 5 µM 93.8%±1.5), which perhaps reduced cell division and daughter cell numbers with inherited changes in methylation, but increased number of DEGs due to both toxicity and methylation changes. As usually observed in the literature, a small portion of DEGs (4% and 4% at 1 µM and 5 µM, respectively) are associated with DMRs in their promoters. These promoter DMRs by themselves are sufficient among other epigenetic marks to induce DEGs. The dataset provides the genomic coordinates of the DMRs and an opportunity to further examine their roles in distal putative promoters or enhancers (yet to be described in the SH) in contributing to gene expression changes, senescence bypass and sustained proliferation as essential carcinogenic events (see companion paper [1]). Finally, this experiment confirms the possibility in future experiments to use 5adC as a positive control for effects on DNA methylation in cells derived from SH.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0190.017

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 head0.035
GPT teacher head0.307
Teacher spread0.272 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations5
Published2023
Admission routes2
Has abstractyes

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