H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cells
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 94 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Mus musculus (mouse)
- Samples
- 94 samples: 34 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cellsScience advances · 2025
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE292289_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1237820 and SRA study SRP571388. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 80 samples.
How we read this: 34 replicated groups read from 94 sample titles; they account for 80 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8855477 WT_RNA WT_RNA
- GSM8855478 DOT1LCI_RNA DOT1LCI_RNA
- GSM8855479 SETD2CI_RNA SETD2CI_RNA
- GSM8855480 DCI_RNA DCI_RNA
- GSM8855481 WT_RNA_2 WT_RNA
- GSM8855482 DOT1LCI_RNA_2 DOT1LCI_RNA
- GSM8855483 SETD2CI_RNA_2 SETD2CI_RNA
- GSM8855484 DCI_RNA_2 DCI_RNA
- GSM8855485 WT_RNA_3 WT_RNA
- GSM8855486 DOT1LCI_RNA_3 DOT1LCI_RNA
- GSM8855487 SETD2CI_RNA_3 SETD2CI_RNA
- GSM8855488 DCI_RNA_3 DCI_RNA
- GSM8855489 WT_neural_day21_RNA WT_neural_day21_RNA
- GSM8855490 DCI_neural_day21_RNA DCI_neural_day21_RNA
- GSM8855491 WT_neural_day21_RNA_2 WT_neural_day21_RNA
- GSM8855492 DCI_neural_day21_RNA_2 DCI_neural_day21_RNA
- GSM8855493 WT_neural_day21_RNA_3 WT_neural_day21_RNA
- GSM8855494 DCI_neural_day21_RNA_3 DCI_neural_day21_RNA
- GSM8855495 DCI_DMSO8h_RNA DCI_DMSO8h_RNA
- GSM8855496 DCI_DMSO24h_RNA DCI_DMSO24h_RNA
- GSM8855497 DCI_VP8h_RNA DCI_VP8h_RNA
- GSM8855498 DCI_VP24h_RNA DCI_VP24h_RNA
- GSM8855499 DCI_DMSO8h_RNA_2 DCI_DMSO8h_RNA
- GSM8855500 DCI_DMSO24h_RNA_2 DCI_DMSO24h_RNA
- GSM8855501 DCI_VP8h_RNA_2 DCI_VP8h_RNA
- GSM8855502 DCI_VP24h_RNA_2 DCI_VP24h_RNA
- GSM8855503 WT_EPZ719_72h_RNA WT_EPZ719_72h_RNA
- GSM8855504 WT_DMSO_72h_RNA WT_DMSO_72h_RNA
- GSM8855505 WT_EPZ719_72h_RNA_2 WT_EPZ719_72h_RNA
- GSM8855506 WT_DMSO_72h_RNA_2 WT_DMSO_72h_RNA
- GSM8855507 WT_DMSO_72h_RNA_3 WT_DMSO_72h_RNA
- GSM8855508 WT_SGC0946_72h_RNA WT_SGC0946_72h_RNA
- GSM8855509 WT_SGC0946_EPZ719_72h_RNA WT_SGC0946_EPZ719_72h_R…
- GSM8855510 WT_DMSO_72h_RNA_4 WT_DMSO_72h_RNA
- GSM8855511 WT_SGC0946_72h_RNA_2 WT_SGC0946_72h_RNA
- GSM8855512 WT_SGC0946_EPZ719_72h_RNA_2 WT_SGC0946_EPZ719_72h_R…
- GSM8855513 WT_serumLIF_RNA WT_serumLIF_RNA
- GSM8855514 WT_serumLIF_RNA_2 WT_serumLIF_RNA
- GSM8855515 DOT1LCI_serumLIF_RNA DOT1LCI_serumLIF_RNA
- GSM8855516 DOT1LCI_serumLIF_RNA_2 DOT1LCI_serumLIF_RNA
+ 54 more — browse all 94 samples with per-sample file links →
- GSE292282 H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cells [RNA-Seq] 44 samples shares h3k79, h3k36, synergistically, trimethylation, methylation, pluripotent, regulate, stem
- GSE292287 H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cells [ChIP-Seq] 42 samples shares h3k79, h3k36, synergistically, trimethylation, methylation, pluripotent, regulate, stem
- GSE292283 H3K79 methylation and H3K36 trimethylation synergistically regulate gene expression in pluripotent stem cells [ATAC-Seq] 8 samples shares h3k79, h3k36, synergistically, trimethylation, methylation, pluripotent, regulate, stem
- GSE247253 H3K36 methylation regulates cell plasticity and regeneration in the intestinal epithelium 149 samples shares h3k36, methylation, regulate
- GSE243566 Systematic perturbations of SETD2, NSD1, NSD2, NSD3 and ASH1L reveal their distinct contributions to H3K36 methylation 125 samples shares h3k36, methylation, stem
- GSE247247 H3K36 methylation regulates cell plasticity and regeneration in the intestinal epithelium (CUT&Tag I) 30 samples shares h3k36, methylation, regulate
- GSE249087 H3K36 methylation regulates cell plasticity and regeneration in the intestinal epithelium (CUT&Tag III) 24 samples shares h3k36, methylation, regulate
- GSE247252 H3K36 methylation regulates cell plasticity and regeneration in the intestinal epithelium (RNA-seq III) 20 samples shares h3k36, methylation, regulate
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.