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RNA-seq, LaminB1 ChIP-seq and in situ Hi-C of double positive thymocytes from control and Suv39h1/Suv39h2 double knockout mice

GSE156297 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 34 samples Submitted 2024/03/27 Platform GPL19057Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 34 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
34 samples: 10 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
Suv39h-catalyzed H3K9me3 is critical for euchromatic genome organization and the maintenance of gene transcriptionGenome research · 2024
Summary (written by the submitters)
H3K9me3-dependent heterochromatin is critical for the silencing of repeat-rich pericentromeric regions and also has key roles in repressing lineage-inappropriate protein-coding genes for healthy cellular function. Within all eukaryotic nuclei, heterochromatin and euchromatin are spatially segregated, with euchromatin typically located in the nuclear interior and heterochromatin at the nuclear periphery.
Read the full summary ↓
We investigated the effects of loss of H3K9me3-dependent heterochromatin in primary immune cells deficient in both Suv39h1 and Suv39h2 (Suv39DKO), the major mammalian histone methyltransferase enzymes which catalyse heterochromatic H3K9me3 deposition.
Published in
Suv39h-catalyzed H3K9me3 is critical for euchromatic genome organization and the maintenance of gene transcription
Keenan CR, Coughlan HD, Iannarella N et al. · Genome research 2024 · PMID 38719473 · doi:10.1101/gr.279119.124
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE156297_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA657281 and SRA study SRP277563. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly in duplicate
Control, RNA-Seq ×3 Suv39h1, Suv39h2 double knock-out, RNA-Seq ×3 Control whole cell extract ×2 Control LaminB1 ChIP ×2 Suv39h1, Suv39h2 double knock-out whole cell … ×2 Suv39h1, Suv39h2 double knock-out LaminB1 ChIP ×2 Control, ×2 Suv39h1, Suv39h2 double knock-out, ×2 +14 more

Supports a between-group comparison across 22 samples.

How we read this: 10 replicated groups read from 34 sample titles; they account for 22 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.

Samples in this study
Datasets on a similar topic

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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.