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Dynamic enhancer interactome promotes senescence and aging [Hi-ChIP II]

GSE253617 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2024/10/31 Platform GPL21626
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 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
12 samples: 3 × H3K27ac_HiChIP.Young.Rep1 vs 3 × H3K27ac_HiChIP.Young.Rep2 vs 3 × H3K27ac_HiChIP.Old.Rep1 vs 3 × H3K27ac_HiChIP.Old.Rep2Groups 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.
Summary (written by the submitters)
Gene expression programs are regulated by enhancers which act in a context-specific manner, and can reside at great distances from their target genes. Extensive three-dimensional (3D) genome reorganization occurs in senescence, but how enhancer interactomes are reconfigured during this process is just beginning to be understood.
Read the full summary ↓
Here we generated high-resolution contact maps of active enhancers and their target genes, assessed chromatin accessibility, and established one-dimensional maps of various histone modifications and transcription factors to comprehensively understand the regulation of enhancer configuration during senescence. Hyper-connected enhancer communities/cliques formed around genes that are highly expressed and within essential gene pathways in each cell state. In addition, motif analysis indicates the involvement of specific transcription factors in hyper-connected regulatory elements in each condition; importantly, MafK, a bZIP family transcription factor, was upregulated in senescence, and reduced expression of MafK ameliorated the senescence phenotypes. Because the accumulation of senescent cells is a key feature of aging, we further investigated enhancer connectomes in the liver of young and aged mice. Hyper-connected enhancer communities were identified during aging, which regulate essential genes that maintain cell differentiation and homeostasis. These findings reveal that hyper-connected enhancer communities correlate with high gene expression in senescence and aging and provide potential hotspots for therapeutic intervention in aging and age-associated diseases.
This dataset
Open GSE253617 in finder → Find more mouse ChIP / ATAC / CUT&Tag datasets →
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.

Series matrix ↓
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 GSE253617_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1066357 and SRA study SRP484609. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × H3K27ac_HiChIP.Young.Rep1 vs 3 × H3K27ac_HiChIP.Young.Rep2 vs 3 × H3K27ac_HiChIP.Old.Rep1 vs 3 × H3K27ac_HiChIP.Old.Rep2

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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