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Age-associated G-quadruplex accumulation and DDX5 loss shape chromatin landscapes in human astrocytes [ATAC-seq]

GSE307273 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2025/12/01 Platform GPL34295
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 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
Homo sapiens (human)
Samples
16 samples: 16 samples, each with a distinct title — no replicated groupsGroups 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
Age-associated G-quadruplex accumulation and DDX5 loss shape chromatin landscapes in human astrocytesResearch square · 2025
Summary (written by the submitters)
Aging disrupts genome organization and transcriptional fidelity, but the role of non-canonical DNA structures in the aging process remains unclear. G-quadruplexes (G4s), stable guanine-rich DNA and RNA structures are established regulators of gene expression and genome integrity, yet their contribution to physiological aging is unknown.
Read the full summary ↓
Using primary human astrocytes derived from individuals spanning early to late adulthood (22–73 years) and fluorescent imaging, we observed increased G4 accumulation and reduced nuclear expression of the G4-resolving helicase DDX5 in older cells. To investigate how these changes relate to genome architecture, we performed ATAC-seq and G4 CUT&Tag across all astrocyte cultures. Older cells exhibited global chromatin compaction and focal G4 enrichment, with gains occurring in both accessible and closed chromatin regions, indicating locus-specific and context-dependent regulation. To determine whether DDX5 modulates these features, we overexpressed DDX5 in young astrocytes and identified transcriptional targets involved in chromatin organization and genome maintenance. Acute DDX5 knockout caused focal G4 accumulation without widespread chromatin changes, indicating that DDX5 maintains and modulates G4 dynamics at defined genomic regions. Together, these findings reveal G4s as dynamic, age-sensitive features of the genome with potential roles in epigenetic regulation and establish DDX5 as a modulator of G4 dynamics and genome integrity during human brain aging.
Published in
Age-associated G-quadruplex accumulation and DDX5 loss shape chromatin landscapes in human astrocytes
Tsvetkov A, J VKM, Escarcega RD et al. · Research square 2025 · PMID 41333436 · doi:10.21203/rs.3.rs-7933297/v1
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 GSE307273_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 PRJNA1315129 and SRA study SRP617641. Searching any of these in the dataset finder brings you back here.

Study design
16 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 16 sample titles: 16 distinct titles with little repetition. 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.