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Diminished transcriptional activity and splicing changes drive gene length-biased rewiring in the aging transcriptome (CUT&Run)

GSE318803 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2026/05/31 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 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
Mus musculus (mouse)
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
Diminished transcriptional activity and splicing changes drive gene length-biased rewiring in the aging transcriptomeProceedings of the National Academy of Sciences of the United States of America · 2026
Summary (written by the submitters)
Transcription by RNA polymerase II (RNAPII), which is essential for protein-coding gene expression and cellular function, is increasingly understood to become dysregulated with aging. Here, we use a multi-modal approach to comprehensively characterize age-dependent changes in RNAPII-mediated transcription in both mouse and human tissues.
Read the full summary ↓
Short-read total RNA sequencing (RNA-seq) to profile nascent transcription reveals a global reduction in overall transcriptional activity/frequency in aged tissues, without apparent change in elongation rates. Transcriptomic analysis reveals a shift toward preferential expression of short genes in aged tissues, with notable upregulation of short stress-response genes and downregulation of long neurodevelopmental genes in the aged mouse brain. These results are recapitulated by analysis of total RNA-seq data from human tissues. Leveraging long-read RNA-seq, we determine that the representation of aberrant mono-exonic and intron-retention splice isoforms is increased in the aged mouse brain. Finally, we characterize the composition of RNAPII transcriptional machinery, finding that interactions between RNAPII and the Mediator complex are decreased in the chromatin of aged mouse liver and brain. Collectively, these analyses provide insight for future aging studies and reveal potential transcriptional control targets for anti-aging drug development.
Published in
Diminished transcriptional activity and splicing changes drive gene length-biased rewiring in the aging transcriptome
Parast S, Das M, He Y et al. · Proceedings of the National Academy of Sciences of the United States of America 2026 · PMID 42301777 · doi:10.1073/pnas.2607264123
This dataset
Open GSE318803 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 GSE318803_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 PRJNA1420650 and SRA study SRP675604. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42301777) ↗
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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