GEO series

Cigarette smoke and biological age induce degenerative heterogeneity in retinal pigment epithelium

GSE288573 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2026/01/03 Platform GPL24247

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: Molecular underpinnings of induced degenerative heterogeneity in the retinal pigment epitheliumProceedings of the National Academy of Sciences of the United States of America · 2026

Summary (written by the submitters)

Environmental exposure such as cigarette smoke induces epigenetic changes that can induce degenerative heterogeneity and accelerate aging. In early age-related macular degeneration (AMD), the leading worldwide cause of blindness among the elderly, retinal pigment epithelial (RPE) cell heterogeneity is a key change. Since smoking is the strongest environmental risk factor for AMD, we hypothesized that cigarette smoke induces degenerative RPE heterogeneity through epigenetic changes that are distinct from aging, and that with aging, the RPE becomes vulnerable to cigarette smoke insult.

Read the full summary ↓

We administered cigarette smoke condensate (CSC) intravitreally to young and aged mice and performed snRNA-seq and snATAC-seq on the RPE/choroid. This analysis identified separate cell clusters corresponding to healthy and abnormal, dedifferentiated RPE in both aged vehicletreated and young CSC-treated mice. The dedifferentiated RPE were characterized by a global decrease in chromatin accessibility and decreased expression of genes in functional categories that were linked to hallmarks of aging. Notably, young, dedifferentiated RPE also exhibited a compensatory upregulation of hallmarks of aging-related genes, specifically those related to mitochondrial function and proteostasis. In contrast, aged dedifferentiated RPE did not express these compensatory changes, and did not survive CSC treatment, as experimentally verified with TUNEL labeling. These changes are relevant to early AMD because we identified through scRNA-seq, similar dedifferentiated and healthy macular RPE clusters in a donor who smoked and another with early AMD, but not from a nonsmoker. Degenerative cellular heterogeneity can include an abnormal cluster that jeopardizes cell survival and may represent an additional hallmark of ocular aging.

Published in

Molecular underpinnings of induced degenerative heterogeneity in the retinal pigment epithelium

Singh KK, Jin Y, Hu MW et al. · Proceedings of the National Academy of Sciences of the United States of America 2026 · PMID 41543898 · doi:10.1073/pnas.2505412123

This dataset

Open GSE288573 in finder → Find more mouse RNA-seq 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 GSE288573_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 PRJNA1218203 and SRA study SRP561009. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41543898) ↗

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

GSM8770147 Young Mice, CSC treatment, 3 days, GEX
GSM8770148 Young Mice, CSC treatment, 3 days, ATAC
GSM8770149 Young Mice, Control, 3 days, GEX
GSM8770150 Young Mice, Control, 3 days, ATAC
GSM8770151 Young Mice, CSC treatment, 6 days, GEX
GSM8770152 Young Mice, CSC treatment, 6 days, ATAC
GSM8770153 Young Mice, Control, 6 days, GEX
GSM8770154 Young Mice, Control, 6 days, ATAC
GSM8770155 Young Mice, CSC treatment, 10 days, GEX
GSM8770156 Young Mice, CSC treatment, 10 days, ATAC
GSM8770157 Young Mice, Control, 10 days, GEX
GSM8770158 Young Mice, Control, 10 days, ATAC
GSM8770159 Old Mice, CSC treatment, 10 days, GEX
GSM8770160 Old Mice, CSC treatment, 10 days, ATAC
GSM8770161 Old Mice, Control, 10 days, GEX
GSM8770162 Old Mice, Control, 10 days, ATAC

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