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In Vitro Modeling of Age-Related Methylation Changes with Intestinal Organoids [RNA-Seq]

GSE294963 Mus musculus (mouse) DNA methylation 11 samples Submitted 2025/06/01 Platform GPL30172
At a glance

DNA methylation · mouse · 11 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Samples
11 samples: 5 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.
Summary (written by the submitters)
Intestinal organoids, three-dimensional cultures from intestinal stem cells, are a powerful model for studying aging, and DNA methylation is an accurate biological clock. Consequently, we hypothesized that organoid DNA methylation could serve as an aging metric and a valuable tool for in vitro aging research. Our initial study revealed significant DNA methylation changes, during organoid culture, with 27% of total CpG sites undergoing hypomethylation, and 11% gaining hypermethylation.
Read the full summary ↓
Hypomethylation occurred predominantly in aging-associated genomic regions, including non-promoter, non-CpG island regions (e.g., transposable elements), while hypermethylation, in CpG islands, significantly (p < 0.001) correlated with aging. Comparison of aging-methylated sites with differentiation-specific CpG sites showed minimal overlap, indicating negligible association. Early-passage (P0 and P2) organoids, derived from 4- and 24-month-old mice, preserved aging-specific methylation patterns, with a correlation coefficient of 0.48 (p < 0.001) between methylation differences in old versus young primary cells. Conversely, long-term passaging revealed distinct methylation changes, specific to each organoid line. Some early passage organoids exhibited more hypomethylation, clustering with mid-passage (P10 - P13) organoids, while late-passage (P24 and P27) organoids entered a crisis stage with severe hypomethylation, growth arrest, and distant clustering. Transposable elements remained hypomethylated, compared to primary cells. Aging-related methylation sites continued to change with passage, and linear modeling predicted that organoids age at a rate of 0.46 months per week in culture. Treatment with decitabine reversed the methylation age of organoids, derived from 24-month-old mice. These findings suggest that organoids effectively model aging, with further research needed to assess culture-associated influences.
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 GSE294963_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 beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1252115 and SRA study SRP579518. Searching any of these in the dataset finder brings you back here.

Study design
5 conditions, mostly in duplicate
Passage11_mouse ×2 Passage12_mouse ×2 Passage13_mouse ×2 Passage2_mouse ×2 Passage4_mouse ×2 Passage3_mouse ×1

Supports a between-group comparison across 10 samples.

How we read this: 5 replicated groups read from 11 sample titles; they account for 10 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
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