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Increased stiffness mimicking ovarian aging induces a fibroinflammatory response in follicles and impairs oocyte quality

GSE317288 Mus musculus (mouse) RNA-seq (gene expression) 32 samples Submitted 2026/01/27 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 32 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
32 samples: 32 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.
Summary (written by the submitters)
Reproductive aging in females is characterized by decreased ovarian reserve and oocyte quality. With aging, both mouse and human ovaries become pro-fibrotic and stiff. However, whether follicles sense and respond to microenvironmental stiffness and affect folliculogenesis and oocyte quality independent of other aging-related factors is unknown.
Read the full summary ↓
To address this question, we cultured mouse secondary follicles in alginate hydrogels that reproduce the stiffness of young and reproductively old mice. RNA-sequencing revealed that follicles respond rapidly to increased stiffness and exhibit enrichment in genes related to inflammation and extracellular matrix remodeling. Long-term culture in stiff hydrogels resulted in reduced follicle survival, granulosa cell viability, estradiol synthesis, and oocyte quality. To begin to determine how stiffness is transmitted within the follicle, we examined transzonal projections, which mediate granulosa cell–oocyte communication and nutrient exchange. In stiff conditions, the number of transzonal projections decreased. Our findings demonstrate that follicles are highly mechanosensitive and that stiffness alone can trigger hallmarks of ovarian aging, including reduced follicle growth, reduced oocyte quality, and a fibroinflammatory phenotype potentially integrated to the oocyte via TZPs.
This dataset
Open GSE317288 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 GSE317288_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1406689 and SRA study SRP665607. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
32 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 32 sample titles: 32 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.