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miR-29 is an important driver of aging-related phenotypes

GSE216398 Mus musculus (mouse) RNA-seq (gene expression) 17 samples Submitted 2025/10/22 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 17 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
17 samples: 6 × WT_2mon vs 6 × TG_2mon vs 5 × WT_2yeaGroups 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)
Aging is a consequence of complex molecular changes, but the roles for individual microRNAs (miRNAs) in aging remain unclear. One of the few miRNAs that is upregulated during both normal and premature aging is miR-29. We confirmed this finding in our study in both mouse and monkey models. Follow-up analysis of the transcriptomic changes during normal aging revealed that miR-29 is among the top miRNAs predicted to drive the aging-related gene expression changes.
Read the full summary ↓
We also showed that partial loss of miR-29 extends the lifespan of Zmpste-/- mice, an established model of progeria, which indicates that miR-29 is functionally important in this accelerated aging model. To examine whether miR-29 upregulation alone is sufficient to promote aging-related phenotypes in vivo, we generated mice in which miR-29 can be conditionally overexpressed (miR-29TG). We found that miR-29 overexpression in mice is sufficient to drive aging-related phenotypes including alopecia, kyphosis, osteoporosis and senescence, and leads to early lethality. Transcriptomic analysis of both young miR-29TG and old WT mice revealed shared downregulation of genes enriched in extracellular matrix and fatty acid metabolism, and shared upregulation of genes in pathways linked to inflammation. Together, these results highlight the functional importance of miR-29 in controlling a gene expression program that drives aging-related phenotypes.
This dataset
Open GSE216398 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 GSE216398_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 PRJNA893541 and SRA study SRP404179. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × WT_2mon vs 6 × TG_2mon vs 5 × WT_2yea

Supports a between-group comparison across 17 samples.

How we read this: 3 replicated groups read from 17 sample titles; they account for 17 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
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.