GEO series

Exosomal miR-302b rejuvenates aging mice by reversing cell cycle arrest [scRNA-Seq]

GSE247074 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/11/01 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 12 samples: 12 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)

Senescent cells (SnCs) are considered the driving force of aging; therefore, restoring the normal function of SnCs or reversing the senescence-associated secretory phenotype (SASP) may have anti-aging effects. Current anti-aging strategies include destroying, or reprogramming, SnCs and inhibiting SASP. However, significant challenges persist, such as the progressive loss of tissue function and risk of tumorigenesis.

Read the full summary ↓

Herein, we report a Senoreviver strategy that breaks cell cycle arrest and reverses SASP simultaneously via human embryonic stem cell exosome (hESC-Exo)-mediated delivery of miR-302b. miRNA-seq analysis revealed that hESC-Exos enriches miR-302 family members. Ago2 CLIP-seq mapping revealed that miR-302b could repress the cell cycle inhibitors Cdkn1a and Ccng2, which collectively restored the proliferative capacity of SnCs and reversed SASP. Our study provides a Senoreviver strategy to rejuvenate SnCs in vitro and in vivo, rather than eliminate or reprogram them, thus holding great promise for maintaining tissue homeostasis, extending the health span, and countering age-related diseases.

This dataset

Open GSE247074 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 GSE247074_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1036182 and SRA study SRP470837. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 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 12 sample titles: 12 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

GSM7882930 Aging_pbs_liver, replicate 1, scRNAseq
GSM7882931 Aging_pbs_liver, replicate 2, scRNAseq
GSM7882932 Aging_pbs_liver, replicate 3, scRNAseq
GSM7882933 Aging_Exos_liver, replicate 1, scRNAseq
GSM7882934 Aging_Exos_liver, replicate 2, scRNAseq
GSM7882935 Aging_Exos_liver, replicate 3, scRNAseq
GSM7882936 Aging_pbs_skin, replicate 1, scRNAseq
GSM7882937 Aging_pbs_skin, replicate 2, scRNAseq
GSM7882938 Aging_pbs_skin, replicate 3, scRNAseq
GSM7882939 Aging_Exos_skin, replicate 1, scRNAseq
GSM7882940 Aging_Exos_skin, replicate 2, scRNAseq
GSM7882941 Aging_Exos_skin, replicate 3, scRNAseq

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Search all mouse RNA-seq datasets in GEO →

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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.