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Transcriptome profiling of ovaries in aged mice administered with Samul-tang

GSE264413 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/04/30 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 × OC # vs 6 × YC # vs 6 × OC+SM #Groups 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
Transcriptome profiling of aged-mice ovaries administered with individual ingredients of Samul-tangScientific data · 2025
Summary (written by the submitters)
Samul-tang (SM), a traditional herbal medicine is used to treat menstrual irregularities and infertility. The mechanism underlying the role of SM in ovary function needs elucidation. In this study, the influence of SM administration on the ovarian reserve of aged mice was investigated. Female BALB/c mice (8 and 40 weeks-old) were administered with distilled water (young or old group) or SM for 4 weeks.
Read the full summary ↓
SM administration prevented age-related ovarian follicle loss in mice. Quality of oocytes and blastocysts were enhanced in SM-administrated mice compared to those of non-treated old mice. Further, SM administration increased the pregnancy rate and number of litters. SM triggered changes in aging-related genes that are linked to the RAS-mediated pathway. Thus, we demonstrate that SM can be used to increase the oocyte yield in aged women, potentially improving age-related cognitive decline in the ovarian reserve.
Published in
Transcriptome profiling of aged-mice ovaries administered with individual ingredients of Samul-tang
Shin H, Kim J, Park M et al. · Scientific data 2025 · PMID 39814759 · doi:10.1038/s41597-025-04370-9
This dataset
Open GSE264413 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 GSE264413_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 PRJNA1102370 and SRA study SRP502846. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39814759) ↗
Study design
6 × OC # vs 6 × YC # vs 6 × OC+SM #

Supports a between-group comparison across 18 samples.

How we read this: 3 replicated groups read from 18 sample titles; they account for 18 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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