← BioTransfer GEO Dataset Finder
GEO series

Single-cell transcriptomics and translatomics dual-omics analysis reveals the potential mechanism of HFD-induced maternal RNA degradation abnormalities

GSE294093 Mus musculus (mouse) Single-cell RNA-seq 42 samples Submitted 2025/04/14 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 42 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
42 samples: 14 conditions, mostly in triplicateGroups 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)
This study explores the impact of high-fat diet (HFD)-induced obesity on maternal RNA degradation and its implications for oocyte quality and development in mice, using a novel transcriptome and translatome sequencing (T&T-seq) strategy. By combining RiboLace for translatome profiling and Smart-seq for transcriptome analysis, the research investigates how HFD disrupts RNA degradation pathways during oocyte maturation, particularly from the germinal vesicle (GV) to metaphase II (MII) stages.
Read the full summary ↓
The findings reveal that HFD impairs the degradation of key transcripts such as BTG4 and CNOT7, and alters the translation efficiency of meiotic regulators, which are crucial for proper meiotic progression. This study provides new insights into how maternal dietary factors influence oocyte quality at the molecular level, with potential implications for fertility and embryonic development.
This dataset
Open GSE294093 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 GSE294093_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 PRJNA1248238 and SRA study SRP577375. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 conditions, mostly in triplicate
Normal diet,RNA-seq,MII ×4 Normal diet,Translatomics,GV ×3 Normal diet,Translatomics,MII ×3 High-fat diet,Translatomics,GV ×3 High-fat diet,Translatomics,MII ×3 Normal diet,Transcriptomics,GV ×3 Normal diet,Transcriptomics,MII ×3 High-fat diet,Transcriptomics,GV ×3 +6 more

Supports a case/control comparison: 3 samples read as cases, 21 as controls.

How we read this: 14 replicated groups read from 42 sample titles; they account for 42 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.