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Transcriptome profiling of FGL2-stimulated enteric neural crest cells to investigate metabolic dysregulation in Hirschsprung disease pathogenesis

GSE305114 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2025/08/14 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples: 10 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.
Paper
FGL2-induced metabolic dysregulation in enteric neural crest cells provides insight into Hirschsprung disease pathogenesisiScience · 2025
Summary (written by the submitters)
This dataset comprises bulk RNA sequencing data from primary mouse enteric neural crest cells (ENCCs) stimulated with fibrinogen-like protein 2 (FGL2) or left untreated as controls. ENCCs were isolated from embryonic day 14–15 C57BL/6J mice and cultured under defined conditions to ensure >95% expression of P75 and nestin markers. Following FGL2 stimulation, total RNA was extracted, and sequencing libraries were prepared using the NEBNext Ultra RNA Library Prep Kit for Illumina.
Read the full summary ↓
Paired-end sequencing (2 × 150 bp) was performed on the Illumina NovaSeq 6000 platform. The study aims to identify transcriptional changes and signaling pathway alterations induced by FGL2 in ENCCs, providing insights into the role of FGL2-mediated metabolic dysregulation in the pathogenesis of Hirschsprung disease.
Published in
FGL2-induced metabolic dysregulation in enteric neural crest cells provides insight into Hirschsprung disease pathogenesis
Han J, Liu X, Wang Y et al. · iScience 2025 · PMID 40978140 · doi:10.1016/j.isci.2025.113423
This dataset
Open GSE305114 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 GSE305114_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 PRJNA1304459 and SRA study SRP608091. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40978140) ↗
Study design
10 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 10 sample titles: 10 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

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.