← BioTransfer GEO Dataset Finder
GEO series

Casz1 is required for both inner hair cell fate stabilization and outer hair cell survival

GSE249055 Mus musculus (mouse) RNA-seq (gene expression) 73 samples Submitted 2025/02/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 73 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
73 samples: 73 × P14_Casz1 -/- IHCGroups 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
Casz1 is required for both inner hair cell fate stabilization and outer hair cell survivalScience (New York, N.Y.) · 2025
Summary (written by the submitters)
Cochlear inner hair cells (IHCs) and outer hair cells (OHCs) require different transcription factors for their cell fate stabilization and survival, suggesting separate mechanisms are involved. Here, we found that the transcription factor Casz1 was crucial for early IHC fate consolidation and for OHC survival during mouse development.
Read the full summary ↓
Loss of Casz1 resulted in transdifferentiation of IHCs into OHCs, without affecting OHC production. However, long-term OHC survival was compromised in Casz1 mutant mice. In addition, the transcription factor Gata3 was downregulated in Casz1-deleted IHCs and overexpressing Gata3 partially rescued IHC properties, OHC numbers, and hearing in Casz1-deleted mice. Thus, Casz1 plays critical roles in early IHC fate stabilization and OHC survival and could potentially provide a lead for therapies aimed at regenerating both IHCs and OHCs.
Published in
Casz1 is required for both inner hair cell fate stabilization and outer hair cell survival
Sun Y, Ren M, Zhang Y et al. · Science (New York, N.Y.) 2025 · PMID 39883789 · doi:10.1126/science.ado4930
This dataset
Open GSE249055 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 GSE249055_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 PRJNA1047095 and SRA study SRP475191. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39883789) ↗
Study design
73 × P14_Casz1 -/- IHC

Supports a between-group comparison across 73 samples.

How we read this: 1 replicated groups read from 73 sample titles; they account for 73 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

+ 33 more — browse all 73 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.