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Molecular logic for cellular specializations that initiate the auditory parallel processing pathways

GSE273145 Mus musculus (mouse) Single-nucleus RNA-seq 398 samples Submitted 2024/11/04 Platform GPL21103Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 398 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
398 samples: 5 conditions, mostly in duplicateGroups 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
Molecular logic for cellular specializations that initiate the auditory parallel processing pathwaysNature communications · 2025
Summary (written by the submitters)
The cochlear nuclear complex (CN), the starting point for all central auditory processing, comprises a suite of neuronal cell types that are highly specialized for neural coding of acoustic signals, yet molecular logic governing cellular specializations remains largely unknown. By combining single-nucleus RNA sequencing and Patch-seq analysis, we reveal a set of transcriptionally distinct cell populations encompassing all previously observed types and discover multiple new subtypes with anatomical and physiological identity.
Read the full summary ↓
The resulting complete cell-type taxonomy reconciles anatomical position, morphological, physiological, and molecular criteria, enabling determination of molecular basis of the remarkable cellular phenotypes in the CN. In particular, CN cell-type identity is encoded in a transcriptional architecture that orchestrates functionally congruent expression across a small set of gene families to customize projection patterns, input-output synaptic communication, and biophysical features required for encoding distinct aspects of acoustic signals. This high-resolution account of cellular heterogeneity from the molecular to the circuit level illustrates molecular logic for cellular specializations and enables genetic dissection of auditory processing and hearing disorders with unprecedented specificity.
Published in
Molecular logic for cellular specializations that initiate the auditory parallel processing pathways
Jing J, Hu M, Ngodup T et al. · Nature communications 2025 · PMID 39788966 · doi:10.1038/s41467-024-55257-z
This dataset
Open GSE273145 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 GSE273145_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 PRJNA1013912 and SRA study SRP459158. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39788966) ↗
Study design
5 conditions, mostly in duplicate
patch-seq sample_S ×387 single nucleus sample_p2s ×2 single nucleus sample_p3s ×2 single nucleus sample_p5s ×2 single nucleus sample_p6s ×2 single nucleus sample_p1s ×1 single nucleus sample_p4s ×1 single nucleus sample_p7s ×1

Supports a between-group comparison across 395 samples.

How we read this: 5 replicated groups read from 398 sample titles; they account for 395 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

+ 358 more — browse all 398 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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