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Molecular and functional profiling of cell diversity and identity in the lateral superior olive, an auditory brainstem center with ascending and descending projections

GSE241761 Mus musculus (mouse) RNA-seq (gene expression) 96 samples Submitted 2024/04/24 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 96 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
96 samples: 86 × cell vs 10 × NCGroups 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 and functional profiling of cell diversity and identity in the lateral superior olive, an auditory brainstem center with ascending and descending projectionsFrontiers in cellular neuroscience · 2024
Summary (written by the submitters)
The lateral superior olive (LSO), a conspicuous integration center in the auditory brainstem, contains a remarkably heterogeneous neuron population. Ascending neurons, predominantly principal neurons (pLSOs), process interaural level differences for sound localization. Descending neurons (lateral olivocochlear neurons, LOCs) provide feedback into the cochlea and likely protect from acoustic overexposure.
Read the full summary ↓
The molecular determinants of the neuronal diversity in the LSO are largely unknown. Here, we employed patch-seq analysis in juvenile mice to classify LSO neurons by their functional and molecular profiles, including developmental aspects. Across the sample (n=86), genes involved in ATPsynthesis were particularly highly expressed, confirming the energy expenditure of auditory neurons. Two clusters were identified, pLSOs and LOCs. They were distinguishable by 353 differentially expressed genes (DEGs), most being novel for the LSO. Electrophysiological analysis corroborated the transcriptomic clustering. We focused on genes impacting neuronal input-output properties and validated some by immunohistochemistry, electrophysiology, and pharmacology. These genes encode proteins like osteopontin, Kv11.3, and Kvb3 (pLSO-specific), calcitonin-gene-related peptide (LOC-specific), or Kv7.2 and Kv7.3 (no DEGs). We identified 12 ‘Super DEGs’ and 12 genes demonstrating ‘Cluster similarity’. Collectively, we provide fundamental and comprehensive insights into the molecular composition of individual ascending and descending neurons in the juvenile auditory brainstem and how this may relate to their specific functions, including developmental aspects.
Published in
Molecular and functional profiling of cell diversity and identity in the lateral superior olive, an auditory brainstem center with ascending and descending projections
Maraslioglu-Sperber A, Pizzi E, Fisch JO et al. · Frontiers in cellular neuroscience 2024 · PMID 38846638 · doi:10.3389/fncel.2024.1354520
This dataset
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.

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 GSE241761_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1009815 and SRA study SRP457113. Searching any of these in the dataset finder brings you back here.

Study design
86 × cell vs 10 × NC

Supports a between-group comparison across 96 samples.

How we read this: 2 replicated groups read from 96 sample titles; they account for 96 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

+ 56 more — browse all 96 samples with per-sample file links →

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.