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Establishment and validation of the NEX-RiboTag system for profiling the excitatory neuronal translatome in the postnatal mouse forebrain

GSE331310 Mus musculus (mouse) Single-cell RNA-seq 11 samples Submitted 2026/06/23 Platform GPL34290
At a glance

Single-cell RNA-seq · mouse · 11 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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
11 samples: 11 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
Establishment and validation of the NEX-RiboTag system for profiling the excitatory neuronal translatome in the postnatal mouse forebrainNeuroscience · 2026
Summary (written by the submitters)
Excitatory neurons are the principal neurons of the mammalian cortex and hippocampus and are essential for postnatal circuit maturation. Although single-cell RNA sequencing has refined their molecular taxonomy, dissociation-induced stress artifacts and the disconnect between transcript abundance and translational output can limit functional interpretation.
Read the full summary ↓
Bulk proteomics lacks cell-type specificity, while single-cell proteomics remains constrained by limited sensitivity and throughput. These limitations leave a gap between transcriptional identity and cell-type-resolved translational output. Because translation directly governs the selective recruitment of mRNAs for protein synthesis, defining excitatory neuron-specific translatome in vivo is valuable to bridge this gap. Here, we established and validated a NEX-RiboTag mouse line for targeted profiling of ribosome-associated mRNAs in cortical and hippocampal excitatory neurons. By crossing Neurod6 (NEX)-Cre mice with RiboTag reporter mice, we achieved Cre-dependent ribosomal tagging in excitatory neurons of the cortex and the hippocampus. RNA sequencing analysis at the 1-week postnatal stage demonstrated enrichment of excitatory neuronal markers and depletion of inhibitory neuronal and glial transcripts. Comparative analysis revealed a clear separation between the whole-tissue transcriptome and the ribosome-associated fractions, with enrichment of synaptic and metabolic pathways characteristic of excitatory neurons. Together, these datasets provide a valuable resource for investigating translational regulation in postnatal excitatory neurons and for studying molecular programs underlying neuronal maturation and synapse formation.
Published in
Establishment and validation of the NEX-RiboTag system for profiling the excitatory neuronal translatome in the postnatal mouse forebrain
Zheng K, Liu M, Jin B et al. · Neuroscience 2026 · PMID 42324055 · doi:10.1016/j.neuroscience.2026.06.027
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 GSE331310_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: 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 PRJNA1467668 and SRA study SRP701688. Searching any of these in the dataset finder brings you back here.

Study design
11 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 11 sample titles: 11 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
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