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Neuron type-specific mRNA translation programs provide a gateway for memory consolidation.

GSE300675 Mus musculus (mouse) RNA-seq (gene expression) 153 samples Submitted 2026/05/07 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 153 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
153 samples: 153 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.
Summary (written by the submitters)
Long-term memory consolidation is a dynamic process that requires a heterogeneous ensemble of neurons, each with a highly specialized molecular signature. Considerable effort has been devoted to identifying molecular changes that accompany the process of consolidation, but mostly hours or days after training, when memory consolidation is already complete.
Read the full summary ↓
Studies have shown that protein synthesis is elevated during the early stages of consolidation, but how this increase impacts neuronal function remains unclear. We hypothesize that mRNAs translated during the early stages of consolidation could provide information on how diverse neurons involved in memory formation restructure their molecular signatures to support memory. Here, we generate a landscape of the translatome of three neuron types in the dorsal hippocampus during the first hour of contextual memory consolidation. Our results reveal that translation programs associated with consolidation are different among neurons, fueling the reconfiguration of specific biological processes. We further demonstrate the patterned translation of mRNAs in different neuron types during consolidation is explained by features hard-coded in the mRNA sequence, suggesting ubiquitous mechanisms controlling activity-induced neuronal translation. Altogether, our work uncovers previously unknown mechanisms controlling activity-induced translation in neurons and provides a large, readily available resource for scientists interested in the role of memory formation in health and disease.
This dataset
Open GSE300675 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 GSE300675_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 PRJNA1281649 and SRA study SRP594359. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
153 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 153 sample titles: 153 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

+ 113 more — browse all 153 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.