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Mega-Enhancers Compartmentalize Transcriptionally Active Long Genes in the Brain [RNA-Seq]

GSE339044 Mus musculus (mouse) RNA-seq (gene expression) 71 samples Submitted 2026/07/21 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 71 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
71 samples: 12 conditions, mostly in triplicateGroups 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)
Exceptionally long genes and cis-regulatory enhancers are selectively activated in mammalian brain neurons, and these loci are mutation hotspots in neurological disorders. However, the organization of these large genomic elements at the level of chromosome folding, beyond local enhancer-promoter interactions, remains poorly understood.
Read the full summary ↓
Here, we report the discovery of a genomic subcompartment in the mouse cerebellum formed by near-megabase long enhancers and their associated long genes encoding synaptic or signaling proteins. Genomic regions within this subcompartment are enriched in the outer-half of the nucleus, while other transcriptionally active structures are enriched in the nuclear interior. Using an in vivo CRISPR genetic mini-screen, we uncover a specific role for the transcription factor Etv1 in coupling the compartmentalization of neuronal long genes with their expression. Together, our study defines mechanisms that organize transcriptionally active genes across chromosomes in the mammalian brain.
This dataset
Open GSE339044 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 GSE339044_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 PRJNA1496866 and SRA study SRP718940. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
RNA-seq GN, ctrl, FANS, IVE+day8, ×12 RNA-seq GN, brd4 KD, syncTRAP, IVE+day8, ×11 RNA-seq GN, ctrl, syncTRAP, IVE+day8, ×7 RNA-seq GN, ctrl, syncTRAP, IVE+day8, CD1-P14, ×7 RNA-seq GN, etv1 KD, FANS, IVE+day8, ×6 RNA-seq GN, top1-2b KD, FANS, IVE+day8, ×6 RNA-seq GN, ctrl, syncTRAP, IVE+day4, CD1-P10, ×6 RNA-seq cerebellum, CD1-P10, ×3 +6 more

Supports a between-group comparison across 69 samples.

How we read this: 12 replicated groups read from 71 sample titles; they account for 69 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

+ 31 more — browse all 71 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.