GEO series

Nup153 regulates neuronal responsiveness through HDAC1-mediated epigenetic modulation [RNA-seq]

GSE275919 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/07/31 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 16 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: 16 samples: 5 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)

Neural activity-dependent gene regulation is central to the development of neural networks and neuronal plasticity. Induction of activity-dependent gene programs is equally important as repression of these programs, and both need to be balanced carefully. However, little is known about how repressive mechanisms modulate neuronal responsiveness across the genome before stimulation.

Read the full summary ↓

Here, we identify nucleoporin-dependent regulation of neuronal responsiveness in which Nup153 represses neuronal genes including activity-regulated genes (ARGs) in the basal state. By characterizing the genome-wide landscape of chromatin accessibility, histone modifications and Nup153 chromatin binding, we show that Nup153 directly influences their target genes and associated chromatin states through both basal activity-dependent and -independent mechanisms. Mechanistically, Nup153 recruits HDAC1 to regulate histone acetylation and repress target chromatin regions. We propose that Nup153 acts as a structural platform to recruit epigenetic repressor to maintain activity-dependent programs in the poised state, thus maintaining neuronal responsiveness as a gatekeeper.

This dataset

Open GSE275919 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 GSE275919_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 PRJNA1152568 and SRA study SRP528678. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 conditions, mostly in triplicate

RNA_Basal_shControl ×4 RNA_Basal_shNup153_1 ×3 RNA_Basal_shNup153_2 ×3 RNA_TTX_AP5_shControl ×3 RNA_TTX_AP5_shNup153_2 ×3

Supports a between-group comparison across 16 samples.

How we read this: 5 replicated groups read from 16 sample titles; they account for 16 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

GSM8488109 RNA_Basal_shControl_Replicate1 RNA_Basal_shControl
GSM8488110 RNA_Basal_shControl_Replicate2 RNA_Basal_shControl
GSM8488111 RNA_Basal_shControl_Replicate3 RNA_Basal_shControl
GSM8488112 RNA_Basal_shControl_Replicate4 RNA_Basal_shControl
GSM8488113 RNA_Basal_shNup153_1_Replicate1 RNA_Basal_shNup153_1
GSM8488114 RNA_Basal_shNup153_1_Replicate2 RNA_Basal_shNup153_1
GSM8488115 RNA_Basal_shNup153_1_Replicate3 RNA_Basal_shNup153_1
GSM8488116 RNA_Basal_shNup153_2_Replicate1 RNA_Basal_shNup153_2
GSM8488117 RNA_Basal_shNup153_2_Replicate2 RNA_Basal_shNup153_2
GSM8488118 RNA_Basal_shNup153_2_Replicate3 RNA_Basal_shNup153_2
GSM8488119 RNA_TTX_AP5_shControl_Replicate1 RNA_TTX_AP5_shControl
GSM8488120 RNA_TTX_AP5_shControl_Replicate2 RNA_TTX_AP5_shControl
GSM8488121 RNA_TTX_AP5_shControl_Replicate3 RNA_TTX_AP5_shControl
GSM8488122 RNA_TTX_AP5_shNup153_2_Replicate1 RNA_TTX_AP5_shNup153_2
GSM8488123 RNA_TTX_AP5_shNup153_2_Replicate2 RNA_TTX_AP5_shNup153_2
GSM8488124 RNA_TTX_AP5_shNup153_2_Replicate3 RNA_TTX_AP5_shNup153_2

Datasets on a similar topic

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GSE289641 Noncanonical PRC2 chromatin association reveals a key role of EZHIP in intergenerational epigenetic memory transition [RNA-Seq] 68 samples shares epigenetic, rna-seq

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