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Sub-compartment specific small non-coding RNA expression deregulation and altered nucleoli in mesial temporal lobe epilepsy

GSE269625 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/11/05 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 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.
Paper
Compartment-specific small non-coding RNA changes and nucleolar defects in human mesial temporal lobe epilepsyActa neuropathologica · 2024
Summary (written by the submitters)
Large scale changes in coding and non-coding RNA expression is a common feature of the resected hippocampal tissue from pharmacoresistant mesial temporal lobe epilepsy (mTLE) patients. However, there is very less insight on the expression and localization changes of the key regulatory RNAs at a sub-compartment level contributing to pathological mechanisms in mTLE.
Read the full summary ↓
In the present study we set out to understand the global sub-compartment specific changes in miRNA expression and localization and the alterations in the nucleus that possibly drive these changes and the consequences towards mTLE pathogenesis. We compared the nuclear and cytoplasmic distribution of miRNAs by small RNA-seq in subcellular fractionations of hippocampal tissue from mTLE patients and controls. Several miRNAs were found to be specifically enriched in the nucleus of hippocampal cells from patients compared to the controls, where miR-92b-3p (a miRNA-enriched in neurons) was the most de-regulated nuclear miRNA. By performing miR-92b co-immunoprecipitation (co-IP) assay on N2A nuclei and RNA-seq we identified enrichment of mTLE relevant pathways involving mitochondrial and ribosomal processes.
Published in
Compartment-specific small non-coding RNA changes and nucleolar defects in human mesial temporal lobe epilepsy
Vangoor VR, Giuliani G, de Wit M et al. · Acta neuropathologica 2024 · PMID 39509000 · doi:10.1007/s00401-024-02817-8
This dataset
Open GSE269625 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 GSE269625_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 PRJNA1122786 and SRA study SRP513259. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39509000) ↗
Study design
6 conditions, mostly in triplicate
Nuc_Control ×3 Nuc_Sc ×3 Nuc_92b ×3 Whole_Control ×3 Whole_Sc ×3 Whole_92b ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
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