← BioTransfer GEO Dataset Finder
GEO series

Global gene expression profile of cortices from Aifm1 KI and Hq mutant and control mouse

GSE196414 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/01/28 Platform GPL21103
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: 4 × Aifm1-KI vs 4 × Aifm1-WT vs 4 × Hq-mut vs 4 × Hq-WTGroups 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
Integrated analysis of transcriptomic and proteomic alterations in mouse models of ALS/FTD identify early metabolic adaptions with similarities to mitochondrial dysfunction disordersAmyotrophic lateral sclerosis & frontotemporal degeneration · 2024
Summary (written by the submitters)
In this study, global transcriptome profiling was performed for Aifm1-KI and Hq mutant (as model of mitochondial defect) and control samples from mouse cortices, More than 20 million high-quality reads were obtained from each sample using Illumina platform. A consensus reference-guided assembly was generated for the transcriptome data from all samples and gene expression was analysed.
Published in
Integrated analysis of transcriptomic and proteomic alterations in mouse models of ALS/FTD identify early metabolic adaptions with similarities to mitochondrial dysfunction disorders
Matveeva A, Watters O, Rukhadze A et al. · Amyotrophic lateral sclerosis & frontotemporal degeneration 2024 · PMID 37779364 · doi:10.1080/21678421.2023.2261979
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 GSE196414_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: 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 PRJNA804867 and SRA study SRP359056. Searching any of these in the dataset finder brings you back here.

Study design
4 × Aifm1-KI vs 4 × Aifm1-WT vs 4 × Hq-mut vs 4 × Hq-WT

Supports a between-group comparison across 16 samples.

How we read this: 4 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
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.