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An in vitro neurogenetics platform for precision disease modeling in the mouse

GSE194402 Mus musculus (mouse) RNA-seq (gene expression) 76 samples Submitted 2024/04/10 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 76 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
76 samples: 70 distinct titles, 6 of them repeatedGroups 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
An in vitro neurogenetics platform for precision disease modeling in the mouseScience advances · 2024
Summary (written by the submitters)
The mouse is often the model of choice for genetic analysis of neurological disorders, but the introduction of disease mutations into a particular inbred strain sometimes fails to yield phenotypes relevant to human disease. Interrogating genetically diverse panels of mice can identify better models of human sensitivity and resistance to candidate disease variants.
Read the full summary ↓
We developed an in vitro methodology for modeling multiple stages of central nervous system development using a panel of genetically diverse mouse embryonic stem cell lines. Chemical knockdown of the neurodevelopmental gene Dyrk1a demonstrated profound strain differences in the cellular response to the ablation of DYRK1A activity throughout development in vitro. Responsive strains showed in vitro developmental defects consistent with observations in vivo on Dyrk1a knockout mice, and transcriptomic analysis of sensitive and resistant cell strain backgrounds successfully identified key molecular pathways in neural development known to be associated with Dyrk1a haploinsufficiency in vivo. Thus we demonstrate that high throughput comparative phenotype analysis of differentiated cells from human and genetically diverse mouse pluripotent stem cells bearing disease mutations can provide a facile route to identification of optimal mouse strains for precision disease modeling in vivo.
Published in
An in vitro neurogenetics platform for precision disease modeling in the mouse
Cortes DE, Escudero M, Korgan AC et al. · Science advances 2024 · PMID 38569042 · doi:10.1126/sciadv.adj9305
This dataset
Open GSE194402 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 GSE194402_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 PRJNA800438 and SRA study SRP356722. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38569042) ↗
Study design
70 distinct titles, 6 of them repeated
1_GT20-16825_S ×2 7_GT20-16817_S ×2 13_GT20-16843_S ×2 23_GT20-16821_S ×2 28_GT20-16816_S ×2 32_GT20-16840_S ×2

How we read this: Read from 76 sample titles: 70 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

+ 36 more — browse all 76 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.