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Combining high-risk ADRD mutations across genetically distinct mice

GSE293440 Mus musculus (mouse) RNA-seq (gene expression) 290 samples Submitted 2025/04/05 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 290 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
290 samples: 138 conditions, mostly in duplicateGroups 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)
Alzheimer’s disease and related dementias (ADRD), including Alzheimer’s disease (AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), and mixed dementia are characterized by diverse pathologies and etiologies. ADRDs are typically distinguished based on combinations of associated pathologies in the brain such as amyloid, tau, TDP-43 inclusions, alpha-synuclein aggregates, and cerebral amyloid angiopathy, and these pathologies often co-occur even in cases clinically diagnosed as one disease.
Read the full summary ↓
The heterogeneity of ADRDs presents significant challenges in model development for disease mechanism elucidation, drug discovery, and preclinical testing. Current animal models of ADRD fail to incorporate mixed pathologies and demonstrate low concordance with the diverse genetic, molecular, pathological, and cognitive features of human disease. Further, genetic background is critical for accurately modeling the complex genetic, molecular and cognitive features of late-onset AD in mice, and that incorporation of genetic diversity significantly improves concordance between mouse models and human patients in these parameters. Using CRISPR genome editing, we knocked-in several known human disease-causing mutations into C57BL/6J mice. Through serial breeding, we combined these KI mutations into various 3X, 4X, 5X and 6X knock-in models. We then crossed these 3X-5X models to various genetic backgrounds (C57BL/6J, DBA/2J, FVB/NJ, WSB/EiJ) to achieve a diverse F1 panel of genetically altered mice. Our goal was to maintain physiological expression levels of genes that induce commonly co-occurring pathologies in brain and peripheral tissues, while addressing these critical concerns often overlooked in most mouse models of neurodegenerative diseases (i.e., genetic diversity, late symptom onset, systemic expression of mutations, etc).
This dataset
Open GSE293440 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 GSE293440_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 PRJNA1243442 and SRA study SRP573960. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
138 conditions, mostly in duplicate
Female, Young, B6xD2, APP-PSEN1-Tardbp, Het, ×3 Male, Young, B6xD2, APP-PSEN1-Tardbp, Het, ×2 Male, Old, B6xD2, APP-PSEN1-Tardbp, Het, ×2 Female, Old, B6xFVB, APP-PSEN1-Tardbp, Het, ×2 Male, Old, B6xFVB, APP-PSEN1-Tardbp, Het, ×2 Female, Young, B6xWSB, APP-PSEN1-Tardbp, Het, ×2 Female, Old, B6xWSB, APP-PSEN1-Tardbp, Het, ×2 Male, Young, B6xWSB, APP-PSEN1-Tardbp, Het, ×2 +143 more

Supports a between-group comparison across 277 samples.

How we read this: 138 replicated groups read from 290 sample titles; they account for 277 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

+ 250 more — browse all 290 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.