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Cholesterol and matrisome pathways dysregulated in APOE ε4 human microglia and astrocytes [mouseApoe]

GSE190186 Mus musculus (mouse) RNA-seq (gene expression) 44 samples Submitted 2022/06/23 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 44 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
44 samples
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)
The impact of Apolipoprotein E4 (APOE4), the strongest genetic risk factor for Alzheimer's disease (AD), on human brain cellular function remains unclear. Here we investigated the effects of APOE4 on brain cell types derived from population and isogenic human induced pluripotent stem cell models, post-mortem brain and APOE targeted replacement mice.
Read the full summary ↓
Population and isogenic models uncover that APOE4 local haplotype rather than a single risk allele alone contributes to the risk. Global transcriptomic analyses reveal human specific, APOE4-driven lipid metabolic dysregulation in astrocytes and microglia. APOE4 leads to elevated de novo cholesterol synthesis despite the intracellular cholesterol accumulation due to lysosomal sequestration of cholesterol in astrocytes. Transcriptome analyses uncovered Matrisome dysregulation associated with upregulated chemotaxis, glial activation and lipid biosynthesis in astrocytes, co-cultured with neurons that recapitulates altered astrocyte matrisome signaling in human brain. Thus, APOE4 initiates glia-specific cell and non-cell autonomous dysregulation that may contribute to increased AD risk.
This dataset
Open GSE190186 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 GSE190186_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 PRJNA786226 and SRA study SRP349252. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35750033) ↗
Samples in this study

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+ 44 more — browse all 44 samples with per-sample file links →

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