CD36-mediated lipid-accumulation in reactive microglia drives retinal degeneration through Nlrp3-IL-1β pathway
RNA-seq (gene expression) · mouse · 10 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
- 10 samples: 5 × WT-CD36 positive cells vs 5 × WT-CD36-negative cellsGroups 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.
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE324526_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1435755 and SRA study SRP682829. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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.
- GSM9579063 WT-CD36 positive cells-1 WT-CD36 positive cells
- GSM9579064 WT-CD36 positive cells-2 WT-CD36 positive cells
- GSM9579065 WT-CD36 positive cells-3 WT-CD36 positive cells
- GSM9579066 WT-CD36 positive cells-4 WT-CD36 positive cells
- GSM9579067 WT-CD36 positive cells-5 WT-CD36 positive cells
- GSM9579068 WT-CD36-negative cells-1 WT-CD36-negative cells
- GSM9579069 WT-CD36-negative cells-2 WT-CD36-negative cells
- GSM9579070 WT-CD36-negative cells-3 WT-CD36-negative cells
- GSM9579071 WT-CD36-negative cells-4 WT-CD36-negative cells
- GSM9579072 WT-CD36-negative cells-5 WT-CD36-negative cells
- GSE304931 Alpha retinal ganglion cell-derived SPP1 instructs microglia to limit neurodegeneration 23 samples shares degeneration, microglia, retinal
- GSE103334 Temporal tracking of microglia activation in neurodegeneration at single-cell resolution 2208 samples shares degeneration, microglia
- GSE247436 Deletion of Gba in neurons, but not microglia, causes neurodegeneration in a Gaucher mouse model 32 samples shares degeneration, microglia
- GSE263679 Integrated stress response associated with dark microglia contributes to neurodegeneration [TRAP-seq] 29 samples shares degeneration, microglia
- GSE254104 Alzheimer’s disease-linked risk alleles elevate microglial cGAS-associated senescence and neurodegeneration in a tauopathy model [snRNAseq] 27 samples shares degeneration, microglia
- GSE254103 Alzheimer’s disease-linked risk alleles elevate microglial cGAS-associated senescence and neurodegeneration in a tauopathy model [bulk_RNAseq] 24 samples shares degeneration, microglia
- GSE285713 Enhancing TREM2 expression activates microglia and modestly mitigates Tau pathology and neurodegeneration 24 samples shares degeneration, microglia
- GSE273797 Pathophysiology of microglial-driven neurodegeneration in Histiocytosis [Proj_11769] 20 samples shares degeneration, microglia
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.