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A glial circadian gene expression atlas reveals cell type and disease-specific reprogramming in response to amyloid pathology or aging

GSE261698 Mus musculus (mouse) RNA-seq (gene expression) 165 samples Submitted 2024/06/26 Platform GPL21493Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 165 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
165 samples: 79 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.
Paper
A glial circadian gene expression atlas reveals cell type and disease-specific reprogramming in response to amyloid pathology or agingbioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
While circadian rhythm disruption may promote neurodegenerative disease, how aging and neurodegenerative pathology impact circadian gene expression patterns in different brain cell types is unknown. Here, we used translating ribosome affinity purification methods to define the circadian translatomes of astrocytes, microglia, and bulk cerebral cortex, in healthy mouse brain and in the settings of amyloid-beta plaque pathology or aging.
Read the full summary ↓
Our data reveal that glial circadian translatomes are highly cell type-specific and exhibit profound, context-dependent reprogramming of rhythmic transcripts in response to amyloid pathology or aging. Transcripts involved in glial activation, immunometabolism, and proteostasis, as well as nearly half of all Alzheimer Disease (AD)-associated risk genes, displayed circadian oscillations, many of which were altered by pathology. Amyloid-related differential gene expression was also dependent on time of day. Thus, circadian rhythms in gene expression are cell- and context dependent and provide important insights into glial gene regulation in health, AD, and aging.
Published in
A glial circadian gene expression atlas reveals cell type and disease-specific reprogramming in response to amyloid pathology or aging
Sheehan PW, Fass S, Sapkota D et al. · bioRxiv : the preprint server for biology 2024 · PMID 38853870 · doi:10.1101/2024.05.28.596297
This dataset
Open GSE261698 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 GSE261698_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 PRJNA1088445 and SRA study SRP495462. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38853870) ↗
Study design
79 conditions, mostly in duplicate
Microglia, APP, 2am, ×2 Microglia, APP, 4am, ×2 Microglia, APP, 6am, ×2 Microglia, APP, 8am, ×2 Microglia, APP, 10am, ×2 Microglia, APP, 12pm, ×2 Microglia, APP, 2pm, ×2 Microglia, APP, 4pm, ×2 +78 more

Supports a between-group comparison across 158 samples.

How we read this: 79 replicated groups read from 165 sample titles; they account for 158 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

+ 125 more — browse all 165 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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