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Tlr7 Drives Sex Differences in Age- and AD-related Demyelination [snRNAseq]

GSE282329 Mus musculus (mouse) Single-nucleus RNA-seq 95 samples Submitted 2024/11/29 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 95 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Mus musculus (mouse)
Samples
95 samples: 5 conditions, mostly with about 23 replicates eachGroups 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
Tlr7 drives sex differences in age- and Alzheimer's disease-related demyelinationScience (New York, N.Y.) · 2024
Summary (written by the submitters)
Alzheimer’s disease (AD) and other age-related disorders associated with demyelination exhibit sex differences. Here, we used single-nuclei transcriptomics to dissect the contributions of sex chromosomes and gonads in demyelination and AD. In a mouse model of demyelination, we identified the role of sex chromosomes and gonads in modifying microglia and oligodendrocyte responses before and after myelin loss.
Read the full summary ↓
In an AD-related mouse model expressing APOE4, XY sex chromosomes heightened interferon response and tau-induced demyelination. The X-linked gene Toll-like receptor 7 (Tlr7) regulated sex-specific interferon response to myelin. Deletion of Tlr7 dampened sex differences while protecting against demyelination. Administering TLR7 inhibitor mitigated tau-induced motor impairment and demyelination in male mice, indicating that Tlr7 plays a role in the male-biased IFN-I response in aging- and AD-related demyelination.
Published in
Tlr7 drives sex differences in age- and Alzheimer's disease-related demyelination
Lopez-Lee C, Kodama L, Fan L et al. · Science (New York, N.Y.) 2024 · PMID 39607927 · doi:10.1126/science.adk7844
This dataset
Open GSE282329 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 GSE282329_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1186824 and SRA study SRP545560. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39607927) ↗
Study design
5 conditions, mostly with about 23 replicates each
LG93E4-NY ×24 SRY-NY ×23 LG9-NY ×23 Jax ×12 LG70-NY ×12 FCG-NY1 ×1

Supports a between-group comparison across 94 samples.

How we read this: 5 replicated groups read from 95 sample titles; they account for 94 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

+ 55 more — browse all 95 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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