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Comparative gene expression profiling analysis of hippocampus and liver RNA-seq data for young (3-month-old) and aged (22-month-old) WT mice in both control and ethanol feeding conditions.

GSE283201 Mus musculus (mouse) RNA-seq (gene expression) 32 samples Submitted 2025/12/04 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 32 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
32 samples: 8 conditions, mostly with about 4 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.
Summary (written by the submitters)
Alcohol consumption is believed to affect Alzheimer's disease (AD) risk, but the contributing mechanisms are not well understood. A potential mediator of the proposed alcohol-AD connection is autophagy, a degradation pathway that maintains organelle and protein homeostasis. The purpose of this study is to explore whether chronic alcohol consumption worsens the age-related decline in lysosomal biogenesis in the brain and exacerbates cognitive decline associated with aging.
Read the full summary ↓
To explore the effect of alcohol on brain autophagy, we exposed young (3-month old) and aged (23-month old) mice to chronic plus binge alcohol-feeding paradigms and the mouse brain and liver RNA were extracted followed by RNA sequencing analysis.
This dataset
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.

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 GSE283201_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1192316 and SRA study SRP548442. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly with about 4 replicates each
H-Y-EDE ×4 H-Y-CDM ×4 H-A-EDE ×4 H-A-CDM ×4 L-Y-EDE ×4 L-Y-CDM ×4 L-A-EDE ×4 L-A-CDM ×4

Supports a between-group comparison across 32 samples.

How we read this: 8 replicated groups read from 32 sample titles; they account for 32 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
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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.