GEO series

Cortical bulk RNA sequencing of APOE-TR mice under calorie restriction and normal diet

GSE286644 Mus musculus (mouse) RNA-seq (gene expression) 69 samples Submitted 2026/06/30 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 69 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: 69 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 efficacy of calorie restriction (CR) in enhancing cognition, promoting healthy aging, and extending lifespan is well-established. However, the influence of the apolipoprotein E (APOE) genotype, a key modifier of aging and age-related disorder, on the beneficial effects of CR remains unclear. In this study, we utilized humanized APOE mouse models expressing APOE2, APOE3, or APOE4 (referred to as E2, E3, and E4 mice, respectively).

Read the full summary ↓

These mice were subjected to either standard ad libitum (AL) feeding or 30% CR feeding, starting at 12 months and continuing until 20 months of age (N = 11–20/genotype/group, mixed sex). To investigate how APOE genotype modifies brain transcriptional responses to CR, we performed bulk RNA sequencing on brain cortical tissues including 69 samples from all the groups. The RNA-seq data were adjusted for flow cell, exonic coverage, and extraction batch effects. Using preprocessed gene expression profiles, we conducted weighted gene co-expression network analyses (WGCNA) and differential gene expression analyses. Consistently across both approaches, our results revealed an upregulation of the cholesterol synthesis pathway in E3- and E4-CR mice, but not in E2-CR mice. CR related DEGs also predicted the enhanced myelination, which were further validated through immunofluorescent staining for PDGFRA (an OPC marker), ASPA (an OL marker), and MBP (a myelin sheath protein), as well as electron microscopy of corpus callosum tissues in E3- and E4-CR mice, but not in E2-CR mice. Overall, our study highlights the critical role of APOE genotype in modulating the brain’s response to CR, emphasizing the importance of considering APOE genotype in developing prevention strategies for aging and age-related disorders.

This dataset

Open GSE286644 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 GSE286644_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 PRJNA1209964 and SRA study SRP557094. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

A cohort of 69 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run BU-LF-3 … BU-LF-160 and carry no group information.

Samples in this study

GSM8729939 BU-LF-3
GSM8729940 BU-LF-4
GSM8729941 BU-LF-6
GSM8729942 BU-LF-7
GSM8729943 BU-LF-10
GSM8729944 BU-LF-14
GSM8729945 BU-LF-17
GSM8729946 BU-LF-18
GSM8729947 BU-LF-19
GSM8729948 BU-LF-22
GSM8729949 BU-LF-25
GSM8729950 BU-LF-26
GSM8729951 BU-LF-31
GSM8729952 BU-LF-34
GSM8729953 BU-LF-35
GSM8729954 BU-LF-36
GSM8729955 BU-LF-38
GSM8729956 BU-LF-40
GSM8729957 BU-LF-41
GSM8729958 BU-LF-42
GSM8729959 BU-LF-46
GSM8729960 BU-LF-50
GSM8729961 BU-LF-51
GSM8729962 BU-LF-52
GSM8729963 BU-LF-56
GSM8729964 BU-LF-58
GSM8729965 BU-LF-59
GSM8729966 BU-LF-61
GSM8729967 BU-LF-63
GSM8729968 BU-LF-65
GSM8729969 BU-LF-66
GSM8729970 BU-LF-69
GSM8729971 BU-LF-70
GSM8729972 BU-LF-71
GSM8729973 BU-LF-74
GSM8729974 BU-LF-76
GSM8729975 BU-LF-81
GSM8729976 BU-LF-82
GSM8729977 BU-LF-83
GSM8729978 BU-LF-84

+ 29 more — browse all 69 samples with per-sample file links →

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Search all mouse RNA-seq datasets in GEO →

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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.