← BioTransfer GEO Dataset Finder
GEO series

Persistent epigenome anomalies in induced pluripotent stem cells from late-onset sporadic Alzheimer’s disease cases [RNA-seq]

GSE255982 Homo sapiens (human) RNA-seq (gene expression) 52 samples Submitted 2024/07/30 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 52 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
Homo sapiens (human)
Samples
52 samples: 18 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.
Summary (written by the submitters)
Reprogramming of adult somatic cells into induced pluripotent stem cells (iPSCs) resets the aging clock and is thought to erase other epigenomic marks. Here we show that iPSCs from late-onset sporadic Alzheimer’s disease (AD) cases retain epigenomic anomalies that supersede developmental defects, genomic instability, and neurodegeneration.
Read the full summary ↓
When compared to iPSCs from elderly controls, AD iPSCs display reduced BMI1 and KDM5A expression, a more relax heterochromatin, and an altered DNA methylome. AD neuroepithelial cells show lesser efficient neural induction and forebrain specification, together with perturbed WNT signaling. They also present a unique genomic instability phenotype characterized by replication stress and DNA damage at the nuclear envelope-associated heterochromatin. BMI1 knockdown in control neuroepithelial cells phenocopied the AD-related pathologies. Long-term AD neuronal cultures show a dedifferentiation and loss-of-cell identity phenotype resembling epigenome erosion. BMI1 overexpression in AD neurons mitigates amyloid accumulation, tau pathology, heterochromatin fragmentation and G4 DNA induction. These findings implicate persistent epigenomic anomalies or uncharacterized genetic alterations working in trans on the epigenome in AD iPSCs, which could have broader implications in our understanding of the disease origin and pathophysiological mechanisms.
This dataset
Open GSE255982 in finder → Find more human 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 GSE255982_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 PRJNA1077346 and SRA study SRP490059. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in duplicate
GB14NJ ×3 GB1410 ×2 GB2_1 ×2 GB1_4 ×2 AD17_1 ×2 AD1_1 ×2 AD2_2 ×2 AD18_1 ×2 +25 more

Supports a between-group comparison across 37 samples.

How we read this: 18 replicated groups read from 52 sample titles; they account for 37 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

+ 12 more — browse all 52 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.