GEO series

RFTS mutation alters RNA splicing and drives neurodegeneration via its RNA-binding function

GSE284549 Homo sapiens (human) DNA methylation 47 samples Submitted 2026/06/01 Platform GPL24676

At a glance

DNA methylation · human · 47 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 47 samples: 47 samples, each with a distinct title — no replicated groupsGroups 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)

DNA Methyltransferase 1 (DNMT1) is a key enzyme in maintaining DNA methylation. Mutations in the RFTS domain of DNMT1 are associated with two neurodegenerative diseases: Hereditary sensory and autonomic neuropathy type 1E with dementia and hearing loss (HSAN1E) and Autosomal dominant cerebellar ataxia, deafness, and narcolepsy (ADCA-DN), the molecular pathogenic mechanisms of which have not yet been elucidated.

Read the full summary ↓

Pre-mRNA alternative splicing is an important post-transcriptional process for increasing protein functional diversity in organisms, and the dysregulation of the alternative splicing process plays a significant role in the occurrence and development of neurodegenerative diseases.

This dataset

Open GSE284549 in finder → Find more human methylation 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 GSE284549_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1199509 and SRA study SRP551755. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

47 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 47 sample titles: 47 distinct titles with little repetition. 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

GSM8683152 Hela, siNC_1, rrbs-seq
GSM8683153 Hela, siNC_2, rrbs-seq
GSM8683154 Hela, siNC_3, rrbs-seq
GSM8683155 Hela, siDNMT1_1, rrbs-seq
GSM8683156 Hela, siDNMT1_2, rrbs-seq
GSM8683157 Hela, siDNMT1_3, rrbs-seq
GSM8683158 NPC, WT_1, rrbs-seq
GSM8683159 NPC, WT_2, rrbs-seq
GSM8683160 NPC, HT_1, rrbs-seq
GSM8683161 NPC, HT_2, rrbs-seq
GSM8683162 NPC, AV_1, rrbs-seq
GSM8683163 NPC, AV_2, rrbs-seq
GSM8683164 Hela, siNC_1, rna-seq
GSM8683165 Hela, siNC_2, rna-seq
GSM8683166 Hela, siNC_3, rna-seq
GSM8683167 Hela, siDNMT1_1, rna-seq
GSM8683168 Hela, siDNMT1_2, rna-seq
GSM8683169 Hela, siDNMT1_3, rna-seq
GSM8683170 NPC, WT_1, NC, rna-seq
GSM8683171 NPC, WT_2, NC, rna-seq
GSM8683172 NPC, WT_3, NC, rna-seq
GSM8683173 NPC, WT_4, NC, rna-seq
GSM8683174 NPC, HT_1, NC, rna-seq
GSM8683175 NPC, HT_2, NC, rna-seq
GSM8683176 NPC, HT_3, NC, rna-seq
GSM8683177 NPC, HT_4, NC, rna-seq
GSM8683178 NPC, AV_1, NC, rna-seq
GSM8683179 NPC, AV_2, NC, rna-seq
GSM8683180 NPC, AV_3, NC, rna-seq
GSM8683181 NPC, AV_4, NC, rna-seq
GSM8683182 NPC, HT_1, procainimide, rna-seq
GSM8683183 NPC, HT_2, procainimide, rna-seq
GSM8683208 NPC, WT_1, rna-bis-seq
GSM8683209 NPC, WT_2, rna-bis-seq
GSM8683210 NPC, WT_3, rna-bis-seq
GSM8683211 NPC, HT_1, rna-bis-seq
GSM8683212 NPC, HT_2, rna-bis-seq
GSM8683213 NPC, HT_3, rna-bis-seq
GSM8683214 NPC, AV_1, rna-bis-seq
GSM8683215 NPC, AV_2, rna-bis-seq

+ 7 more — browse all 47 samples with per-sample file links →

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GSE297199 The landscape of gain and loss of function mutations in melanoma [RNA-seq] 242 samples shares mutation
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GSE279322 Development of MAPT S305 mutation models exhibiting elevated 4R tau expression, resulting in altered neuronal and astrocytic function 156 samples shares mutation
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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.