GEO series

DNMT1 RFTS mutation alters RNA splicing and drives neurodegeneration via its RNA-binding function [RNA-Seq]

GSE284387 Homo sapiens (human) RNA-seq (gene expression) 26 samples Submitted 2026/06/01 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 26 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: 26 samples: 26 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 GSE284387 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 GSE284387_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 PRJNA1198923 and SRA study SRP551761. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

26 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 26 sample titles: 26 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

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
GSM8866183 NPC, WT_1, NC, batch2, rna-seq
GSM8866184 NPC, WT_2, NC, batch2, rna-seq
GSM8866185 NPC, CR_1, NC, batch2, rna-seq
GSM8866186 NPC, CR_2, NC, batch2, rna-seq
GSM8866187 NPC, CR_1, procainimide, batch2, rna-seq
GSM8866188 NPC, CR_2, procainimide, batch2, rna-seq

Datasets on a similar topic

GSE284549 RFTS mutation alters RNA splicing and drives neurodegeneration via its RNA-binding function 47 samples shares rfts, neurodegeneration, rna-binding, mutation, splicing, alters
GSE329304 SUMOylation enhances DNMT1 function to repress mega-intergenic RNAs and viral mimicry [ChIP_gUHRF1-and-WT-vs-RFTS] 13 samples shares dnmt1, rfts
GSE337276 DNA methylation maintenance by DNMT1 is essential for human trophoblast stem cell homeostasis and differentiation [RNA-seq] 15 samples shares dnmt1, rna-seq
GSE319745 DNMT1 loss leads to hypermethylation of a subset of late replicating domains by DNMT3A (RNA-seq) 10 samples shares dnmt1, rna-seq
GSE305298 RNA-seq data from human HCT116 wild-type cells, HCT116 DNMT1 hypomorphs, and HCT116 UHRF1 hypomorphs. 8 samples shares dnmt1, rna-seq
GSE298942 Discovery of a Novel DNMT1 Inhibitor with Improved Efficacy in Treating β-Thalassemia [RNA-seq] 8 samples shares dnmt1, rna-seq
GSE290803 Oncogenic role of the DNMT1 in diffuse large B-cell lymphomas [RNA-seq] 6 samples shares dnmt1, rna-seq
GSE290282 Large-scale tethered screen of RNA-binding proteins reveals novel regulators of poly(A) site selection [RNA-Seq] 92 samples shares rna-binding, rna-seq

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