Huntingtin loss-of-function contributes to transcriptional deregulation in Huntington’s disease (RNA-Seq)
RNA-seq (gene expression) · human · 11 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
- 11 samples: 11 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.
- Paper
- HTT loss-of-function contributes to RNA deregulation in developing Huntington's disease neuronsCell & bioscience · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE270472_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1126697 and SRA study SRP515337. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 11 sample titles: 11 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.
- GSM8343537 IC1_1, RNA passage 4
- GSM8343538 IC1_2, RNA passage 5
- GSM8343539 IC1_3, RNA passage 6
- GSM8343540 HD_1, RNA passage 4
- GSM8343541 HD_2, RNA passage 5
- GSM8343542 HD_3, RNA passage 6
- GSM8343543 HD_4, RNA passage 7
- GSM8343544 KO_1, RNA passage 4
- GSM8343545 KO_2, RNA passage 5
- GSM8343546 KO_3, RNA passage 6
- GSM8343547 KO_4, RNA passage 7
- GSE244979 Conserved transcriptional response to adversity-related inflammation contributes to Meniere’s disease progression [RNA-Seq 2] 28 samples shares contributes, rna-seq
- GSE244978 Conserved transcriptional response to adversity-related inflammation contributes to Meniere’s disease progression [RNA-Seq 1] 10 samples shares contributes, rna-seq
- GSE228254 Mono and biallelic inactivation of Huntingtin gene in patient-specific iPS cells reveal HTT roles in striatal development and in neuronal functions impaired in Huntington’s disease 31 samples shares huntingtin, huntington
- GSE280581 Intragenic Epigenetic Deregulation by IDH2 Mutations Synergizes with SRSF2 Mutations Causing Mis-splicing of Key Transcriptional Regulators [RNA-seq] 20 samples shares deregulation, rna-seq
- GSE254719 Dual targeting of EZH2 and Histone Deacetylases in hematological malignancies promotes transcriptional and metabolic deregulation leading to ferroptosis. [RNA-Seq] 18 samples shares deregulation, rna-seq
- GSE279442 SETD2 loss-of-function uniquely sensitizes cells to epigenetic targeting of NSD1-directed H3K36 methylation [RNA-seq] 50 samples shares loss-of-function, rna-seq
- GSE295126 VGLL1 contributes to both the transcriptome and epigenome of the developing trophoblast compartment [RNA-Seq] 43 samples shares contributes, rna-seq
- GSE298146 SOX4 Mediated Differentiation of Specific T Lymphocyte Subsets at the Maternal-Fetal Interface Contributes to Preterm Labor [RNA-Seq] 34 samples shares contributes, rna-seq
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.