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Transcriptional profiling of hippocampus from a zQ175 KI mouse model of Huntington's disease treated with either HTT-10150 siRNA targeting full-length HTT or combination of HTT-634 and HTT-486 siRNAs targeting HTT1a

GSE284500 Mus musculus (mouse) RNA-seq (gene expression) 192 samples Submitted 2026/05/05 Platform GPL24247Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 192 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
192 samples: 48 conditions, mostly with about 4 replicates eachGroups 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
Lowering the HTT1a transcript as an effective therapy for Huntington's disease in a knockin mouse modelScience translational medicine · 2026
Summary (written by the submitters)
In this study, we conducted a comprehensive transcriptional profiling of the hippocampus utilizing a zQ175 knock-in (KI) mouse model of Huntington's disease, which was treated with either HTT-10150 siRNA specifically designed to target the full-length huntingtin (Htt) mRNA or combination of HTT-634 and HTT-486 siRNAs targeting HTT1a. Our investigation aimed to assess the impact of this intervention across different time points.
Published in
Lowering the HTT1a transcript as an effective therapy for Huntington's disease in a knockin mouse model
Papadopoulou AS, Alterman J, Landles C et al. · Science translational medicine 2026 · PMID 41849583 · doi:10.1126/scitranslmed.adw2495
This dataset
Open GSE284500 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 GSE284500_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 PRJNA1199444 and SRA study SRP552074. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41849583) ↗
Study design
48 conditions, mostly with about 4 replicates each
2.6[8]10_WT_NTC_HIP_female ×4 2.6[8]10_WT_HTT-634.486_HIP_female ×4 2.6[8]10_WT_HTT-10150_HIP_female ×4 2.6[8]10_zQ175_NTC_HIP_female ×4 2.6[8]10_zQ175_HTT-10150_HIP_female ×4 2.6[8]10_zQ175_HTT-634.486_HIP_female ×4 2.6[8]10_zQ175_Untreated_HIP_female ×4 2.6[8]10_WT_Untreated_HIP_male ×4 +40 more

Supports a between-group comparison across 192 samples.

How we read this: 48 replicated groups read from 192 sample titles; they account for 192 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

+ 152 more — browse all 192 samples with per-sample file links →

Datasets on a similar topic

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.