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Aptamer-Mediated Multivalent Endogenous ADAR1 Recruitment for Highly Efficient RNA Editing

GSE334805 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2026/07/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 9 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
9 samples: 3 × CLUSTE vs 3 × MARRS vs 3 × ControlGroups 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)
Adenosine-to-inosine (A-to-I) RNA editing mediated by endogenous ADAR enzymes represents a promising therapeutic strategy for correcting disease-causing mutations at the transcript level without permanent genomic modification. To improve endogenous ADAR1 recruitment and RNA editing efficiency, we developed MARRS (Multivalent ADAR1 Recruiting RNA-editing System), a programmable RNA editing platform that incorporates engineered multivalent RNA aptamers targeting the Zα domain of ADAR1 p150 within a circular RNA scaffold.
Read the full summary ↓
RNA sequencing was performed to characterize transcriptome-wide gene expression changes associated with MARRS and CLUSTER systems compared with control samples. The dataset consists of three experimental groups (Control, CLUSTER, and MARRS), each represented by three biological replicates. These data provide a resource for investigating the molecular consequences of enhanced endogenous ADAR1 recruitment and evaluating the transcriptomic impact of programmable RNA editing strategies.
This dataset
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.

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 GSE334805_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1475822 and SRA study SRP707467. Searching any of these in the dataset finder brings you back here.

Study design
3 × CLUSTE vs 3 × MARRS vs 3 × Control

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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
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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.