← BioTransfer GEO Dataset Finder
GEO series

Z-Form Stabilization By The Zα Domain Of Adar1p150 Has Subtle Effects On A-To-I Editing

GSE297017 Homo sapiens (human) RNA-seq (gene expression) 39 samples Submitted 2026/05/31 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 39 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
39 samples: 13 conditions, mostly in triplicateGroups 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)
The role of Adenosine Deaminase Acting on RNA 1 (ADAR1)’s Z-conformation stabilizing Zα domain in A-to-I editing is unclear. Previous studies on Zα mutations faced limitations, including variable ADAR1p150 expression, differential editing analysis challenges, and unaccounted changes in ADAR1p150 localization. To address these issues, we developed a Cre-lox system in ADAR1p150 KO cells to generate stable cell lines expressing Zα mutant ADAR1p150 constructs.
Read the full summary ↓
Using total RNA sequencing analyzing editing clusters as a proxy for dsRNAs, we found that Zα mutations slightly decreased overall A-to-I editing, consistent with recent findings. These decreases correlated with mislocalization of ADAR1p150 rather than reduced editing specificity, and practically no statistically significant differentially edited sites were identified between wild-type and Zα mutant ADAR1p150 constructs. These results suggest that Zα’s impact on editing is minor and that phenotypes in Zα mutant mouse models and human patients may arise from editing-independent inhibition of ZBP1, rather than changes in RNA editing.
This dataset
Open GSE297017 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 GSE297017_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 PRJNA1262398 and SRA study SRP585099. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
13 conditions, mostly in triplicate
wild-type -IFNB ×3 wild-type +IFNB ×3 wild-type +IFNB, +DOX ×3 ADAR1 KO ×3 ADAR1p150 KO ×3 ADAR1p150 -DOX ×3 ADAR1p150 +DOX ×3 ADAR1p150 ++DOX ×3 +5 more

Supports a between-group comparison across 39 samples.

How we read this: 13 replicated groups read from 39 sample titles; they account for 39 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.