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Gene expression changes in human pluripotent and fibroblast cells and mouse embryonic fibroblasts upon NORAD lncRNA knockdown

GSE241264 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2024/12/22 Platform GPL30173Platform GPL30172Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 34 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
34 samples: 10 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
lncRNA NORAD modulates STAT3/STAT1 balance and innate immune responses in human cells via interaction with STAT3Nature communications · 2025
Summary (written by the submitters)
RNA sequencing data from knockdowns of the long non-coding RNA NORAD in human foreskin fibroblasts (HFFs), human embryonic stem cells (hESCs), and mouse embryonic fibroblasts (MEFs) for varying durations (8–72 hours, depending on the cell type). Total RNA was purified using TRI-reagent, and libraries were prepared using the CEL-seq2 protocol. RNA-seq data were processed with cutadapt, aligned to the reference genome using RNA-STAR, and gene expression counts were generated with HTSEQ count.
Published in
lncRNA NORAD modulates STAT3/STAT1 balance and innate immune responses in human cells via interaction with STAT3
Argoetti A, Shalev D, Polyak G et al. · Nature communications 2025 · PMID 39794357 · doi:10.1038/s41467-025-55822-0
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 GSE241264_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 PRJNA1007599 and SRA study SRP456097. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly with about 4 replicates each
ES_si_control ×4 ES_si_NORAD ×4 HFF_si_NORAD_16h ×4 HFF_si_control_16h ×4 HFF_si_control_24h ×4 HFF_si_NORAD_24h ×4 MEF_si_control ×3 MEF_si_Norad ×3 +2 more

Supports a between-group comparison across 34 samples.

How we read this: 10 replicated groups read from 34 sample titles; they account for 34 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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