← BioTransfer GEO Dataset Finder
GEO series

RNA-seq analysis of wild-type HEK293, HEK293 treated with DMSO, ML216 or NSC617145, wild-type mESCs and dhx9KO mESCs

GSE254763 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2024/07/25 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 5 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.
Paper
Genome-wide mapping of native co-localized G4s and R-loops in living cellseLife · 2024
Summary (written by the submitters)
G4s are built by stacked guanine tetrads connected via Hoogsteen hydrogen bonds and can be formed by intra- or inter-molecular folding of the tetramers. R-loops are three-stranded structures which contain a DNA-RNA hybrid and a displaced single-stranded DNA. Both G4s and R-loops are involved in key biological processes, including transcriptional regulation, replication, genomic instability, class switch recombination in B cells, DNA damage and repair, and telomere maintenance.
Read the full summary ↓
To understand the transcriptional regulation of G4s and R-loops, we performed the RNA-seq analysis on HEK293 cells treated with the inhibitors of G4 resolving helicase ML216 or NSC617145 and mESCs in which the resolving helicase DHX9 of G4 and R-loop was knockout.
Published in
Genome-wide mapping of native co-localized G4s and R-loops in living cells
Liu T, Shen X, Ren Y et al. · eLife 2024 · PMID 39392462 · doi:10.7554/eLife.99026
This dataset
Open GSE254763 in finder → Find more 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 GSE254763_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 PRJNA1071643 and SRA study SRP487224. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39392462) ↗
Study design
5 conditions, mostly in triplicate
HEK293_DMSO ×3 HEK293_ML216 ×3 HEK293_NSC617145 ×3 mESC_WT ×3 mESC_Dhx9KO ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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 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.