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Effect of TOP1 knockdown and/or RNase H OE on the transcriptional profile of MCF-7 cells [CEL_Seq]

GSE241306 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2024/05/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 4 × CEL_seq_ctrl_siRNA_EV vs 4 × CEL_seq_ctrl_siRNA_Rnase_H_OE vs 4 × CEL_seq_TOP1_KD_EV vs 4 × CEL_seq_TOP1_KD_Rnase_H_OEGroups 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
Protocol for mapping physiological DSBs using in-suspension break labeling in situ and sequencingSTAR protocols · 2024
Summary (written by the submitters)
DNA double-stranded breaks (DSBs) pose a significant threat to genomic integrity, and their generation during essential cellular processes like transcription remains poorly understood. In this study, we employed CEL-seq technique to investigate the effect of TOP1 KD and RNase H OE on transcriptional profile, with the different genetic manipulations.
Read the full summary ↓
Our findings revealed the presence of DSBs at highly expressed genes enriched with TOP1 and R-loops, indicating their crucial involvement in transcription-associated genomic instability. Depletion of R-loops and TOP1 specifically reduced DSBs at highly expressed genes, uncovering their pivotal roles in transcriptional DSB formation. By elucidating the intricate interplay between TOP1cc trapping, R-loops, and DSBs, our study provides novel insights into the mechanisms underlying transcription-associated genomic instability. Moreover, we establish a link between transcriptional DSBs and early molecular changes driving cancer development. Notably, our study highlights the distinct etiology and molecular characteristics of driver mutations compared to passenger mutations, shedding light on the potential for targeted therapeutic strategies. Overall, these findings deepen our understanding of the regulatory mechanisms governing DSBs in hypertranscribed genes associated with carcinogenesis, opening avenues for future research and therapeutic interventions.
Published in
Protocol for mapping physiological DSBs using in-suspension break labeling in situ and sequencing
Hidmi O, Oster S, Shatleh D et al. · STAR protocols 2024 · PMID 38717906 · doi:10.1016/j.xpro.2024.103059
This dataset
Open GSE241306 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 GSE241306_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 PRJNA1007671 and SRA study SRP456144. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38717906) ↗
Study design
4 × CEL_seq_ctrl_siRNA_EV vs 4 × CEL_seq_ctrl_siRNA_Rnase_H_OE vs 4 × CEL_seq_TOP1_KD_EV vs 4 × CEL_seq_TOP1_KD_Rnase_H_OE

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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

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