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Induction of a transcriptional adaptation response by RNA destabilization events [dst175]

GSE286097 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2025/03/17 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
12 samples: 3 × Wildtype vs 3 × PTC1 vs 3 × PTC2 vs 3 × LDGroups 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)
Transcriptional adaptation (TA) is a cellular process whereby mRNA-destabilizing mutations lead to the transcriptional upregulation of so-called adapting genes. The nature of the TA-triggering factor(s) remains unclear. Here, we first generated Cas9-induced mutations in mouse Actg1, including an mRNA-destabilizing allele and an RNA-less allele.
Read the full summary ↓
We find in the Actg1 mRNA-destabilizing allele, higher levels of Actg2 mRNA as well as increased chromatin accessibility at the Actg2 locus compared with wild-type and the RNA-less allele. Notably, Cas13d experiments show that Actg1 mRNA cleavage, but not Actg1 pre-mRNA cleavage, also triggers Actg2 upregulation; however, this upregulation is not associated with increased chromatin accessibility at the Actg2 locus. Furthermore, time course experiments show that increased Actg2 expression persists even after Actg1 mRNA degradation by Cas13d ceases. Together, our data highlight the importance of cytoplasmic mRNA degradation as a trigger for the TA response and suggest that chromatin remodeling is not necessary for TA.
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 GSE286097_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1207915 and SRA study SRP555998. Searching any of these in the dataset finder brings you back here.

Study design
3 × Wildtype vs 3 × PTC1 vs 3 × PTC2 vs 3 × LD

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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