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3D genome organization during TGFB-induced transcription requires nuclear microRNA and G-quadruplexes [Cut&Tag]

GSE273972 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2024/09/27 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: 12 samples, each with a distinct title — no replicated groupsGroups 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
Nuclear microRNA 9 mediates G-quadruplex formation and 3D genome organization during TGF-β-induced transcriptionNature communications · 2024
Summary (written by the submitters)
Studying the dynamics of three-dimensional (3D) chromatin structure is essential to the understanding of biological processes in the nucleus. Integrative analysis of multi-omics data in recent publications have provided comprehensive and multilevel insight into 3D genome organization emphasizing its role for transcriptional regulation.
Read the full summary ↓
While enhancers are regulatory elements that play a central role in the spatiotemporal control of gene expression, chromatin looping has been broadly accepted as a means for enhancer-promoter interactions yielding cell-type-specific gene expression signatures. On the other hand, G-quadruplexes (G4s) are non-canonical DNA secondary structures that are enriched at promoters and related to increased gene expression. However, the role of G4s in promoter-distal regulatory elements, such as super-enhancers (SE), as well as in 3D genome organization and chromatin looping mediating long-range enhancer-promoter interactions has remained elusive. Here we show that mature microRNA 9 (miR-9) is enriched at promoters and SE of genes that are inducible by tissue growth factor beta 1 (TGFB1) signaling. Further, we find that nuclear miR-9 is required for chromatin features related to increased transcriptional activity, such as broad domains of the euchromatin histone mark H3K4me3 (histone 3 tri-methylated lysine 4) and G4s. Moreover, we show that nuclear miR-9 is required for promoter-super-enhancer looping. Our study places a nuclear microRNA in the same structural and functional context with G4s and promoter-enhancer interactions during 3D genome organization and transcriptional activation induced by TGFB1 signaling, a critical regulator of proliferation programs in cancer and fibrosis.
Published in
Nuclear microRNA 9 mediates G-quadruplex formation and 3D genome organization during TGF-β-induced transcription
Cordero J, Swaminathan G, Rogel-Ayala DG et al. · Nature communications 2024 · PMID 39706840 · doi:10.1038/s41467-024-54740-x
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 GSE273972_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 PRJNA1144390 and SRA study SRP524241. Searching any of these in the dataset finder brings you back here.

Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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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