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Xist exploits three-dimensional chromosome architecture to spread across the X-chromosome

GSE46918 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 37 samples Submitted 2013/05/30 Platform GPL13112
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 37 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
37 samples: 32 distinct titles, 5 of them repeatedGroups 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)
Many large noncoding RNAs (lncRNAs) regulate chromatin, but the mechanisms by which they localize to genomic targets remain unexplored. Here we investigate the localization mechanisms of Xist during X-chromosome inactivation (XCI), a paradigm of lncRNA-mediated chromatin regulation. During the maintenance of XCI, Xist binds broadly across the X-chromosome.
Read the full summary ↓
During initiation of XCI, Xist initially transfers to distal regions across the X-chromosome that are not defined by specific sequences. Instead, Xist identifies these regions by exploiting the three-dimensional conformation of the X-chromosome. Xist initially accumulates on the periphery of actively transcribed regions and requires its silencing domain to spread across active regions. This suggests a model where Xist coats the entire X-chromosome by searching in three dimensions, modifying chromosome structure, and spreading to newly accessible locations.
This dataset
Open GSE46918 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE46918_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA203042 and SRA study SRP022711. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 23828888) ↗
Study design
32 distinct titles, 5 of them repeated
pSM33-0hr-Xist ×2 pSM33-1hr-Xist ×2 pSM33-2hr-Xist ×2 pSM33-3hr-Xist ×2 pSM33-6hr-Xist ×2

How we read this: Read from 37 sample titles: 32 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
Datasets on a similar topic

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