GEO series

A proteomics screen uncovers CTCF as a key G-quadruplex binding protein [CUT&Tag]

GSE288516 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 28 samples Submitted 2026/05/15 Platform GPL24247

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 28 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: 28 samples: 28 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.

Summary (written by the submitters)

DNA G-quadruplexes (G4s) are non-B form secondary DNA structures that are highly conserved across evolution. G4 structures occupy key regulatory sites in the mammalian genomes and are implicated in several cellular processes. However, the mechanisms by which G4s contribute to distinct facets of genome function are not well understood.

Read the full summary ↓

Here, we conduct an unbiased proteomics screen with G4s of diverse topologies to uncover novel G4 binding activities in key genomic regulators involved in regulation of nucleosome remodeling, paraspeckle assembly, RNA splicing, transcriptional elongation, and 3D genome organization. Among the most prominent hits, we identify the genomic architectural protein, CTCF as one of the strongest G4 binders. Building on this discovery, we perform extensive biochemical validation of CTCF-G4 interaction and identify CTCF mutants, with pronounced affinity for G4s over its consensus DNA motif. By implementing well-established approaches and newly developed G4 mapping tools, we define a comprehensive catalog of genomic G4s and study their association with CTCF binding. Furthermore, using genetic reconstitution studies with specific CTCF mutants, we ascribe genomic functions to CTCF-G4 interactions in regulation of CTCF occupancy, chromatin looping and gene expression. Our work establishes the G4 binding activity of CTCF and provides new insights into the functional significance of G4 structures.

This dataset

Open GSE288516 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 GSE288516_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 PRJNA1217902 and SRA study SRP560943. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

28 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 28 sample titles: 28 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

GSM8769259 EV_aux_CTCF_1_S13
GSM8769260 EV_aux_CTCF_2_S14
GSM8769261 EV_ctrl_CTCF_1_S6
GSM8769262 EV_ctrl_CTCF_2_S7
GSM8769263 FL_aux_CTCF_1_S20
GSM8769264 FL_aux_CTCF_2_S21
GSM8769265 MT_aux_CTCF_1_S23
GSM8769266 MT_aux_CTCF2_S24
GSM8769267 EV_aux_BG4_1_S11
GSM8769268 EV_aux_BG4_2_S12
GSM8769269 EV_ctrl_BG4_1_S4
GSM8769270 EV_ctrl_BG4_2_S5
GSM8769271 FL_aux_BG4_1_S18
GSM8769272 FL_aux_BG4_2_S19
GSM8769273 MT_aux_BG4_1_S27
GSM8769274 MT_aux_BG4_2_S28
GSM8769275 EV_aux_NMMb_1_S9
GSM8769276 EV_aux_NMMb_2_S10
GSM8769277 EV_ctrl_NMMb_1_S2
GSM8769278 EV_ctrl_NMMb_2_S3
GSM8769279 FL_aux_NMMb_1_S16
GSM8769280 FL_aux_NMMb_2_S17
GSM8769281 MT_aux_NMMb_1_S25
GSM8769282 MT_aux_NMMb_2_S26
GSM8769283 EV_aux_NMM_S8
GSM8769284 EV_ctrl_NMM_S1
GSM8769285 FL_aux_NMM_S15
GSM8769286 MT_aux_NMM_S22

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