GEO series

Independent cell type-specific expression and distal regulation of the 9p21 locus cell cycle regulators: p14ARF, p16INK4A, p15INK4A, and ANRIL

GSE309515 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 72 samples Submitted 2026/06/23 Platform GPL20301Platform GPL18573

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 72 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: Homo sapiens (human)
Samples: 72 samples: 6 conditions, mostly in duplicateGroups 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.

SuperSeries — this record groups several sub-series.

Summary (written by the submitters)

This SuperSeries is composed of the SubSeries listed below.

This dataset

Open GSE309515 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 GSE309515_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 PRJNA1336182 and SRA study SRP629457. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in duplicate

CRISPRa screen and dial-up scRNA-seq, WI-38 f… ×16 CRISPRa screen mRNA scRNA-seq, WI-38 fibrobla… ×16 Total RNA, WI-38 fibroblasts, PDL ×6 Region capture micro-C, WI-38 fibroblasts, PD… ×2 Region capture micro-C, WI-38 fibroblasts, PD… ×2 Region capture micro-C, WI-38 fibroblasts, PD… ×2 WI-38 fibroblasts, PDL33, CTCF ChIP ×1 WI-38 fibroblasts, PDL33, CTCF ChIP, biologic… ×1 +26 more

Supports a between-group comparison across 44 samples.

How we read this: 6 replicated groups read from 72 sample titles; they account for 44 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

GSM9268080 WI-38 fibroblasts, PDL33, CTCF ChIP
GSM9268081 WI-38 fibroblasts, PDL33, CTCF ChIP, biological replicate
GSM9268082 WI-38 fibroblasts, PDL54, CTCF ChIP
GSM9268083 WI-38 fibroblasts, PDL33, H3K27ac ChIP
GSM9268084 WI-38 fibroblasts, PDL33, H3K27ac ChIP, biological replicate
GSM9268085 WI-38 fibroblasts, PDL54, H3K27ac ChIP
GSM9268086 WI-38 fibroblasts, PDL33, whole cell extract
GSM9268087 WI-38 fibroblasts, PDL33, whole cell extract, biological replicate
GSM9268088 WI-38 fibroblasts, PDL54, whole cell extract
GSM9268101 Region capture micro-C, WI-38 fibroblasts, PDL 21 Rep1 Region capture micro-C,…
GSM9268102 Region capture micro-C, WI-38 fibroblasts, PDL 21 Rep2 Region capture micro-C,…
GSM9268103 Region capture micro-C, WI-38 fibroblasts, PDL 33 Rep1 Region capture micro-C,…
GSM9268104 Region capture micro-C, WI-38 fibroblasts, PDL 33 Rep2 Region capture micro-C,…
GSM9268105 Region capture micro-C, WI-38 fibroblasts, PDL 48 Rep 2
GSM9268106 Region capture micro-C, WI-38 fibroblasts, PDL 53.5 Rep 1
GSM9268107 Region capture micro-C, WI-38 fibroblasts, PDL 57 Rep 1 Region capture micro-C,…
GSM9268108 Region capture micro-C, WI-38 fibroblasts, PDL 57 Rep 2 Region capture micro-C,…
GSM9268113 Total RNA, WI-38 fibroblasts, PDL 21 Total RNA, WI-38 fibrob…
GSM9268114 Total RNA, WI-38 fibroblasts, PDL 33 Total RNA, WI-38 fibrob…
GSM9268115 Total RNA, WI-38 fibroblasts, PDL 41 Total RNA, WI-38 fibrob…
GSM9268116 Total RNA, WI-38 fibroblasts, PDL 48 Total RNA, WI-38 fibrob…
GSM9268117 Total RNA, WI-38 fibroblasts, PDL 53.5
GSM9268118 Total RNA, WI-38 fibroblasts, PDL 54 Total RNA, WI-38 fibrob…
GSM9268119 Total RNA, WI-38 fibroblasts, PDL 57 Total RNA, WI-38 fibrob…
GSM9268130 Dial-up scRNA-seq, WI-38 fibroblasts, PDL 25 (Chan et al. 2022)
GSM9268131 Dial-up scRNA-seq, WI-38 fibroblasts, PDL 29 (Chan et al. 2022)
GSM9268132 Dial-up scRNA-seq, WI-38 fibroblasts, PDL 33 (Chan et al. 2022)
GSM9268133 Dial-up scRNA-seq, WI-38 fibroblasts, PDL 37 (Chan et al. 2022)
GSM9268134 Dial-up scRNA-seq, WI-38 fibroblasts, PDL 46 (Chan et al. 2022)
GSM9268135 Dial-up scRNA-seq, WI-38 fibroblasts, PDL 50 (Chan et al. 2022)
GSM9268136 Dial-up scRNA-seq, breast tissue sample BRCA1-C (Gray et al. 2022).
GSM9268137 Dial-up scRNA-seq, breast tissue sample BRCA1-D (Gray et al. 2022).
GSM9268138 Dial-up scRNA-seq, breast tissue sample BRCA1-H (Gray et al. 2022).
GSM9268139 Dial-up scRNA-seq, breast tissue sample BRCA2-B (Gray et al. 2022).
GSM9268140 Dial-up scRNA-seq, breast tissue sample BRCA2-D (Gray et al. 2022).
GSM9268141 Dial-up scRNA-seq, breast tissue sample BRCA2-E (Gray et al. 2022).
GSM9268142 Dial-up scRNA-seq, breast tissue sample BRCA2-A (Gray et al. 2022).
GSM9268143 Dial-up scRNA-seq, breast tissue sample WT-A (Gray et al. 2022).
GSM9268144 Dial-up scRNA-seq, breast tissue sample WT-D (Gray et al. 2022).
GSM9268145 Dial-up scRNA-seq, breast tissue sample WT-C (Gray et al. 2022).

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

GSE309511 Independent cell type-specific expression and distal regulation of the 9p21 locus cell cycle regulators: p14ARF, p16INK4A, p15INK4A, and ANRIL [CRISPR and scRNA-seq] 32 samples shares p16ink4a, p15ink4a, p14arf, anril, 9p21, type-specific, independent, regulators
GSE309498 Independent cell type-specific expression and distal regulation of the 9p21 locus cell cycle regulators: p14ARF, p16INK4A, p15INK4A, and ANRIL [scRNA-seq] 16 samples shares p16ink4a, p15ink4a, p14arf, anril, 9p21, type-specific, independent, regulators
GSE309491 Independent cell type-specific expression and distal regulation of the 9p21 locus cell cycle regulators: p14ARF, p16INK4A, p15INK4A, and ANRIL [ChIP-seq] 9 samples shares p16ink4a, p15ink4a, p14arf, anril, 9p21, type-specific, independent, regulators
GSE309495 Independent cell type-specific expression and distal regulation of the 9p21 locus cell cycle regulators: p14ARF, p16INK4A, p15INK4A, and ANRIL [RNA-seq] 7 samples shares p16ink4a, p15ink4a, p14arf, anril, 9p21, type-specific, independent, regulators
GSE270684 The EZH2 and EZH1 inhibitor valemetostat derepresses p16INK4a to induce early endomitotic exit in megakaryocytes [scATAC-Seq] 66 samples shares p16ink4a
GSE266210 Bulk RNA-sequencing results of p16INK4A-high and -low glioblastoma, IDH-wild type, grade 4. 11 samples shares p16ink4a
GSE270683 The EZH2 and EZH1 inhibitor valemetostat derepresses p16INK4a to induce early endomitotic exit in megakaryocytes [RNA-Seq] 6 samples shares p16ink4a
GSE65392 Circular non-coding RNA ANRIL modulates ribosomal RNA maturation and atherosclerosis in humans. 6 samples shares anril

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