Genome wide mapping of the effect of SMAD2/3 regulating treatments upon the epigenomic landscape in high passage growth arrested cells being withdrawn from rapamycin
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 33 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
- 33 samples: 33 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
- Ligand-specific regulation of a binary enhancer code dictating cellular senescenceProceedings of the National Academy of Sciences of the United States of America · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE146568_RAW.tar (it can run to tens of gigabytes).
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 PRJNA610866 and SRA study SRP251897. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 33 sample titles: 33 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.
- GSM4395493 TSF101_BJ_HPGA_anti-SMAD23_RM_Control
- GSM4395494 TSF102_BJ_HPGA_anti-SMAD23_RM_Activin
- GSM4395495 TSF103_BJ_HPGA_anti-SMAD23_RM_TGFB2
- GSM4395496 TSF104_BJ_HPGA_anti-SMAD23_RM_Control
- GSM4395497 TSF105_BJ_HPGA_anti-SMAD23_RM_Inhibin
- GSM4395498 TSF106_BJ_HPGA_anti-SMAD23_RM_Inhibin+TGFB2
- GSM4395499 TSF107_BJ_HPGA_anti-SMAD23_RW_Control
- GSM4395500 TSF108_BJ_HPGA_anti-SMAD23_RW_Activin
- GSM4395501 TSF109_BJ_HPGA_anti-SMAD23_RW_TGFB2
- GSM4395502 TSF110_BJ_HPGA_anti-SMAD23_RW_Control
- GSM4395503 TSF111_BJ_HPGA_anti-SMAD23_RW_Inhibin
- GSM4395504 TSF112_BJ_HPGA_anti-SMAD23_RW_Inhibin+TGFB2
- GSM4395505 TSF131_BJ_HPGA_anti-NFI_RM_Control
- GSM4395506 TSF132_BJ_HPGA_anti-NFI_RW_Control
- GSM4395507 TSF141_BJ_HPGA_anti-p65_R10_Maintained_Control
- GSM4395508 TSF142_BJ_HPGA_anti-p65_R10_Withdrawal_Control
- GSM4395509 TSF143_BJ_HPGA_anti-p65_R10_Withdrawal_Activin
- GSM4395510 TSF144_BJ_HPGA_anti-p65_R10_Withdrawal_TGFB2
- GSM4395511 TSF145_BJ_HPGA_anti-p65_R10_Withdrawal_Control
- GSM4395512 TSF146_BJ_HPGA_anti-p65_R10_Withdrawal_Inhibin
- GSM4395513 TSF147_BJ_HPGA_anti-p65_R10_Withdrawal_Inhibin+TGFB2
- GSM4395514 TSF56_BJ_HPGA_anti-H3K27ac_RM_Control
- GSM4395515 TSF57_BJ_HPGA_anti-H3K27ac_RM_Activin
- GSM4395516 TSF58_BJ_HPGA_anti-H3K27ac_RM_TGFB2
- GSM4395517 TSF59_BJ_HPGA_anti-H3K27ac_RM_Control
- GSM4395518 TSF60_BJ_HPGA_anti-H3K27ac_RM_Inhibin
- GSM4395519 TSF61_BJ_HPGA_anti-H3K27ac_RM_Inhibin+TGFB2
- GSM4395520 TSF62_BJ_HPGA_anti-H3K27ac_RW_Control
- GSM4395521 TSF63_BJ_HPGA_anti-H3K27ac_RW_Activin
- GSM4395522 TSF64_BJ_HPGA_anti-H3K27ac_RW_TGFB2
- GSM4395523 TSF65_BJ_HPGA_anti-H3K27ac_RW_Control
- GSM4395524 TSF66_BJ_HPGA_anti-H3K27ac_RW_Inhibin
- GSM4395525 TSF67_BJ_HPGA_anti-H3K27ac_RW_Inhibin+TGFB2
- GSE313611 IGF2BP3 promotes progression of head and neck cancers through the circHECTD2/hsa_miR_4310/7157-5p/Smad2 signaling axis in an m6A modification–dependent manner 21 samples shares smad2
- GSE298598 METTL3/YTHDF2 axis inhibits cell proliferation and fibrosis by degrading the N6-methyladenosine modification of TCF7L2-Smad2/Smad3 mRNA in pterygium 12 samples shares smad2
- GSE280574 mChIP-seq for high-throughput epigenomic profiling reveals a decoupling of H2A.Z and H3K4me3 in cancer 576 samples shares epigenomic
- GSE279298 Comprehensive identification of coronary artery disease-associated variants regulating vascular smooth muscle cell gene expression [CUT&RUN] 48 samples shares regulating
- GSE306127 Impact of vitamin D deficiency on defective endometrial decidualization and the repressive role of VDR in the epigenomic network [CUT&Run] 48 samples shares epigenomic
- GSE329231 Epigenomic profiling of H3K9me3 and H3K27ac across melanoma cell lines with different mutational backgrounds 45 samples shares epigenomic
- GSE307363 3D epigenomic landscape of human retinal pigment epithelium [CUT&Tag] 40 samples shares epigenomic
- GSE246585 Epigenomic exploration of decidualizing human endometrial stromal cell dynamics 40 samples shares epigenomic
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.