GEO series

Methylation pseudotime analysis for label-free profiling of the temporal chromatin landscape with long-read sequencing

GSE290978 Homo sapiens (human) DNA methylation 46 samples Submitted 2025/03/05 Platform GPL26624Platform GPL26167Platform GPL24106

At a glance

DNA methylation · human · 46 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 46 samples: 46 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.

Summary (written by the submitters)

Faithful epigenetic inheritance across cell divisions is essential to maintaining cell identity and involves numerous epigenetic modifications, whose roles in coordinating chromatin architecture are less understood. Technological approaches to temporally order epigenetic modifications throughout the cell cycle often face limitations in sequence resolution and rely on potentially damaging mitotic labeling or conversion steps.

Read the full summary ↓

Herein, we present Methylation Pseudotime Analysis Through read-level Heterogeneity (MPATH), a label- and conversion-free method to infer post-replication DNA strand maturity from methylation patterns across single molecules. We showed that MPATH is generally applicable across human embryonic stem cell (hESC) lines in which CpG methylation heterogeneity is coupled to replication, but not applicable to breast cancer cells, in which CpG methylation heterogeneity may also be associated with other factors. We also analyzed differentiated human cell lines and human and mouse mesenchymal stem cells and found that while MPATH showed reduced ability to infer DNA strand maturity within these contexts, it still captured general trends in DNA methylation that were associated with chromatin maturation. When applied to long reads generated by NOMe-seq, MPATH revealed that nucleosome compaction and CpG methylation uniformity are coupled across replication-associated timescales. Finally, extension of MPATH to phased reads reveals allele-specific trends in pseudotime distribution associated with X chromosome inactivation. Our findings suggest that when coupled with multimodal sequencing strategies, MPATH could provide valuable insights into chromatin restoration dynamics.

This dataset

Open GSE290978 in finder → Find more datasets →

Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE290978_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1231230. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

46 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 46 sample titles: 46 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

GSM8826779 BrdU 10m pulse 0h chase
GSM8826780 BrdU 10m pulse 16h chase
GSM8826781 BrdU 20m pulse 0h chase
GSM8826782 BrdU 20m pulse 16h chase
GSM8826783 BrdU 30m pulse 0h chase
GSM8826784 BrdU 30m pulse 16h chase
GSM8826785 BrdU 1h pulse 0h chase
GSM8826786 BrdU 1h pulse 16h chase
GSM8826787 Mock 0h
GSM8826788 Mock 16h
GSM8826789 BioRep1, BrdU 500 uM 0h
GSM8826790 BioRep1, BrdU 500 uM 16h
GSM8826791 BioRep1, Mock 500uM 0h
GSM8826792 BioRep2, BrdU 500 uM 0h
GSM8826793 BioRep2, BrdU 500 uM 16h
GSM8826794 HUES64_Unlabeled
GSM9644138 H9, BrdU 50uM, 10m pulse 0h chase
GSM9644139 H9, BrdU 50uM, 10m pulse 16h chase
GSM9644140 H9, BrdU 50uM, 30m pulse 0h chase
GSM9644141 H9, BrdU 50uM, 1h pulse 0h chase
GSM9644142 H9, Mock 0h
GSM9644143 H9, Mock 16h
GSM9644144 HUES8 TKO, BrdU 500 uM, 0h chase
GSM9644145 HUES8 TKO, BrdU 500 uM, 16h chase
GSM9644146 HUES8 TKO, Mock 500uM, 0h chase
GSM9644147 HUES8 TKO, Mock 500uM, 16h chase
GSM9644148 MDA-MB-231, BrdU 500 uM, 0h chase
GSM9644149 MDA-MB-231, BrdU 500 uM, 16h chase
GSM9644150 MDA-MB-231, Mock 500uM, 0h chase
GSM9644151 MDA-MB-231, Mock 500uM, 16h chase
GSM9644152 HUES64, Nocodazole
GSM9644153 HUES64, Noc_Untreated_Control
GSM9644154 Unlabeled
GSM9928752 BJ, BrdU 500uM, 0h chase
GSM9928753 BJ, BrdU 500uM, 16h chase
GSM9928754 BJ, Mock 500uM, 0h chase
GSM9928755 THP1, BrdU 500uM, 0h chase
GSM9928756 THP1, BrdU 500uM, 16h chase
GSM9928757 THP1, Mock 500uM, 0h chase
GSM9928758 hBMMSC, BrdU 500uM, 0h chase

+ 6 more — browse all 46 samples with per-sample file links →

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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.