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Lactylation of histone variant MacroH2A1 at K134 regulates osteogenic differentiation of bone marrow mesenchymal stem cells [ATAC]

GSE331503 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 2 samples Submitted 2026/05/30 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 2 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
2 samples
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)
Osteoporosis, a prevalent age-related bone disorder, stems from imbalanced osteoclast/osteoblast activity and skewed mesenchymal stem cell (MSC) lineage commitment. Although lactate is linked to osteoporosis pathogenesis, the role of protein lactylation in MSC osteogenic differentiation remains unelucidated. This experiment explored protein lactylation during early MSC osteogenic differentiation, focusing on histone variant MacroH2A1.
Read the full summary ↓
Proteomics identified 375–318 lactylated proteins across undifferentiated, osteogenic differentiation Day 3 (OB3), and adipogenic differentiation Day 3 (AD3) MSCs; MacroH2A1 lactylation at lysine 134 (K134) was downregulated in OB3. MacroH2A1(K134Ala) mutation (disrupting lactylation) enhanced MSC osteogenesis. In ovariectomized mice, AAV-MacroH2A1(K134Ala) increased femoral trabecular bone mass and reduced marrow adipose tissue. This experiment demonstrates that MacroH2A1 K134 lactylation regulates MSC osteogenic commitment via epigenetic and transcriptional modulation, offering mechanistic insights and a potential therapeutic target for osteoporosis.
This dataset
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.

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 GSE331503_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1468496 and SRA study SRP702272. Searching any of these in the dataset finder brings you back here.

Samples in this study

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