← BioTransfer GEO Dataset Finder
GEO series

Inflammatory signaling differentially changes chromatin accessibility and gene expression of the PD- associated kinase LRRK2 between human and mice [ChIP-Seq]

GSE309352 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2026/03/26 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 14 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
14 samples: 3 × ChIP-Seq, human iPSC-derived microglia, IFN-γ treatment, without antibody, ChIP, vs 3 × ChIP-Seq, human iPSC-derived microglia, untreated, control, without antibody, ChIP, vs 3 × ChIP-Seq, human iPSC-derived microglia, IFN-γ treatment, STAT1 antibody, ChIP, vs 3 × ChIP-Seq, human iPSC-derived microglia, untreated, control, STAT1 antibody, ChIP,Groups 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
Inflammatory signaling differentially changes chromatin accessibility and gene expression of the PD- associated kinase LRRK2 between human and miceMolecular neurodegeneration · 2026
Summary (written by the submitters)
The genomic locus that encodes the Leucine-rich repeat kinase 2 (LRRK2) gene is highly pleomorphic, being associated with both Parkinson’s disease (PD) and Crohn’s disease (CD). As well as coding variants that are associated with risk of PD and CD and act as gain of function kinase mutations increasing phosphorylation of RAB substrates, non-coding variants in the promoter region of LRRK2 increase expression of the gene, notably in immune cells.
Read the full summary ↓
If regulation of LRRK2 expression is a causal contributor to age-related diseases, it would therefore be important to understand the mechanism(s) by which LRRK2 is regulated, particularly in the context of inflammation. We were able to show that interferon-ɣ exposure induces robust LRRK2 activation in human iPSC-derived microglia through mechanisms that involve signaling of the Janus-activated Kinase complex to phosphorylate STAT1 which then binds to the LRRK2 promoter and is associated with remodeling of chromatin structure in this genomic locus. Additional regulation includes the stress-induced transcription factor and long non-coding RNA encoded at the same locus, resulting in enhanced LRRK2 mRNA levels. However, we were unable to demonstrate any induction of Lrrk2 mRNA in the mouse brain but could show evidence of the same effect in acutely cultured human brain slices. These divergent results across species are resolved by the demonstration the introduction of a human bacterial artificial chromosome transgene into the mouse genome can then recapitulate sensitivity to interferon-ɣ in microglia. These results demonstrate that there are differences between species in how genes associated with human diseases are regulated and provide important information that should be incorporated in disease modeling.
Published in
Inflammatory signaling differentially changes chromatin accessibility and gene expression of the PD- associated kinase LRRK2 between human and mice
Beilina A, Park JH, Landeck N et al. · Molecular neurodegeneration 2026 · PMID 41851867 · doi:10.1186/s13024-026-00938-0
This dataset
Open GSE309352 in finder → Find more human 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 GSE309352_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 PRJNA1335222 and SRA study SRP628372. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41851867) ↗
Study design
3 × ChIP-Seq, human iPSC-derived microglia, IFN-γ treatment, without antibody, ChIP, vs 3 × ChIP-Seq, human iPSC-derived microglia, untreated, control, without antibody, ChIP, vs 3 × ChIP-Seq, human iPSC-derived microglia, IFN-γ treatment, STAT1 antibody, ChIP, vs 3 × ChIP-Seq, human iPSC-derived microglia, untreated, control, STAT1 antibody, ChIP,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 12 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
Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

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.