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Transcriptional and epigenetic targets of MEF2C in human microglia contribute to cellular functions related to autism risk and age-related disease [ATAC-Seq]

GSE306987 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2025/10/01 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 12 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
12 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.
Summary (written by the submitters)
MEF2C is a transcription factor with wide ranging roles and has specifically been implicated in restraining the microglial inflammatory response, participating in nervous system development, and contributing to aging and neurological disease. While MEF2C murine models have provided critical insights, the homeostatic and disease-associated functions of MEF2C in human microglia remain unclear.
Read the full summary ↓
To examine this question, we profile microglia differentiated from isogenic, CRISPR-modified MEF2C haploinsufficient and knockout induced-pluripotent stem cell (iPSC) lines. A combination of transcriptomic, epigenetic and functional analyses revealed that loss of MEF2C leads to a hyperinflammatory microglial phenotype with broad impairment in phagocytosis, lipid accumulation, lysosomal dysfunction and elevated basal inflammatory cytokine and inflammasome activation. Transcriptomic and epigenetic approaches identified substantial overlap between reduced microglial MEF2C expression and primary brain idiopathic autism datasets, suggesting a broader role of microglial MEF2C dysregulation in idiopathic autism especially as relates to the transcription factors repressive functions. Reduced MEF2C expression has been associated with brain aging, and we find that reduction in MEF2C leads to a premature aging or senescence associated phenotype in microglia. These findings are extended to a murine xenotransplantation model wherein reductions in MEF2C expression in human microglia leads to an ameboid hyperinflammatory phenotype with lysosomal and lipid dysfunction. Taken together, these studies reveal novel aspects of microglial MEF2C function that contribute to homeostasis and development of neurological disease.
This dataset
Open GSE306987 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 GSE306987_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 PRJNA1314104 and SRA study SRP616665. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in duplicate
HET_237_ATAC ×2 KO_2H10_ATAC ×2 HET_2H11_ATAC ×2 Control_42N_ATAC ×2 Control_71N_ATAC ×2 KO_IG4_ATAC ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 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

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