GEO series

KMT2D controls cerebellar granule cell differentiation by temporally activating neuronal transcriptional factor genes [CUT&RUN]

GSE282802 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2025/11/14 Platform GPL21103

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 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: Mus musculus (mouse)
Samples: 10 samples: 10 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: KMT2D temporally activates neuronal transcriptional factor genes to mediate cerebellar granule cell differentiationScience advances · 2025

Summary (written by the submitters)

Spatiotemporal gene expression is the fundamental feature for cellular differentiation, including neurogenesis. The epigenetic mechanism underlying spatiotemporal gene regulation during in vivo cellular differentiation remains largely unknown. The cerebellum contains ~80% of the total number of neurons in the human brain. Granule cells (GCs) constitute the vast majority of cerebellar neurons, and GC genesis is spatiotemporally regulated.

Read the full summary ↓

Here, we show that Atoh1-Cre-mediated knockout (ACKO) of the Kmt2d gene encoding the lysine methyltransferase KMT2D (MLL4 and a COMPASS-like enzyme) in the cerebellar GC lineage in mice inhibits cerebellar GC differentiation while increasing cerebellar cell proliferation. Kmt2d ACKO impaired cerebellum-associated behaviors and caused facial peculiarity, microcephaly, and smaller body size (Kabuki syndrome-like characteristics) in mice. KMT2D temporally activates neuronal differentiation programs in cerebellar GC lineage. KMT2D-mediated activation of the key neuronal transcription factor genes En2, Pax6, and Myt1l is critical for GC differentiation. KMT2D positively programs super-enhancers/enhancers associated with these genes. Single cell RNA-seq analysis showed that Kmt2d ACKO inhibited the transition of GC progenitor to GCs while having a cell-non-autonomous impact on other cerebellar cells. These findings provide a unique epigenetic mechanism in which KMT2D temporally orchestrates gene expression required for cerebellar GC differentiation by programming neuronal enhancers.

Published in

KMT2D temporally activates neuronal transcriptional factor genes to mediate cerebellar granule cell differentiation

Dhar SS, Ko KP, Jang J et al. · Science advances 2025 · PMID 41004595 · doi:10.1126/sciadv.adu7174

This dataset

Open GSE282802 in finder → Find more mouse 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 GSE282802_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 PRJNA1190443 and SRA study SRP547477. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41004595) ↗

Study design

10 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 10 sample titles: 10 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

GSM8650760 GCP-CB cells, IgG, Control, replicate 1, SD1, Input
GSM8650761 GCP-CB cells, H3K27ac, Control, replicate 1, SD2, CUT&RUN
GSM8650762 GCP-CB cells, H3K27ac, Control, replicate 2, SD3, CUT&RUN
GSM8650763 GCP-CB cells, IgG, KO, replicate 1, SD4, Input
GSM8650764 GCP-CB cells, H3K27ac, KO, replicate 1, SD5, CUT&RUN
GSM8650765 GCP-CB cells, H3K7ac, KO, replicate 2, SD6, CUT&RUN
GSM8650766 GCP-CB cells, KMT2D, Control, replicate 1, SD2, CUT&RUN
GSM8650767 GCP-CB cells, KMT2D, Control, replicate 2, SD3, CUT&RUN
GSM8650768 GCP-CB cells, KMT2D, KO, replicate 1, SD5, CUT&RUN
GSM8650769 GCP-CB cells, KMT2D, KO, replicate 2, SD6, CUT&RUN

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