GEO series

KMT2D-deficiency destabilizes lineage progression in immature neural progenitors

GSE302350 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2026/02/17 Platform GPL34281

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 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: 16 samples: 16 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.

Summary (written by the submitters)

Neurodevelopment is driven by integrated regulation of chromatin shaping, transcription, and proliferative timing. Although KMT2D is known to catalyze H3K4 methylation at promoters and enhancers to activate lineage genes, its role in regulating fate specification within neural progenitor populations remains poorly defined. We performed single-cell multiome sequencing on human induced pluripotent stem cell (hiPSC)-derived cerebral organoids to simultaneously profile chromatin and transcriptional states in KMT2D-deficient cells.

Read the full summary ↓

We found that lineage transcription factors such as PAX6, NEUROD4, and OLIG1 showed premature activation accompanied by disrupted temporal coordination between chromatin accessibility and transcription, indicating unstable regulation that fails to sustain the expression of several lineage-specific genes. Live-cell imaging using FUCCI reporters revealed that KMT2D-deficient progenitors accumulate in G1 phase more rapidly within 24-hours of neural induction. Further, KS1 patient-derived neural progenitors showed similar, yet less pronounced, disruptions in lineage mark expression over time. Our findings suggest that loss of KMT2D perturbs the coordination of chromatin accessibility, gene expression, and cell cycle timing in neural progenitors at the onset of lineage acquisition, potentially initiating generational instability that impairs lineage resolution and alters differentiation trajectories over time.

This dataset

Open GSE302350 in finder → Find more human RNA-seq 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 GSE302350_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 PRJNA1290236 and SRA study SRP600097. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

16 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 16 sample titles: 16 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

GSM9102443 Multiome, WT Cerebral organoids, 51 day, Rep 1, RNA
GSM9102444 Multiome, WT Cerebral organoids, 51 day, Rep 2, RNA
GSM9102445 Multiome, KO Cerebral organoids, 51 day, Rep1, RNA
GSM9102446 Multiome, KO Cerebral organoids, 51 day, Rep 2, RNA
GSM9102447 Multiome, WT Cerebral organoids, 74 day, Rep 1, RNA
GSM9102448 Multiome, WT Cerebral organoids, 74 day, Rep 2, RNA
GSM9102449 Multiome, KO Cerebral organoids, 74 day, Rep1, RNA
GSM9102450 Multiome, KO Cerebral organoids, 74 day, Rep 2, RNA
GSM9102451 Multiome, WT Cerebral organoids, 51 day, Rep 1, ATAC
GSM9102452 Multiome, WT Cerebral organoids, 51 day, Rep 2, ATAC
GSM9102453 Multiome, KO Cerebral organoids, 51 day, Rep1, ATAC
GSM9102454 Multiome, KO Cerebral organoids, 51 day, Rep 2, ATAC
GSM9102455 Multiome, WT Cerebral organoids, 74 day, Rep 1, ATAC
GSM9102456 Multiome, WT Cerebral organoids, 74 day, Rep 2, ATAC
GSM9102457 Multiome, KO Cerebral organoids, 74 day, Rep1, ATAC
GSM9102458 Multiome, KO Cerebral organoids, 74 day, Rep 2, ATAC

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