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Single-cell Multiome Analysis of Chromatin State and Transcriptome in the Human Basal Ganglia
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Single-cell Multiome Analysis of Chromatin State and Transcriptome in the Human Basal Ganglia

Lei Chang, Kai Li, Yang Xie +57 more
February 2026
 ·
bioRxiv
 ·
DOI 
10.64898/2026.02.03.703645
94
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It ranks in the top 1% of preprints assessed in Genomics this quarter.
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Why this is interesting

The first single-cell atlas jointly profiling histone modifications and transcriptomes across the human basal ganglia decodes the combinatorial regulatory grammar of neuronal identity and makes noncoding neuropsychiatric risk variants interpretable at cell-type resolution.

Author perspective

What is the most important insight, discovery, or finding from your paper that you would like other scientists to know?
“

We created detailed molecular maps of individual brain cells that reveal how the genome is turned on and off to produce the remarkable diversity of cell types in the mouse and human brains. Our work shows that gene silencing is an active and informative process, not simply the absence of gene activity, and helps preserve the developmental history and identity of brain cells. These maps also identify the DNA switches and cell types linked to neurological and psychiatric diseases. Finally, we trained artificial intelligence models to predict how DNA sequences control brain function, providing a powerful framework for understanding disease-causing genetic variants and designing future therapies.

”
Bing Ren

QED claims analysis

Summary

Single-cell joint profiling of three histone modifications and transcriptomes across human basal ganglia regions reveals cell-type-specific chromatin states spanning 50% of the genome, identifies over 500,000 regulatory elements including active enhancers and repressive silencers, and demonstrates that combinatorial homeobox transcription factor programs specify neuronal identity while enabling interpretation of neuropsychiatric disease risk variants through cell-type-resolved regulatory networks.

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Main Claim 1 –

Single-cell multiome maps active and repressive chromatin in basal ganglia

Supporting evidence

  • Spatial epigenomic gradients map basal ganglia regional functional specialization
Main Claim 2 –

Histone marks annotate chromatin states and 532,547 cell-type cCREs

Supporting evidence

  • Combinatorial homeobox TF code specifies basal ganglia neuronal identity
  • Conserved MSN regulatory programs; species-specific divergence at distal elements
Main Claim 3 –

Basal ganglia epigenomes link neuropsychiatric risk variants to target genes

Supporting evidence

  • EpiBRAIN predicts cell-type variant regulatory effects from histone marks

Abstract

The basal ganglia play essential roles in motor control, emotion, learning and reward processing. Their dysfunction contributes to many neurological and psychiatric disorders. However, the gene regulatory programs defining basal ganglia cell-type identity and function remain poorly understood, limiting interpretation of disease-associated non-coding variants. Here, we present the first single-cell multiome atlas of histone modifications and transcriptomes across eight basal ganglia regions from neurotypical adult human donors. Joint profiling reveals cell-type-specific deployment of active and repressive cis-regulatory elements and gene regulatory networks, and suggests a combinatorial homeobox transcription factor code underlying cell identity. Integration with matched spatial transcriptomic MERFISH data uncovers regional heterogeneity of epigenomic landscapes. Comparative analysis between human and mouse medium spiny neurons uncovers conservation of core gene regulatory features. This atlas interprets non-coding risk variants of neuropsychiatric disorders and supports the development of a deep learning model to predict gene regulation and functional effects of disease-associated variants.

HIGHLIGHTS

Joint single-cell profiling of transcriptomes and three histone modifications across eight human basal ganglia regions characterizes active and repressive chromatin states at cell-type resolution.

Cell-type-specific gene regulatory programs decode combinatorial homeobox TF grammar governing the identity and diversification of basal ganglia neurons.

Intergrative analyses link noncoding neuropsychiatric risk variants to specific cell types, regulatory elements, and candidate target genes.

A sequence-to-function deep-learning model predicts gene regulation from DNA sequence and prioritizes functional disease-associated variants.

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