An Integrated Single-Cell and Epigenomic Resource for Comparative Analysis of the Basal Ganglia

The basal ganglia regulate motor, cognitive, and affective behaviors, and their dysfunction underlies diverse neurological and psychiatric disorders. Comprehensive, accessible multi-omics resources are needed to understand the regulatory mechanisms governing basal ganglia cell types. Here we present an open, interactive web-based platform for exploring single-cell multi-omics datasets from basal ganglia, generated using 10X Multiome, snm3C-seq, and Paired-Tag technologies from the BICAN (NIH BRAIN Initiative Cell Atlas Network) consortium. The platform is available at https://basalganglia.epigenomes.net/ and enables integrated visualization of gene expression, chromatin accessibility, DNA methylation, histone modifications, and chromatin conformation across cell types and human, macaque, marmoset, and mouse species, with direct genome browser support and comparative epigenomic functionality. Representative analyses demonstrate cell-type-specific regulatory landscapes, conserved and species-specific regulatory elements, and links between epigenomic regulation and transcription. This resource provides a scalable, community-oriented foundation for advancing basal ganglia biology and interpreting regulatory mechanisms relevant to brain function and disease.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-01-30
DOI
https://doi.org/10.64898/2026.01.29.702575
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
22.24
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An Integrated Single-Cell and Epigenomic Resource for Comparative Analysis of the Basal Ganglia

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1 citations
bioRxiv (Cold Spring Harbor Laboratory)
Single-cell and spatial transcriptomics
22.24
article

An Integrated Single-Cell and Epigenomic Resource for Comparative Analysis of the Basal Ganglia

Nelson Johansen, Shane Liu, Joseph R. Ecker, Daofeng Li, Cindy Tatiana Báez-Becerra, X Xu, Benpeng Miao, T -C Liu, Lei Chang, Bing Xiu Ren, Yuanyuan Fu, Quan Zhu, Chanrung Seng, Wenjin Zhang, Wubin Ding, Amit Klein, Tyler Mollenkopf, M. Margarita Behrens, Trygve E. Bakken, Ed S. Lein, Kai Li, Natalie Schenker, Ting Wang, Xie Yang, Jonathan A. Rink, Huaming Chen, Michael Hawrylycz, Rebecca D. Hodge
article en
1 citations

Abstract

The basal ganglia regulate motor, cognitive, and affective behaviors, and their dysfunction underlies diverse neurological and psychiatric disorders. Comprehensive, accessible multi-omics resources are needed to understand the regulatory mechanisms governing basal ganglia cell types. Here we present an open, interactive web-based platform for exploring single-cell multi-omics datasets from basal ganglia, generated using 10X Multiome, snm3C-seq, and Paired-Tag technologies from the BICAN (NIH BRAIN Initiative Cell Atlas Network) consortium. The platform is available at https://basalganglia.epigenomes.net/ and enables integrated visualization of gene expression, chromatin accessibility, DNA methylation, histone modifications, and chromatin conformation across cell types and human, macaque, marmoset, and mouse species, with direct genome browser support and comparative epigenomic functionality. Representative analyses demonstrate cell-type-specific regulatory landscapes, conserved and species-specific regulatory elements, and links between epigenomic regulation and transcription. This resource provides a scalable, community-oriented foundation for advancing basal ganglia biology and interpreting regulatory mechanisms relevant to brain function and disease.

bioRxiv (Cold Spring Harbor Laboratory)
James S. McDonnell Foundation (US), Salk Institute for Biological Studies (US), Allen Institute for Brain Science (US), Howard Hughes Medical Institute (US), University of California, Irvine (US), Washington University in St. Louis (US), Columbia University Irving Medical Center (US), University of California San Diego (US), Allen Institute (US), New York Genome Center (US)
Openalex Percentile: Top 2%
Single-cell and spatial transcriptomics
22.24
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