Nelson Johansen

The basal ganglia (BG) are a set of topographically organized, interconnected structures that are pivotal for regulating volitional movement and other aspects of cognitive, motivational, and affective behavior. Recently generated taxonomies of transcriptomically-defined cell types (T-types) have revealed both fine-grained distinctions in gene expression between neurons in these structures as well as continuous transcriptomic variation across similar T-types [Refs. 1-9], which are both related to location within a structure. However, it remains unclear to what extent these and other cellular properties co-vary with each other. Therefore, we performed Patch-seq experiments [Refs. 10-11] on over 900 neurons in mouse brain slices from BG to provide an integrated view of the co-variation between gene expression, location, physiology, and morphology measured from the same neurons. Medium spiny neurons (MSNs) from both the direct and indirect pathways across the dorsal and ventral striatum follow a gene expression gradient that varies in a dorsolateral to ventromedial direction; we find that this gradient also corresponds with systematic differences in action potential kinetics and dendritic arborization. Our analysis also characterizes additional multimodal dimensions of MSN variation, such as those between direct and indirect pathway neurons and between matrix and striosome neurons. Furthermore, through comparison with Patch-seq data from macaque, we demonstrate that the relationship between the transcriptomic/spatial gradient and electrophysiological and morphological properties is conserved across these two species. We also find that properties of striatal interneurons, such as action potential kinetics, vary across the striatum in a manner consistent with the MSN gradient. Outside the striatum, our multimodal Patch-seq dataset from the globus pallidus, subthalamic nucleus, and substantia nigra enabled us to characterize transcriptomically-defined types and link them to prior descriptions of cell types in these structures. Finally, we examined to what extent the MSN transcriptomic/spatial gradient persisted across different stages of the BG circuit by comparing Patch-seq neurons to reconstructed whole-neuron morphologies and the topography of their interareal projections, finding that the gradient is better preserved in GPe and GPi compared to SNr. Our study links transcriptomic variation across T-types in mouse BG to spatial localization and phenotypic differences at the level of individual cells, improving our understanding of cell type architecture in topographically organized circuits of the brain.

SUMMARY: Understanding how cell types are organized across the central nervous system (CNS) is key to uncovering neural function. Here, we integrate single-nucleus Multiome (RNA+ATAC) sequencing, spatial transcriptomics, and computational analyses to map conserved cell type signatures in the adult mouse brainstem and spinal cord. We identify a shared core of neuronal and non-neuronal cell types, alongside region-specific specializations reflecting distinct functions. Spatial data reveal conserved cellular niches across the brainstem–spinal cord boundary, indicating a continuous organizational logic. Cross-region comparisons uncover recurrent gene expression modules and signaling programs that may support shared circuit features. Chromatin accessibility profiling highlights cell-type-specific regulatory programs and implicates Hox transcription factors in positional identity. Notably, cell-type and positional identities are largely orthogonal, with varying regional influence across neuronal classes: motor neurons show strong positional coupling, whereas glutamatergic and GABAergic interneurons show minimal entrainment. This work provides a reference for the shared molecular architecture of these CNS regions.

The BRAIN Initiative Cell Atlas Network (BICAN) is generating large-scale multimodal datasets to profile cell types in the human, non-human primate, and mouse brain. The diversity of single-cell and spatial transcriptomic and epigenomic assays, combined with varied experimental contexts, multiple data-generating laboratories and distributed infrastructure, poses substantial challenges for data integration and reuse in BICAN. To address this, we implemented a standards framework that enables layered integration of these data into knowledge-ready products for interoperable brain cell atlases. This framework organizes data based on three progressively structured layers. First, we introduced an assay-agnostic modeling layer that unifies the representation of single-cell and spatial omics data using a common set of biological entities and processes assessed by diverse experimental techniques. Second, we implemented harmonized metadata standards that capture key experimental features linked to biospecimen provenance across heterogeneous tissue sources, species, and preparations, supporting integration and validation while minimizing burden on data contributors. Third, we present an extensible representation for data-driven cell type taxonomies that integrates molecular data with annotations, ontology mappings, and evidence. Together, these contributions represent an end-to-end framework that transforms heterogeneous datasets into structured, interoperable resources that support broad community reuse via mapping algorithms, annotation systems, and visualization platforms. This approach links biospecimen provenance with cell-level outputs and embeds these in a standardized taxonomy format, enabling downstream applications such as cross-dataset integration, reference mapping, and knowledge-driven analysis. More broadly, our work demonstrates a generalizable strategy for enabling an efficient data-to-knowledge pipeline in a large-scale consortium setting.

Single-cell mapping methods convert raw, heterogeneous single-cell datasets into interpretable and comparable representations of biological identity. As reference cell-type taxonomies mature, mapping new datasets to shared references has become a central strategy for enabling cross-study integration, reproducible annotation, and cumulative biological knowledge. Here we present MapMyCells , an open-source framework designed to align diverse single-cell omics datasets to hierarchical reference taxonomies with minimal preprocessing. MapMyCells provides out-of-the-box support for an expanding set of high-quality brain cell-type references generated by the Allen Institute for Brain Science, the BRAIN Initiative, and the Seattle Alzheimer’s Disease Brain Cell Atlas, including whole-brain mouse and human atlases, aging and Alzheimer’s disease cohorts, and a cross-species consensus taxonomy initially focused on the basal ganglia. MapMyCells enables efficient mapping of hundreds of thousands of cells on standard workstations without specialized hardware, providing a deterministic, scalable, and modality-agnostic approach that is robust across species and molecular assays. The framework produces interpretable confidence metrics and quantitative summaries of mapping performance, allowing users to evaluate assignment precision and accuracy. We demonstrate the mapping of unlabeled transcriptomic, epigenomic, and spatial datasets to reference taxonomies and describe a general workflow for preparing arbitrary hierarchical taxonomies for reference-based mapping. As the ecosystem of single-cell reference atlases expands, MapMyCells offers a practical and reproducible solution for community-scale cell-type annotation and cross-dataset integration, supporting the development of unified and extensible brain cell atlases.

The basal ganglia are evolutionary ancient subcortical nuclei that form interconnected loops with the neocortex and limbic system to regulate movement, learning, habit formation, emotion, and motivation. Their dysfunction contributes to major neurological and psychiatric disorders, yet most cellular-level insights derive from rodent studies, leaving knowledge gaps in humans and translationally relevant primate species. To address this, we generated multi-modal Patch-seq data linking transcriptomic identity with morphological and electrophysiological properties in macaque striatum, the input nucleus of the basal ganglia. We found underappreciated diversity among medium spiny neurons, including non-canonical types, and variation aligned with functional gradients. Interneurons also exhibited spatial variation and even greater morphoelectric diversity, highlighting their functional modularity. Despite broad evolutionary conservation, we identified primate-specific features and key differences from rodent striatal neurons. By integrating molecular classification with cellular properties that shape network function, our findings provide insights into the functional organization of the primate striatum.

SUMMARY: The mammalian basal ganglia (BG) orchestrate motor, cognitive, and affective functions, yet cell type-specific genetic access remains limited, especially beyond rodents. Key structures implicated in movement and psychiatric disorders, including pallidum, subthalamic nucleus, and dopaminergic midbrain, lack scalable tools for cross-species targeting. Here, we present a comprehensive enhancer-AAV library enabling selective labeling and manipulation of major BG neuronal populations: striatal projection neuron subtypes, pallidal and subthalamic neurons, and midbrain dopaminergic and GABAergic populations. Using an evolutionarily informed discovery pipeline, we identified enhancers targeting canonical, non-canonical, and disease-relevant cell types, with validation demonstrating robust cross-species conservation of specificity between mouse and macaque. Computational modeling revealed sequence features predictive of in vivo performance, including motif grammar, chromatin accessibility, and evolutionary conservation, and identified distinct regulatory architectures across glial, projection, and interneuron lineages. This work establishes a comprehensive cross-species viral toolkit for the BG, unlocking previously inaccessible cell types for circuit dissection.

SUMMARY: The spinal cord contains evolutionarily conserved cell types critical for motor function, sensory processing, and autonomic regulation, many of which are implicated in diverse neurological diseases and injuries. Yet the field lacks a comprehensive molecular characterization of cellular diversity in human, macaque, and mouse spinal cord. Here, we present a unified, cross-species cell type atlas based on the integration of single-nucleus gene expression, chromatin accessibility, and spatial transcriptomic data from segments within cervical, thoracic, lumbar, and sacral regions, including motor neurons (MNs) sampled across the entire rostro-caudal axis of the macaque spinal cord. Leveraging the spatial distributions of our molecularly defined cell types, we generated a cell type-guided anatomical map of spinal cord laminae and nuclei. We identified both conserved and species-specific cellular features, including gene expression patterns across distinct MN subtypes in the primate spinal cord. Cross-species cis-regulatory analysis and deep learning sequence models dissected the enhancer logic underlying viral targeting, uncovering conserved transcription factor grammar encoding cellular identity. Together, these results establish a unifying molecular and anatomical taxonomy of spinal cord cell types across species.

SUMMARY: Astrocytes shape synapses and circuits, yet human basal ganglia astrocyte diversity is incompletely defined. We built a multimodal atlas by integrating single-nucleus RNA-sequencing and chromatin accessibility with DNA methylation, 3D chromatin conformation, and spatial transcriptomics, then mapped basal ganglia programs onto a whole-brain reference. Astrocytes segregated into three anatomical subgroups spanning striatal gray matter, extra-striatal gray matter, and white matter, with subgroup-biased neurotransmitter transporters and synapse-associated programs consistent with differences in dominant afferent input. Within striatum, dorsal and ventral astrocyte populations aligned with distinct microcircuits and were conserved in nonhuman primates. A deep learning sequence model identified subgroup-associated enhancer code and, when benchmarked against published enhancer-AAV datasets, supported the design of candidate viral tools to target basal ganglia astrocyte programs in vivo . Together, these data define major axes of human astrocyte specialization and provide a framework for cell type-specific dissection of basal ganglia function.

The basal ganglia (BG) are conserved brain regions essential for motor control, learning, emotion, and cognition, and are implicated in neurological and psychiatric disease. Yet a unified cross-species taxonomy of BG cell types is lacking, limiting translation of BG circuit mechanisms, interpretation of human genetic risk, and development of cell type-targeted tools. We present a multiomic consensus atlas of 1.8 million nuclei from human, macaque, and marmoset spanning eight BG structures. Integrating cross-species gene expression, open chromatin, and spatial profiling enables definition of conserved and divergent cell types. Alignment to existing mouse and human atlases identifies 61 homologous cell types conserved over 80 million years. We identify a STRd D2 StrioMat Hybrid medium spiny neuron (MSN) type with molecular, electrophysiological, and morphological features that clarify hybrid MSN identities. Comparative cis-regulatory analysis reveals conserved sequence grammars that encode cell identity and inform viral targeting strategies, providing a foundational resource for BG evolution, function, and disease.

The basal ganglia are interconnected subcortical nuclei with complex topographical organization that orchestrate goal-directed behaviors and are implicated in neurodegenerative movement disorders. We generated a cellular-resolution, spatial transcriptomic atlas of the basal ganglia in human, rhesus macaque, and common marmoset, sampling over one million cells in each species. By integrating spatial data with a cross-species, consensus snRNA-seq cell type taxonomy, this atlas reveals conserved principles of molecular organization within and across structures. The cellular architecture is complex but highly stereotyped, with gene expression gradients superimposed onto discrete compartments. Extensive spatial sampling illuminates 3D gradients of molecular organization in the striatum and reveals cell type-specific core and shell compartments in the primate internal globus pallidus, which is conserved with mouse. This unified, cross-species spatial transcriptomic atlas will be a foundational resource for characterizing the molecular and functional organization of the basal ganglia and their roles in health and disease.