Comprehensive cell atlas of the first-trimester developing human brain

Single-cell and spatial omics: exploring hypothalamic heterogeneity

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

How radial glia progenitor lineages generate cell-type diversity in the developing cerebral cortex

The cerebral cortex is arguably the most complex organ in humans. The cortical architecture is characterized by a remarkable diversity of neuronal and glial cell types that make up its neuronal circuits. Following a precise temporally ordered program, radial glia progenitor (RGP) cells generate all cortical excitatory projection neurons and glial cell-types. Cortical excitatory projection neurons are produced either directly or via intermediate progenitors, through indirect neurogenesis. How the extensive cortical cell-type diversity is generated during cortex development remains, however, a fundamental open question. How do RGPs quantitatively and qualitatively generate all the neocortical neurons? How does direct and indirect neurogenesis contribute to the establishment of neuronal and lineage heterogeneity? Whether RGPs represent a homogeneous and/or multipotent progenitor population, or if RGPs consist of heterogeneous groups is currently also not known. In this review, we will summarize the latest findings that contributed to a deeper insight into the above key questions.

Spatial transcriptomics reveals human cortical layer and area specification

The human cerebral cortex is composed of six layers and dozens of areas that are molecularly and structurally distinct1-4. Although single-cell transcriptomic studies have advanced the molecular characterization of human cortical development, a substantial gap exists owing to the loss of spatial context during cell dissociation5-8. Here we used multiplexed error-robust fluorescence in situ hybridization (MERFISH)9, augmented with deep-learning-based nucleus segmentation, to examine the molecular, cellular and cytoarchitectural development of the human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing more than 18 million single cells, spans eight cortical areas across seven developmental time points. We uncovered the early establishment of the six-layer structure, identifiable by the laminar distribution of excitatory neuron subtypes, 3 months before the emergence of cytoarchitectural layers. Notably, we discovered two distinct modes of cortical areal specification during mid-gestation: (1) a continuous, gradual transition observed across most cortical areas along the anterior-posterior axis and (2) a discrete, abrupt boundary specifically identified between the primary (V1) and secondary (V2) visual cortices as early as gestational week 20. This sharp binary transition in V1-V2 neuronal subtypes challenges the notion that mid-gestation cortical arealization involves only gradient-like transitions6,10. Furthermore, integrating single-nucleus RNA sequencing with MERFISH revealed an early upregulation of synaptogenesis in V1-specific layer 4 neurons. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This study establishes a spatially resolved single-cell analysis paradigm and paves the way for the construction of a comprehensive developmental atlas of the human brain.

Neurodevelopmental hijacking of oligodendrocyte lineage programs drives glioblastoma infiltration

Glioblastoma (GBM) is an aggressive brain tumor with a highly invasive nature. Despite the clinical relevance of this behavior, the molecular underpinnings of infiltrating GBM cells in the peritumoral zone remain underexplored in patients. Here, we show that peritumoral progenitor-like GBM cells activate transcriptional programs associated with increased invasivity, synaptic activity, and NOTCH signaling. These cells spatially colocalize with neurons and exhibit an increased propensity for neuronal crosstalk. The epigenetic encoding of these infiltrative cells mirrors that of uncommitted oligodendrocyte progenitor cells (OPCs) in the developing human brain, a neurodevelopmental state marked by increased synaptic and migratory potential. Functional perturbation of a nominated regulatory factor, ZEB1, confirmed its role in maintaining the invasive and uncommitted developmental potential of infiltrative GBM cells. Our findings provide insights into the neurodevelopmental hijacking that drives GBM infiltration in patients, rationalizing further investigation into targeting differentiation potential as a therapeutic strategy.

Integrated analysis of molecular atlases unveils modules driving developmental cell subtype specification in the human cortex

Human brain development requires generating diverse cell types, a process explored by single-cell transcriptomics. Through parallel meta-analyses of the human cortex in development (seven datasets) and adulthood (16 datasets), we generated over 500 gene co-expression networks that can describe mechanisms of cortical development, centering on peak stages of neurogenesis. These meta-modules show dynamic cell subtype specificities throughout cortical development, with several developmental meta-modules displaying spatiotemporal expression patterns that allude to potential roles in cell fate specification. We validated the expression of these modules in primary human cortical tissues. These include meta-module 20, a module elevated in FEZF2+ deep layer neurons that includes TSHZ3, a transcription factor associated with neurodevelopmental disorders. Human cortical chimeroid experiments validated that both FEZF2 and TSHZ3 are required to drive module 20 activity and deep layer neuron specification but through distinct modalities. These studies demonstrate how meta-atlases can engender further mechanistic analyses of cortical fate specification.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Mapping the developmental profile of ventricular zone-derived neurons in the human cerebellum

The cerebellar ventricular zone (VZ) is the primary source of progenitors that generate cerebellar GABAergic neurons, including Purkinje cells (PCs) and interneurons (INs). This study provides detailed characterization of human cerebellar GABAergic neurogenesis using transcriptomic and histopathological analyses and reveals conserved and unique features compared to rodents. We show that the sequential progression of neurogenesis is conserved and occurs before 8 postconception weeks. Notably, PC differentiation occurs in the outer subventricular zone (SVZ), a region absent in the mouse cerebellum. Human PCs are generated during a compact two-week period before the onset of cerebral cortex histogenesis. A subset of human PCs retain proliferative marker expression weeks after leaving the VZ, another feature not observed in rodents. Human PC maturation is protracted with an extensive migration and reorganization throughout development with dendritic arborization developing in late gestation. We define a continuous transcriptional cascade of PC development from neuroepithelial cells to mature PCs. In contrast, while human interneuronal progenitors are born beginning in early fetal development, they exhibit an even more protracted differentiation across late gestation and into postnatal ages. These findings show dynamic developmental process for human cerebellar GABAergic neurons and underscore the importance of the embryonic environment, with early disruptions having potentially significant impacts.

Specification of human brain regions with orthogonal gradients of WNT and SHH in organoids reveals patterning variations across cell lines

The repertoire of neurons and their progenitors depends on their location along the antero-posterior and dorso-ventral axes of the neural tube. To model these axes, we designed the Dual Orthogonal-Morphogen Assisted Patterning System (Duo-MAPS) diffusion device to expose spheres of induced pluripotent stem cells (iPSCs) to concomitant orthogonal gradients of a posteriorizing and a ventralizing morphogen, activating WNT and SHH signaling, respectively. Comparison with single-cell transcriptomes from the fetal human brain revealed that Duo-MAPS-patterned organoids generated an extensive diversity of neuronal lineages from the forebrain, midbrain, and hindbrain. WNT and SHH crosstalk translated into early patterns of gene expression programs associated with the generation of specific brain lineages with distinct functional networks. Human iPSC lines showed substantial interindividual and line-to-line variations in their response to morphogens, highlighting that genetic and epigenetic variations may influence regional specification. Morphogen gradients promise to be a key approach to model the brain in its entirety.

Generation of human induced pluripotent stem cell-derived cortical neurons expressing the six tau isoforms

BackgroundThe alternative splicing (AS) of MAPT, which encodes Tau, in the adult human brain produces six major isoforms that play critical roles in the pathogenesis of tauopathies including Alzheimer's disease. Previous efforts have failed to differentiate human induced pluripotent stem cells (hiPSCs) to cortical neurons expressing the six isoforms of Tau.ObjectiveWe aim to develop a differentiation method capable of producing the six Tau isoforms in hiPSC-derived cortical neurons.MethodsWe searched for the optimal concentration, duration and treatment window of morphogens in the differentiation of hiPSCs through embryoid bodies (EBs) to dorsal forebrain neuroepithelial cells then to cortical neurons.ResultsThe combined inhibition of WNT, SHH, and SMAD signaling in EBs generated neuroepithelial cells expressing appropriate dorsal forebrain markers, while suppressing ventral, midbrain, and hindbrain genes. Further differentiation in neurogenic and neurotrophic factors produced MAP2+ neurons at day 18. The iPSC-derived neurons expressed markers of all cortical layers and exhibited synapse formation and synaptic physiology. In addition, MAP2+ neurons and mitotic cells expressing radial glial markers formed aggregates that could be dissociated to produce mature neurons with similar properties. Most importantly, the six Tau isoforms were expressed from day 80 in a developmentally regulated manner, modeling the situation in human brains on an accelerated timeline.ConclusionsThis chemically defined differentiation method produces a key hallmark of mature human cortical neurons by expressing the six main splicing isoforms of Tau. It will greatly facilitate disease modeling and therapeutic discovery for many human brain disorders involving cortical neurons.

Primer on machine learning applications in brain immunology

Single-cell and spatial technologies have transformed our understanding of brain immunology, providing unprecedented insights into immune cell heterogeneity and spatial organisation within the central nervous system. These methods have uncovered complex cellular interactions, rare cell populations, and the dynamic immune landscape in neurological disorders. This review highlights recent advances in single-cell "omics" data analysis and discusses their applicability for brain immunology. Traditional statistical techniques, adapted for single-cell omics, have been crucial in categorizing cell types and identifying gene signatures, overcoming challenges posed by increasingly complex datasets. We explore how machine learning, particularly deep learning methods like autoencoders and graph neural networks, is addressing these challenges by enhancing dimensionality reduction, data integration, and feature extraction. Newly developed foundation models present exciting opportunities for uncovering gene expression programs and predicting genetic perturbations. Focusing on brain development, we demonstrate how single-cell analyses have resolved immune cell heterogeneity, identified temporal maturation trajectories, and uncovered potential therapeutic links to various pathologies, including brain malignancies and neurodegeneration. The integration of single-cell and spatial omics has elucidated the intricate cellular interplay within the developing brain. This mini-review is intended for wet lab biologists at all career stages, offering a concise overview of the evolving landscape of single-cell omics in the age of widely available artificial intelligence.

Exploring human brain development and disease using assembloids

How the human brain develops and what goes awry in neurological disorders represent two long-lasting questions in neuroscience. Owing to the limited access to primary human brain tissue, insights into these questions have been largely gained through animal models. However, there are fundamental differences between developing mouse and human brain, and neural organoids derived from human pluripotent stem cells (hPSCs) have recently emerged as a robust experimental system that mimics self-organizing and multicellular features of early human brain development. Controlled integration of multiple organoids into assembloids has begun to unravel principles of cell-cell interactions. Moreover, patient-derived or genetically engineered hPSCs provide opportunities to investigate phenotypic correlates of neurodevelopmental disorders and to develop therapeutic hypotheses. Here, we outline the advances in technologies that facilitate studies by using assembloids and summarize their applications in brain development and disease modeling. Lastly, we discuss the major roadblocks of the current system and potential solutions.

Human assembloid model of the ascending neural sensory pathway

Somatosensory pathways convey crucial information about pain, touch, itch and body part movement from peripheral organs to the central nervous system1,2. Despite substantial needs to understand how these pathways assemble and to develop pain therapeutics, clinical translation remains challenging. This is probably related to species-specific features and the lack of in vitro models of the polysynaptic pathway. Here we established a human ascending somatosensory assembloid (hASA), a four-part assembloid generated from human pluripotent stem cells that integrates somatosensory, spinal, thalamic and cortical organoids to model the spinothalamic pathway. Transcriptomic profiling confirmed the presence of key cell types of this circuit. Rabies tracing and calcium imaging showed that sensory neurons connect to dorsal spinal cord neurons, which further connect to thalamic neurons. Following noxious chemical stimulation, calcium imaging of hASA demonstrated a coordinated response. In addition, extracellular recordings and imaging revealed synchronized activity across the assembloid. Notably, loss of the sodium channel NaV1.7, which causes pain insensitivity, disrupted synchrony across hASA. By contrast, a gain-of-function SCN9A variant associated with extreme pain disorder induced hypersynchrony. These experiments demonstrated the ability to functionally assemble the essential components of the human sensory pathway, which could accelerate our understanding of sensory circuits and facilitate therapeutic development.

Single-Cell Analysis in Cerebrovascular Research: Primed for Breakthroughs and Clinical Impact

Data generated using single-cell RNA-sequencing has the potential to transform understanding of the cerebral circulation and advance clinical care. However, the high volume of data, sometimes generated and presented without proper pathophysiological context, can be difficult to interpret and integrate into current understanding of the cerebral circulation and its disorders. Furthermore, heterogeneity in the representation of brain regions and vascular segments makes it difficult to compare results across studies. There are currently no standards for tissue collection and processing that allow easy comparisons across studies and analytical platforms. There are no standards either for single-cell data analysis and presentation. This topical review introduces single-cell RNA-sequencing to physicians and scientists in the cerebrovascular field, with the goals of highlighting opportunities and challenges of applying this technology in the cerebrovascular field and discussing key concepts and knowledge gaps that can be addressed by single-cell RNA-sequencing.

Adult Hippocampal Neurogenesis in the Human Brain: Updates, Challenges, and Perspectives

The existence of neurogenesis in the adult human hippocampus has been under considerable debate within the past three decades due to the diverging conclusions originating mostly from immunohistochemistry studies. While some of these reports conclude that hippocampal neurogenesis in humans occurs throughout physiologic aging, others indicate that this phenomenon ends by early childhood. More recently, some groups have adopted next-generation sequencing technologies to characterize with more acuity the extent of this phenomenon in humans. Here, we review the current state of research on adult hippocampal neurogenesis in the human brain with an emphasis on the challenges and limitations of using immunohistochemistry and next-generation sequencing technologies for its study.

Single-cell spatial transcriptomic atlas of the whole mouse brain

A comprehensive atlas of genes, cell types, and their spatial distribution across a whole mammalian brain is fundamental for understanding the function of the brain. Here, using single-nucleus RNA sequencing (snRNA-seq) and Stereo-seq techniques, we generated a mouse brain atlas with spatial information for 308 cell clusters at single-cell resolution, involving over 4 million cells, as well as for 29,655 genes. We have identified cell clusters exhibiting preference for cortical subregions and explored their associations with brain-related diseases. Additionally, we pinpointed 155 genes with distinct regional expression patterns within the brainstem and unveiled 513 long non-coding RNAs showing region-enriched expression in the adult brain. Parcellation of brain regions based on spatial transcriptomic information revealed fine structure for several brain areas. Furthermore, we have uncovered 411 transcription factor regulons showing distinct spatiotemporal dynamics during neurodevelopment. Thus, we have constructed a single-cell-resolution spatial transcriptomic atlas of the mouse brain with genome-wide coverage.

mTORC1 activation drives astrocyte reactivity in cortical tubers and brain organoid models of TSC

Tuberous Sclerosis Complex (TSC) is a genetic neurodevelopmental disorder associated with early onset epilepsy, intellectual disability and neuropsychiatric disorders. A hallmark of the disorder is cortical tubers, which are focal malformations of brain development containing dysplastic cells with hyperactive mTORC1 signaling. One barrier to developing therapeutic approaches and understanding the origins of tuber cells is the lack of a model system that recapitulates this pathology. To address this, we established a genetically mosaic cortical organoid system that models a somatic "second-hit" mutation, which is thought to drive the formation of tubers in TSC. With this model, we find that loss of TSC2 cell-autonomously promotes the differentiation of astrocytes, which exhibit features of a disease-associated reactive state. TSC2 -/- astrocytes have pronounced changes in morphology and upregulation of proteins that are risk factors for neurodegenerative diseases, such as clusterin and APOE. Using multiplexed immunofluorescence in primary tubers from TSC patients, we show that tuber cells with hyperactive mTORC1 activity also express reactive astrocyte proteins, and we identify a unique population of cells with expression profiles that match those observed in organoids. Together, this work reveals that reactive astrogliosis is a primary feature of TSC that arises early in cortical development. Dysfunctional glia are therefore poised to be drivers of pathophysiology, nominating a potential therapeutic target for treating TSC and related mTORopathies.

Metabolic Atlas of Early Human Cortex Identifies Regulators of Cell Fate Transitions

Characterization of cell type emergence during human cortical development, which enables unique human cognition, has focused primarily on anatomical and transcriptional characterizations. Metabolic processes in the human brain that allow for rapid expansion, but contribute to vulnerability to neurodevelopmental disorders, remain largely unexplored. We performed a variety of metabolic assays in primary tissue and stem cell derived cortical organoids and observed dynamic changes in core metabolic functions, including an unexpected increase in glycolysis during late neurogenesis. By depleting glucose levels in cortical organoids, we increased outer radial glia, astrocytes, and inhibitory neurons. We found the pentose phosphate pathway (PPP) was impacted in these experiments and leveraged pharmacological and genetic manipulations to recapitulate these radial glia cell fate changes. These data identify a new role for the PPP in modulating radial glia cell fate specification and generate a resource for future exploration of additional metabolic pathways in human cortical development.

Patterning effects of FGF17 and cAMP on generation of dopaminergic progenitors for cell replacement therapy in Parkinson's disease

Cell replacement therapies using human pluripotent stem cell-derived ventral midbrain (VM) dopaminergic (DA) progenitors are currently in clinical trials for treatment of Parkinson's disease (PD). Recapitulating developmental patterning cues, such as fibroblast growth factor 8 (FGF8), secreted at the midbrain-hindbrain boundary (MHB), is critical for the in vitro production of authentic VM DA progenitors. Here, we explored the application of alternative MHB-secreted FGF-family members, FGF17 and FGF18, for VM DA progenitor patterning. We show that while FGF17 and FGF18 both recapitulated VM DA progenitor patterning events, FGF17 induced expression of key VM DA progenitor markers at higher levels than FGF8 and transplanted FGF17-patterned progenitors fully reversed motor deficits in a rat PD model. Early activation of the cAMP pathway mimicked FGF17-induced patterning, although strong cAMP activation came at the expense of EN1 expression. In summary, we identified FGF17 as a promising alternative FGF candidate for robust VM DA progenitor patterning.

Multiomic single-cell profiling identifies critical regulators of postnatal brain

Human brain development spans from embryogenesis to adulthood, with dynamic gene expression controlled by cell-type-specific cis-regulatory element activity and three-dimensional genome organization. To advance our understanding of postnatal brain development, we simultaneously profiled gene expression and chromatin accessibility in 101,924 single nuclei from four brain regions across ten donors, covering five key postnatal stages from infancy to late adulthood. Using this dataset and chromosome conformation capture data, we constructed enhancer-based gene regulatory networks to identify cell-type-specific regulators of brain development and interpret genome-wide association study loci for ten main brain disorders. Our analysis connected 2,318 cell-specific loci to 1,149 unique genes, representing 41% of loci linked to the investigated traits, and highlighted 55 genes influencing several disease phenotypes. Pseudotime analysis revealed distinct stages of postnatal oligodendrogenesis and their regulatory programs. These findings provide a comprehensive dataset of cell-type-specific gene regulation at critical timepoints in postnatal brain development.

The Principle of Cortical Development and Evolution

Human's robust cognitive abilities, including creativity and language, are made possible, at least in large part, by evolutionary changes made to the cerebral cortex. This paper reviews the biology and evolution of mammalian cortical radial glial cells (primary neural stem cells) and introduces the concept that a genetically step wise process, based on a core molecular pathway already in use, is the evolutionary process that has molded cortical neurogenesis. The core mechanism, which has been identified in our recent studies, is the extracellular signal-regulated kinase (ERK)-bone morphogenic protein 7 (BMP7)-GLI3 repressor form (GLI3R)-sonic hedgehog (SHH) positive feedback loop. Additionally, I propose that the molecular basis for cortical evolutionary dwarfism, exemplified by the lissencephalic mouse which originated from a larger gyrencephalic ancestor, is an increase in SHH signaling in radial glia, that antagonizes ERK-BMP7 signaling. Finally, I propose that: (1) SHH signaling is not a key regulator of primate cortical expansion and folding; (2) human cortical radial glial cells do not generate neocortical interneurons; (3) human-specific genes may not be essential for most cortical expansion. I hope this review assists colleagues in the field, guiding research to address gaps in our understanding of cortical development and evolution.

3D Mechanical Response Stem Cell Complex Repairs Spinal Cord Injury by Promoting Neurogenesis and Regulating Tissue Homeostasis

Spinal cord injury (SCI) leads to acute tissue damage that disrupts the microenvironmental homeostasis of the spinal cord, inhibiting cell survival and function, and thereby undermining treatment efficacy. Traditional stem cell therapies have limited success in SCI, due to the difficulties in maintaining cell survival and inducing sustained differentiation into neural lineages. A new solution may arise from controlling the fate of stem cells by creating an appropriate mechanical microenvironment. In this study, mechanical response stem cell complex (MRSCC) is created as an innovative therapeutic strategy for SCI, utilizing 3D bioprinting technology and gelatin microcarriers (GM) loaded with mesenchymal stem cells (MSCs). GM creates an optimal microenvironment for MSCs growth and paracrine activity. Meanwhile, 3D bioprinting allows accurate control of spatial pore architecture and mechanical characteristics of the cell construct to encourage neuroregeneration. The mechanical microenvironment created by MRSCC is found to activate the Piezo1 channel and prevent excessive nuclear translocation of YAP, thereby increasing neural-related gene expression in MSCs. Transplanting MRSCC in rats with spinal cord injuries boosts sensory and motor recovery, reduces inflammation, and stimulates the regeneration of neurons and glial cells. The MRSCC offers a new tissue engineering solution that can promote spinal cord repair.

Cell Type-Agnostic Transcriptomic Signatures Enable Uniform Comparisons of Neurodevelopment

Single-cell transcriptomics has revolutionized our understanding of neurodevelopmental cell identities, yet, predicting a cell type's developmental state from its transcriptome remains a challenge. We perform a meta-analysis of developing human brain datasets comprising over 2.8 million cells, identifying both tissue-level and cell-autonomous predictors of developmental age. While tissue composition predicts age within individual studies, it fails to generalize, whereas specific cell type proportions reliably track developmental time across datasets. Training regularized regression models to infer cell-autonomous maturation, we find that a cell type-agnostic model achieves the highest accuracy (error = 2.6 weeks), robustly capturing developmental dynamics across diverse cell types and datasets. This model generalizes to human neural organoids, accurately predicting normal developmental trajectories (R = 0.91) and disease-induced shifts in vitro. Furthermore, it extends to the developing mouse brain, revealing an accelerated developmental tempo relative to humans. Our work provides a unified framework for comparing neurodevelopment across contexts, model systems, and species.

Chronic exposure to glucocorticoids amplifies inhibitory neuron cell fate during human neurodevelopment in organoids

Disruptions in the tightly regulated process of human brain development have been linked to increased risk for brain and mental illnesses. While the genetic contribution to these diseases is well established, important environmental factors have been less studied at molecular and cellular levels. Here, we used single-cell and cell type-specific techniques to investigate the effect of glucocorticoid (GC) exposure, a mediator of antenatal environmental risk, on gene regulation and lineage specification in unguided human neural organoids. We characterized the transcriptional response to chronic GC exposure during neural differentiation and studied the underlying gene regulatory networks by integrating single-cell transcriptomics with chromatin accessibility data. We found lasting cell type-specific changes that included autism risk genes and several transcription factors associated with neurodevelopment. Chronic GC exposure influenced lineage specification primarily by priming the inhibitory neuron lineage through transcription factors like PBX3. We provide evidence for convergence of genetic and environmental risk factors through a common mechanism of altering lineage specification.

Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics

Mapping cellular organization in the developing brain presents significant challenges due to the multidimensional nature of the data, characterized by complex spatial patterns that are difficult to interpret without high-throughput tools. Here, we present DeepCellMap, a deep-learning-assisted tool that integrates multi-scale image processing with advanced spatial and clustering statistics. This pipeline is designed to map microglial organization during normal and pathological brain development and has the potential to be adapted to any cell type. Using DeepCellMap, we capture the morphological diversity of microglia, identify strong coupling between proliferative and phagocytic phenotypes, and show that distinct spatial clusters rarely overlap as human brain development progresses. Additionally, we uncover an association between microglia and blood vessels in fetal brains exposed to maternal SARS-CoV-2. These findings offer insights into whether various microglial phenotypes form networks in the developing brain to occupy space, and in conditions involving haemorrhages, whether microglia respond to, or influence changes in blood vessel integrity. DeepCellMap is available as an open-source software and is a powerful tool for extracting spatial statistics and analyzing cellular organization in large tissue sections, accommodating various imaging modalities. This platform opens new avenues for studying brain development and related pathologies.

The spatiotemporal transcriptional profiling of murine brain during cerebral malaria progression and after artemisinin treatment

Cerebral malaria (CM) is a severe encephalopathy caused by Plasmodium parasite infection, resulting in thousands of annual deaths and neuro-cognitive sequelae even after anti-malarial drugs treatment. Despite efforts to dissect the mechanism, the cellular transcriptomic reprogramming within the spatial context remains elusive. Here, we constructed single-cell and spatial transcriptome atlases of experimental CM (ECM) male murine brain tissues with or without artesunate (ART) treatment. We identified activated inflammatory endothelial cells during ECM, characterized by a disrupted blood-brain barrier, increased antigen presentation, and leukocyte adhesion. We also observed that inflammatory microglia enhance antigen presentation pathway such as MHC-I to CD8+ cytotoxic T cells. The latter underwent an inflammatory state transition with up-regulated cytokine expression and cytotoxic activity. Multi-omics analysis revealed that the activated interferon-gamma response of injured neurons during ECM and persisted after ART treatment. Overall, our research provides valuable resources for understanding malaria parasite-host interaction mechanisms and adjuvant therapy development.

An integrated perspective on single-cell and spatial transcriptomic signatures in high-grade gliomas

High-grade gliomas (HGG) are incurable brain malignancies in children and adults. Breakthrough advances in transcriptomic technologies unveiled the intricate diversity of cellular states and their spatial organization within HGGs. We qualitatively integrated 55 neoplastic transcriptomic signatures described in 17 single-cell and spatial RNA sequencing-based studies. Our review delineates a spectrum of cellular states, represented by the expression of specific genes, which can be conceptualized along a "reactive-developmental programs" axis. Additionally, we discussed the potential cues influencing these cellular states, including how spatial organization may impact transcriptomic dynamics. Leveraging these insightful discoveries, we discussed a novel, evolutive way to integrate the different transcriptomic signatures in two or three dimensions, incorporating developmental states, their proliferative capacity, and their possible transition towards reactive states. This integrated analysis illuminates the diverse cellular landscape of HGGs and provides a valuable resource for further elucidation of malignant mechanisms, and for the design of therapeutic endeavors.

Phospho-seq: integrated, multi-modal profiling of intracellular protein dynamics in single cells

Cell signaling plays a critical role in neurodevelopment, regulating cellular behavior and fate. While multimodal single-cell sequencing technologies are rapidly advancing, scalable and flexible profiling of cell signaling states alongside other molecular modalities remains challenging. Here we present Phospho-seq, an integrated approach that aims to quantify cytoplasmic and nuclear proteins, including those with post-translational modifications, and to connect their activity with cis-regulatory elements and transcriptional targets. We utilize a simplified benchtop antibody conjugation method to create large custom neuro-focused antibody panels for simultaneous protein and scATAC-seq profiling on whole cells, alongside both experimental and computational strategies to incorporate transcriptomic measurements. We apply our workflow to cell lines, induced pluripotent stem cells, and months-old retinal and brain organoids to demonstrate its broad applicability. We show that Phospho-seq can provide insights into cellular states and trajectories, shed light on gene regulatory relationships, and help explore the causes and effects of diverse cell signaling in neurodevelopment.

Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single-cell resolution

Dissecting human neurobiology at high resolution and with mechanistic precision requires a major leap in scalability, given the need for experimental designs that include multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we have developed and benchmarked complementary strategies to multiplex brain organoids by pooling cells from different pluripotent stem cell (PSC) lines either during organoid generation (mosaic models) or before single-cell RNA sequencing (scRNA-seq) library preparation (downstream multiplexing). We have also developed a new computational method, SCanSNP, and a consensus call to deconvolve cell identities, overcoming current criticalities in doublets and low-quality cell identification. We validated both multiplexing methods for charting neurodevelopmental trajectories at high resolution, thus linking specific individuals' trajectories to genetic variation. Finally, we modeled their scalability across different multiplexing combinations and showed that mosaic organoids represent an enabling method for high-throughput settings. Together, this multiplexing suite of experimental and computational methods provides a highly scalable resource for brain disease and neurodiversity modeling.

Fast, flexible analysis of differences in cellular composition with crumblr

Changes in cell type composition play an important role in human health and disease. Recent advances in single-cell technology have enabled the measurement of cell type composition at increasing cell lineage resolution across large cohorts of individuals. Yet this raises new challenges for statistical analysis of these compositional data to identify changes in cell type frequency. We introduce crumblr (DiseaseNeurogenomics.github.io/crumblr), a scalable statistical method for analyzing count ratio data using precision-weighted linear mixed models incorporating random effects for complex study designs. Uniquely, crumblr performs statistical testing at multiple levels of the cell lineage hierarchy using a multivariate approach to increase power over tests of one cell type. In simulations, crumblr increases power compared to existing methods while controlling the false positive rate. We demonstrate the application of crumblr to published single-cell RNA-seq datasets for aging, tuberculosis infection in T cells, bone metastases from prostate cancer, and SARS-CoV-2 infection.

Examining the NEUROG2 lineage and associated gene expression in human cortical organoids

Proneural genes are conserved drivers of neurogenesis across the animal kingdom. How their functions have adapted to guide human-specific neurodevelopmental features is poorly understood. Here, we mined transcriptomic data from human fetal cortices and generated from human embryonic stem cell-derived cortical organoids (COs) to show that NEUROG1 and NEUROG2 are most highly expressed in basal neural progenitor cells, with pseudotime trajectory analyses indicating that NEUROG1-derived lineages predominate early and NEUROG2 lineages later. Using ChIP-qPCR, gene silencing and overexpression studies in COs, we show that NEUROG2 is necessary and sufficient to directly transactivate known target genes (NEUROD1, EOMES, RND2). To identify new targets, we engineered NEUROG2-mCherry knock-in human embryonic stem cells for CO generation. The mCherry-high CO cell transcriptome is enriched in extracellular matrix-associated genes, and two genes associated with human-accelerated regions: PPP1R17 and FZD8. We show that NEUROG2 binds COL1A1, COL3A1 and PPP1R17 regulatory elements, and induces their ectopic expression in COs, although NEUROG2 is not required for this expression. Neurog2 similarly induces Col3a1 and Ppp1r17 in murine P19 cells. These data are consistent with a conservation of NEUROG2 function across mammalian species.

Cortical arealization of interneurons defines shared and distinct molecular programs in developing human and macaque brains

Cortical interneurons generated from ganglionic eminence via a long-distance journey of tangential migration display evident cellular and molecular differences across brain regions, which seeds the heterogeneous cortical circuitry in primates. However, whether such regional specifications in interneurons are intrinsically encoded or gained through interactions with the local milieu remains elusive. Here, we recruit 685,692 interneurons from cerebral cortex and subcortex including ganglionic eminence within the developing human and macaque species. Our integrative and comparative analyses reveal that less transcriptomic alteration is accompanied by interneuron migration within the ganglionic eminence subdivisions, in contrast to the dramatic changes observed in cortical tangential migration, which mostly characterize the transcriptomic specification for different destinations and for species divergence. Moreover, the in-depth survey of temporal regulation illustrates species differences in the developmental dynamics of cell types, e.g., the employment of CRH in primate interneurons during late-fetal stage distinguishes from their postnatal emergence in mice, and our entropy quantifications manifest the interneuron diversities gradually increase along the developmental ages in human and macaque cerebral cortices. Overall, our analyses depict the spatiotemporal features appended to cortical interneurons, providing a new proxy for understanding the relationship between cellular diversity and functional progression.

Resolving forebrain developmental organisation by analysis of differential growth patterns

The forebrain is the most complex region of the vertebrate CNS, and its developmental organisation is controversial. We fate-mapped the embryonic chick forebrain using lipophilic dyes and Cre-recombination lineage tracing, and built a 4D model of brain growth. We reveal modular patterns of anisotropic growth, ascribed to progenitor regions through multiplex HCR. Morphogenesis is dominated by directional growth towards the eye, more isometric expansion of the prethalamus and dorsal telencephalon, and anterior movement of ventral cells into the hypothalamus. Fate conversion experiments in chick and comparative gene expression analysis in chick and mouse support placement of the hypothalamus ventral to structures extending from the telencephalon up to and including the zona limitans intrathalamica (ZLI), with the dorsoventral axis becoming distorted at the base of the ZLI. Our findings challenge the widely accepted prosomere model of forebrain organisation, and we propose an alternative 'tripartite hypothalamus' model.

MAPbrain: a multi-omics atlas of the primate brain

The brain is the central hub of the entire nervous system. Its development is a lifelong process guided by a genetic blueprint. Understanding how genes influence brain development is critical for deciphering the formation of human cognitive functions and the underlying mechanisms of neurological disorders. Recent advances in multi-omics techniques have now made it possible to explore these aspects comprehensively. However, integrating and analyzing extensive multi-omics data presents significant challenges. Here, we introduced MAPbrain (http://bigdata.ibp.ac.cn/mapBRAIN/), a multi-omics atlas of the primate brain. This repository integrates and normalizes both our own lab's published data and publicly available multi-omics data, encompassing 21 million brain cells from 38 key brain regions and 436 sub-regions across embryonic and adult stages, with 164 time points in humans and non-human primates. MAPbrain offers a unique, robust, and interactive platform that includes transcriptomics, epigenomics, and spatial transcriptomics data, facilitating a comprehensive exploration of brain development. The platform enables the exploration of cell type- and time point-specific markers, gene expression comparison between brain regions and species, joint analyses across transcriptome and epigenome, and navigation of cell types across species, brain regions, and development stages. Additionally, MAPbrain provides an online integration module for users to navigate and analyze their own data within the platform.

Enhanced yield and subtype identity of hPSC-derived midbrain dopamine neuron by modulation of WNT and FGF18 signaling

While clinical trials are ongoing using human pluripotent stem cell-derived midbrain dopamine (mDA) neuron precursor grafts in Parkinson's disease (PD), current protocols to derive mDA neurons remain suboptimal. In particular, the yield of TH+ mDA neurons after in vivo grafting and the expression of some mDA neuron and subtype-specific markers can be further improved. For example, characterization of mDA grafts by single cell transcriptomics has yielded only a small proportion of mDA neurons and a considerable fraction of contaminating cell populations. Here we present an optimized mDA neuron differentiation strategy that builds on our clinical grade ("Boost") protocol but includes the addition of FGF18 and IWP2 treatment ("Boost+") at the mDA neurogenesis stage. We demonstrate that Boost+ mDA neurons show higher expression of EN1, PITX3 and ALDH1A1. Improvements in both mDA neurons yield and transcriptional similarity to primary mDA neurons is observed both in vitro and in grafts. Furthermore, grafts are enriched in authentic A9 mDA neurons by single nucSeq. Functional studies in vitro demonstrate increased dopamine production and release and improved electrophysiological properties. In vivo analyses show increased percentages of TH+ mDA neurons resulting in efficient rescue of amphetamine induced rotation behavior in the 6-OHDA rat model and rescue of some motor deficits in non-drug induced assays, including the ladder rung assay that is not improved by Boost mDA neurons. The Boost+ conditions present an optimized protocol with advantages for disease modeling and mDA neuron grafting paradigms.

Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications

Spatial transcriptomics (ST) represents a revolutionary approach in molecular biology, providing unprecedented insights into the spatial organization of gene expression within tissues. This review aims to elucidate advancements in ST technologies, their computational tools, and their pivotal applications in neuroscience. It is begun with a historical overview, tracing the evolution from early image-based techniques to contemporary sequence-based methods. Subsequently, the computational methods essential for ST data analysis, including preprocessing, cell type annotation, spatial clustering, detection of spatially variable genes, cell-cell interaction analysis, and 3D multi-slices integration are discussed. The central focus of this review is the application of ST in neuroscience, where it has significantly contributed to understanding the brain's complexity. Through ST, researchers advance brain atlas projects, gain insights into brain development, and explore neuroimmune dysfunctions, particularly in brain tumors. Additionally, ST enhances understanding of neuronal vulnerability in neurodegenerative diseases like Alzheimer's and neuropsychiatric disorders such as schizophrenia. In conclusion, while ST has already profoundly impacted neuroscience, challenges remain issues such as enhancing sequencing technologies and developing robust computational tools. This review underscores the transformative potential of ST in neuroscience, paving the way for new therapeutic insights and advancements in brain research.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

MerQuaCo: a computational tool for quality control in image-based spatial transcriptomics

Image-based spatial transcriptomics platforms are powerful tools often used to identify cell populations and describe gene expression in intact tissue. Spatial experiments return large, high-dimension datasets and several open-source software packages are available to facilitate analysis and visualization. Spatial results are typically imperfect. For example, local variations in transcript detection probability are common. Software tools to characterize imperfections and their impact on downstream analyses are lacking so the data quality is assessed manually, a laborious and often a subjective process. Here we describe imperfections in a dataset of 641 fresh-frozen adult mouse brain sections collected using the Vizgen MERSCOPE. Common imperfections included the local loss of tissue from the section, tissue outside the imaging volume due to detachment from the coverslip, transcripts missing due to dropped images, varying detection probability through space, and differences in transcript detection probability between experiments. We describe the incidence of each imperfection and the likely impact on the accuracy of cell type labels. We develop MerQuaCo, open-source code that detects and quantifies imperfections without user input, facilitating the selection of sections for further analysis with existing packages. Together, our results and MerQuaCo facilitate rigorous, objective assessment of the quality of spatial transcriptomics results.

Generating human neural diversity with a multiplexed morphogen screen in organoids

Morphogens choreograph the generation of remarkable cellular diversity in the developing nervous system. Differentiation of stem cells in vitro often relies upon the combinatorial modulation of these signaling pathways. However, the lack of a systematic approach to understand morphogen-directed differentiation has precluded the generation of many neural cell populations, and the general principles of regional specification and maturation remain incomplete. Here, we developed an arrayed screen of 14 morphogen modulators in human neural organoids cultured for over 70 days. Deconvolution of single-cell-multiplexed RNA sequencing data revealed design principles of brain region specification. We tuned neural subtype diversity to generate a tachykinin 3 (TAC3)-expressing striatal interneuron type within assembloids. To circumvent limitations of in vitro neuronal maturation, we used a neonatal rat transplantation strategy that enabled human Purkinje neurons to develop their hallmark complex dendritic branching. This comprehensive platform yields insights into the factors influencing stem cell-derived neural diversification and maturation.

EZHIP's role in diffuse midline glioma: echoes of oncohistones?

The enhancer of zeste inhibitory protein (EZHIP) is typically expressed during germ cell development and has been classified as a cancer-testis antigen (CTA) in various cancers. In 2020, 4% of diffuse midline gliomas (DMGs) were shown to aberrantly express EZHIP, mirroring the DMG hallmark histone H3 K27M (H3K27M) oncohistone mutation. Similar to H3K27M, EZHIP is a negative regulator of polycomb repressive complex 2 (PRC2), leading to global epigenomic remodeling. In this opinion, we explore the similarities and disparities between H3K27M- and EZHIP-DMGs with a focus on their shared functional hallmark of PRC2 inhibition, their genetic and epigenomic landscapes, plausible differences in the cell of origin, and therapeutic avenues. Upcoming research on EZHIP will help better understand its role in gliomagenesis and DMG therapy.

Meta-analysis of single-cell RNA sequencing co-expression in human neural organoids reveals their high variability in recapitulating primary tissue

Human neural organoids offer an exciting opportunity for studying inaccessible human-specific brain development; however, it remains unclear how precisely organoids recapitulate fetal/primary tissue biology. We characterize field-wide replicability and biological fidelity through a meta-analysis of single-cell RNA-sequencing data for first and second trimester human primary brain (2.95 million cells, 51 data sets) and neural organoids (1.59 million cells, 173 data sets). We quantify the degree primary tissue cell type marker expression and co-expression are recapitulated in organoids across 10 different protocol types. By quantifying gene-level preservation of primary tissue co-expression, we show neural organoids lie on a spectrum ranging from virtually no signal to co-expression indistinguishable from primary tissue, demonstrating a high degree of variability in biological fidelity among organoid systems. Our preserved co-expression framework provides cell type-specific measures of fidelity applicable to diverse neural organoids, offering a powerful tool for uncovering unifying axes of variation across heterogeneous neural organoid experiments.

Reconstructing human-specific regulatory functions in model systems

Uniquely human physical traits, such as an expanded cerebral cortex and changes in limb morphology that allow us to use tools and walk upright, are in part due to human-specific genetic changes that altered when, where, and how genes are expressed during development. Over 20 000 putative regulatory elements with potential human-specific functions have been discovered. Understanding how these elements contributed to human evolution requires identifying candidates most likely to have shaped human traits, then studying them in genetically modified animal models. Here, we review the progress and challenges in generating and studying such models and propose a pathway for advancing the field. Finally, we highlight that large-scale collaborations across multiple research domains are essential to decipher what makes us human.

Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations

Across biological systems, cells undergo coordinated changes in gene expression, resulting in transcriptome dynamics that unfold within a low-dimensional manifold. While low-dimensional dynamics can be extracted using RNA velocity, these algorithms can be fragile and rely on heuristics lacking statistical control. Moreover, the estimated vector field is not dynamically consistent with the traversed gene expression manifold. To address these challenges, we introduce a Bayesian model of RNA velocity that couples velocity field and manifold estimation in a reformulated, unified framework, identifying the parameters of an explicit dynamical system. Focusing on the cell cycle, we implement VeloCycle to study gene regulation dynamics on one-dimensional periodic manifolds and validate its ability to infer cell cycle periods using live imaging. We also apply VeloCycle to reveal speed differences in regionally defined progenitors and Perturb-seq gene knockdowns. Overall, VeloCycle expands the single-cell RNA sequencing analysis toolkit with a modular and statistically consistent RNA velocity inference framework.

A multi-regional human brain atlas of chromatin accessibility and gene expression facilitates promoter-isoform resolution genetic fine-mapping

Brain region- and cell-specific transcriptomic and epigenomic features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression profiles in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions were strongly enriched for neuropsychiatric disease risk variants. Moreover, we built enhancer-promoter interactions at promoter-isoform resolution across different brain regions and highlighted the contribution of brain region-specific and promoter-isoform-specific regulation to neuropsychiatric disorders. Including promoter-isoform resolution uncovers additional distal elements implicated in the heritability of diseases, thereby increasing the power to fine-map risk genes. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and underscore the importance of considering isoform information in gene regulation.

High content of nuclei-free low-quality cells in reference single-cell atlases: a call for more stringent quality control using nuclear fraction

The advent of droplet-based single-cell RNA-sequencing (scRNA-seq) has dramatically increased data throughput, enabling the release of a diverse array of tissue cell atlases to the public. However, we will show that prominent initiatives such as the Human Cell Atlas [1], the Tabula Sapiens [2] and the Tabula Muris [3] contain a significant amount of contamination products (frequently affecting the whole organ) in their data portals due to suboptimal quality filtering. Our work addresses a critical gap by advocating for more stringent quality filtering, highlighting the imperative for a shift from existing standards, which currently lean towards greater permissiveness. We will show the importance of incorporating cell intronic fraction in quality control -or MALAT1 expression otherwise- showcasing its informative nature and potential to elevate cell atlas data reliability. In summary, here, we unveil the hidden intronic landscape of every tissue and highlight the importance of more rigorous single-cell RNA-sequencing quality assessment in cell atlases to enhance their applicability in diverse downstream analyses.

INTERSPECIES ORGANOIDS REVEAL HUMAN-SPECIFIC MOLECULAR FEATURES OF DOPAMINERGIC NEURON DEVELOPMENT AND VULNERABILITY

The disproportionate expansion of telencephalic structures during human evolution involved tradeoffs that imposed greater connectivity and metabolic demands on midbrain dopaminergic neurons. Despite the central role of dopaminergic neurons in human-enriched disorders, molecular specializations associated with human-specific features and vulnerabilities of the dopaminergic system remain unexplored. Here, we establish a phylogeny-in-a-dish approach to examine gene regulatory evolution by differentiating pools of human, chimpanzee, orangutan, and macaque pluripotent stem cells into ventral midbrain organoids capable of forming long-range projections, spontaneous activity, and dopamine release. We identify human-specific gene expression changes related to axonal transport of mitochondria and reactive oxygen species buffering and candidate cis- and trans-regulatory mechanisms underlying gene expression divergence. Our findings are consistent with a model of evolved neuroprotection in response to tradeoffs related to brain expansion and could contribute to the discovery of therapeutic targets and strategies for treating disorders involving the dopaminergic system.

Genome-wide screening reveals essential roles for HOX genes and imprinted genes during caudal neurogenesis of human embryonic stem cells

Mapping the essential pathways for neuronal differentiation can uncover new therapeutics and models for neurodevelopmental disorders. We thus utilized a genome-wide loss-of-function library in haploid human embryonic stem cells, differentiated into caudal neuronal cells. We show that essential genes for caudal neurogenesis are enriched for secreted and membrane proteins and that a large group of neurological conditions, including neurodegenerative disorders, manifest early neuronal phenotypes. Furthermore, essential transcription factors are enriched with homeobox (HOX) genes demonstrating synergistic regulation and surprising non-redundant functions between HOXA6 and HOXB6 paralogs. Moreover, we establish the essentialome of imprinted genes during neurogenesis, demonstrating that maternally expressed genes are non-essential in pluripotent cells and their differentiated germ layers, yet several are essential for neuronal development. These include Beckwith-Wiedemann syndrome- and Angelman syndrome-related genes, for which we suggest a novel regulatory pathway. Overall, our work identifies essential pathways for caudal neuronal differentiation and stage-specific phenotypes of neurological disorders.

Population-Level Cell Trajectory Inference Based on Gaussian Distributions

In the past decade, inferring developmental trajectories from single-cell data has become a significant challenge in bioinformatics. RNA velocity, with its incorporation of directional dynamics, has significantly advanced the study of single-cell trajectories. However, as single-cell RNA sequencing technology evolves, it generates complex, high-dimensional data with high noise levels. Existing trajectory inference methods, which overlook cell distribution characteristics, may perform inadequately under such conditions. To address this, we introduce CPvGTI, a Gaussian distribution-based trajectory inference method. CPvGTI utilizes a Gaussian mixture model, optimized by the Expectation-Maximization algorithm, to construct new cell populations in the original data space. By integrating RNA velocity, CPvGTI employs Gaussian Process Regression to analyze the differentiation trajectories of these cell populations. To evaluate the performance of CPvGTI, we assess CPvGTI's performance against several state-of-the-art methods using four structurally diverse simulated datasets and four real datasets. The simulation studies indicate that CPvGTI excels in pseudo-time prediction and structural reconstruction compared to existing methods. Furthermore, the discovery of new branch trajectories in human forebrain and mouse hematopoiesis datasets confirms CPvGTI's superior performance.

An integrated transcriptomic cell atlas of human neural organoids

Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.7 million cells1-26. Mapping to developing human brain references27-30 shows primary cell types and states that have been generated in vitro, and estimates transcriptomic similarity between primary and organoid counterparts across protocols. We provide a programmatic interface to browse the atlas and query new datasets, and showcase the power of the atlas to annotate organoid cell types and evaluate new organoid protocols. Finally, we show that the atlas can be used as a diverse control cohort to annotate and compare organoid models of neural disease, identifying genes and pathways that may underlie pathological mechanisms with the neural models. The human neural organoid cell atlas will be useful to assess organoid fidelity, characterize perturbed and diseased states and facilitate protocol development.

Generation of Mammalian Astrocyte Functional Heterogeneity

Mammalian astrocytes have regional roles within the brain parenchyma. Indeed, the notion that astrocytes are molecularly heterogeneous could help explain how the central nervous system (CNS) retains embryonic positional information through development into specialized regions into adulthood. A growing body of evidence supports the concept of morphological and molecular differences between astrocytes in different brain regions, which might relate to their derivation from regionally patterned radial glia and/or local neuron inductive cues. Here, we review evidence for regionally encoded functions of astrocytes to provide an integrated concept on lineage origins and heterogeneity to understand regional brain organization, as well as emerging technologies to identify and further investigate novel roles for astrocytes.

A polarized FGF8 source specifies frontotemporal signatures in spatially oriented cell populations of cortical assembloids

Organoids generating major cortical cell types in distinct compartments are used to study cortical development, evolution and disorders. However, the lack of morphogen gradients imparting cortical positional information and topography in current systems hinders the investigation of complex phenotypes. Here, we engineer human cortical assembloids by fusing an organizer-like structure expressing fibroblast growth factor 8 (FGF8) with an elongated organoid to enable the controlled modulation of FGF8 signaling along the longitudinal organoid axis. These polarized cortical assembloids mount a position-dependent transcriptional program that in part matches the in vivo rostrocaudal gene expression patterns and that is lost upon mutation in the FGFR3 gene associated with temporal lobe malformations and intellectual disability. By producing spatially oriented cell populations with signatures related to frontal and temporal area identity within individual assembloids, this model recapitulates in part the early transcriptional divergence embedded in the protomap and enables the study of cortical area-relevant alterations underlying human disorders.