Identification of visual cortex cell types and species differences using single-cell RNA sequencing

Synaptic plasticity in human thalamocortical assembloids

Synaptic plasticities, such as long-term potentiation (LTP) and depression (LTD), tune synaptic efficacy and are essential for learning and memory. Current studies of synaptic plasticity in humans are limited by a lack of adequate human models. Here, we modeled the thalamocortical system by fusing human induced pluripotent stem cell-derived thalamic and cortical organoids. Single-nucleus RNA sequencing revealed that >80% of cells in thalamic organoids were glutamatergic neurons. When fused to form thalamocortical assembloids, thalamic and cortical organoids formed reciprocal long-range axonal projections and reciprocal synapses detectable by light and electron microscopy, respectively. Using whole-cell patch-clamp electrophysiology and two-photon imaging, we characterized glutamatergic synaptic transmission. Thalamocortical and corticothalamic synapses displayed short-term plasticity analogous to that in animal models. LTP and LTD were reliably induced at both synapses; however, their mechanisms differed from those previously described in rodents. Thus, thalamocortical assembloids provide a model system for exploring synaptic plasticity in human circuits.

Single-nucleus multi-omics of Parkinson's disease reveals a glutamatergic neuronal subtype susceptible to gene dysregulation via alteration of transcriptional networks

The genetic architecture of Parkinson's disease (PD) is complex and multiple brain cell subtypes are involved in the neuropathological progression of the disease. Here we aimed to advance our understanding of PD genetic complexity at a cell subtype precision level. Using parallel single-nucleus (sn)RNA-seq and snATAC-seq analyses we simultaneously profiled the transcriptomic and chromatin accessibility landscapes in temporal cortex tissues from 12 PD compared to 12 control subjects at a granular single cell resolution. An integrative bioinformatic pipeline was developed and applied for the analyses of these snMulti-omics datasets. The results identified a subpopulation of cortical glutamatergic excitatory neurons with remarkably altered gene expression in PD, including differentially-expressed genes within PD risk loci identified in genome-wide association studies (GWAS). This was the only neuronal subtype showing significant and robust overexpression of SNCA. Further characterization of this neuronal-subpopulation showed upregulation of specific pathways related to axon guidance, neurite outgrowth and post-synaptic structure, and downregulated pathways involved in presynaptic organization and calcium response. Additionally, we characterized the roles of three molecular mechanisms in governing PD-associated cell subtype-specific dysregulation of gene expression: (1) changes in cis-regulatory element accessibility to transcriptional machinery; (2) changes in the abundance of master transcriptional regulators, including YY1, SP3, and KLF16; (3) candidate regulatory variants in high linkage disequilibrium with PD-GWAS genomic variants impacting transcription factor binding affinities. To our knowledge, this study is the first and the most comprehensive interrogation of the multi-omics landscape of PD at a cell-subtype resolution. Our findings provide new insights into a precise glutamatergic neuronal cell subtype, causal genes, and non-coding regulatory variants underlying the neuropathological progression of PD, paving the way for the development of cell- and gene-targeted therapeutics to halt disease progression as well as genetic biomarkers for early preclinical diagnosis.

Multi-sample non-negative spatial factorization

It is important to model biological variation when analyzing spatial transcriptomics data from multiple samples. One approach to multi-sample analysis is to spatially align samples, but this is a challenging problem. Here, we provide an alignment-free framework for generalizing a one-sample spatial factorization model to multi-sample data. Using this framework, we develop a method, called multi-sample non-negative spatial factorization (mNSF) that extends the one-sample non-negative spatial factorization (NSF) framework to a multi-sample dataset. Our model allows for a sample-specific model for the spatial correlation structure and extracts a low-dimensional representation of the data. We illustrate the performance of mNSF by simulation studies and real data. mNSF identifies true factors in simulated data, identifies shared anatomical regions across samples in real data and reveals region-specific biological functions. mNSFs performance is similar to alignment based methods when alignment is possible, but extends analysis to situations where spatial alignment is impossible. We expect multi-sample factorization methods to be a powerful class of methods for analyzing spatially resolved transcriptomics data.

Functional diversities within neurons and astrocytes in the adult rat auditory cortex revealed by single-nucleus RNA sequencing

The mammalian cerebral cortex is composed of a rich diversity of cell types. Cortical cells are organized into networks that rely on their functional diversity to ultimately carry out a variety of sophisticated cognitive functions. To investigate the breadth of transcriptional diverse cell types in the sensory cortex, we have used single-nucleus RNA sequencing (snRNA-seq) in the auditory cortex of the adult rat. A variety of unique excitatory and inhibitory neuron types were identified. In addition, we report for the first time a diversity of astrocytes in the auditory cortex that may represent functionally unique subtypes. Together, these results pave the way for building models of how neurons in the sensory cortex work in concert with astrocytes at synapses to fulfill high-cognitive functions like learning and memory.

Expression characteristics and potential function of non-coding RNA in mouse cortical cells

Non-coding RNAs (ncRNAs) play essential regulatory functions in various physiological and pathological processes in the brain. To systematically characterize the ncRNA profile in cortical cells, we downloaded single-cell SMART-Seq v4 data of mouse cerebral cortex. Our results revealed that the ncRNAs alone are sufficient to define the identity of most cortical cell types. We identified 1,600 ncRNAs that exhibited cell type specificity, even yielding to distinguish microglia from perivascular macrophages with ncRNA. Moreover, we characterized cortical layer and region specific ncRNAs, in line with the results by spatial transcriptome (ST) data. By constructing a co-expression network of ncRNAs and protein-coding genes, we predicted the function of ncRNAs. By integrating with genome-wide association studies data, we established associations between cell type-specific ncRNAs and traits related to neurological disorders. Collectively, our study identified differentially expressed ncRNAs at multiple levels and provided the valuable resource to explore the functions and dysfunctions of ncRNAs in cortical cells.

Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity

Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.

Microglial inflammation in genome instability: A neurodegenerative perspective

The maintenance of genome stability is crucial for cell homeostasis and tissue integrity. Numerous human neuropathologies display chronic inflammation in the central nervous system, set against a backdrop of genome instability, implying a close interplay between the DNA damage and immune responses in the context of neurological disease. Dissecting the molecular mechanisms of this crosstalk is essential for holistic understanding of neuroinflammatory pathways in genome instability disorders. Non-neuronal cell types, specifically microglia, are major drivers of neuroinflammation in the central nervous system with neuro-protective and -toxic capabilities. Here, we discuss how persistent DNA damage affects microglial homeostasis, zooming in on the cytosolic DNA sensing cGAS-STING pathway and the downstream inflammatory response, which can drive neurotoxic outcomes in the context of genome instability.

ScISOr-ATAC reveals convergent and divergent splicing and chromatin specificities between matched cell types across cortical regions, evolution, and in Alzheimer's Disease

Multimodal measurements have become widespread in genomics, however measuring open chromatin accessibility and splicing simultaneously in frozen brain tissues remains unconquered. Hence, we devised Single-Cell-ISOform-RNA sequencing coupled with the Assay-for-Transposase-Accessible-Chromatin (ScISOr-ATAC). We utilized ScISOr-ATAC to assess whether chromatin and splicing alterations in the brain convergently affect the same cell types or divergently different ones. We applied ScISOr-ATAC to three major conditions: comparing (i) the Rhesus macaque (Macaca mulatta) prefrontal cortex (PFC) and visual cortex (VIS), (ii) cross species divergence of Rhesus macaque versus human PFC, as well as (iii) dysregulation in Alzheimer's disease in human PFC. We found that among cortical-layer biased excitatory neuron subtypes, splicing is highly brain-region specific for L3-5/L6 IT_RORB neurons, moderately specific in L2-3 IT_CUX2.RORB neurons and unspecific in L2-3 IT_CUX2 neurons. In contrast, at the chromatin level, L2-3 IT_CUX2.RORB neurons show the highest brain-region specificity compared to other subtypes. Likewise, when comparing human and macaque PFC, strong evolutionary divergence on one molecular modality does not necessarily imply strong such divergence on another molecular level in the same cell type. Finally, in Alzheimer's disease, oligodendrocytes show convergently high dysregulation in both chromatin and splicing. However, chromatin and splicing dysregulation most strongly affect distinct oligodendrocyte subtypes. Overall, these results indicate that chromatin and splicing can show convergent or divergent results depending on the performed comparison, justifying the need for their concurrent measurement to investigate complex systems. Taken together, ScISOr-ATAC allows for the characterization of single-cell splicing and chromatin patterns and the comparison of sample groups in frozen brain samples.

Towards correlative archaeology of the human mind

Retracing human cognitive origins started out at the systems level with the top-down interpretation of archaeological records spanning from man-made artifacts to endocasts of ancient skulls. With emerging evolutionary genetics and organoid technologies, it is now possible to deconstruct evolutionary processes on a molecular/cellular level from the bottom-up by functionally testing archaic alleles in experimental models. The current challenge is to complement these approaches with novel strategies that allow a holistic reconstruction of evolutionary patterns across human cognitive domains. We argue that computational neuroarcheology can provide such a critical mesoscale framework at the brain network-level, linking molecular/cellular (bottom-up) to systems (top-down) level data for the correlative archeology of the human mind.

Patch-seq: Advances and Biological Applications

Multimodal analysis of gene-expression patterns, electrophysiological properties, and morphological phenotypes at the single-cell/single-nucleus level has been arduous because of the diversity and complexity of neurons. The emergence of Patch-sequencing (Patch-seq) directly links transcriptomics, morphology, and electrophysiology, taking neuroscience research to a multimodal era. In this review, we summarized the development of Patch-seq and recent applications in the cortex, hippocampus, and other nervous systems. Through generating multimodal cell type atlases, targeting specific cell populations, and correlating transcriptomic data with phenotypic information, Patch-seq has provided new insight into outstanding questions in neuroscience. We highlight the challenges and opportunities of Patch-seq in neuroscience and hope to shed new light on future neuroscience research.

Specialized astrocytes mediate glutamatergic gliotransmission in the CNS

Multimodal astrocyte-neuron communications govern brain circuitry assembly and function1. For example, through rapid glutamate release, astrocytes can control excitability, plasticity and synchronous activity2,3 of synaptic networks, while also contributing to their dysregulation in neuropsychiatric conditions4-7. For astrocytes to communicate through fast focal glutamate release, they should possess an apparatus for Ca2+-dependent exocytosis similar to neurons8-10. However, the existence of this mechanism has been questioned11-13 owing to inconsistent data14-17 and a lack of direct supporting evidence. Here we revisited the astrocyte glutamate exocytosis hypothesis by considering the emerging molecular heterogeneity of astrocytes18-21 and using molecular, bioinformatic and imaging approaches, together with cell-specific genetic tools that interfere with glutamate exocytosis in vivo. By analysing existing single-cell RNA-sequencing databases and our patch-seq data, we identified nine molecularly distinct clusters of hippocampal astrocytes, among which we found a notable subpopulation that selectively expressed synaptic-like glutamate-release machinery and localized to discrete hippocampal sites. Using GluSnFR-based glutamate imaging22 in situ and in vivo, we identified a corresponding astrocyte subgroup that responds reliably to astrocyte-selective stimulations with subsecond glutamate release events at spatially precise hotspots, which were suppressed by astrocyte-targeted deletion of vesicular glutamate transporter 1 (VGLUT1). Furthermore, deletion of this transporter or its isoform VGLUT2 revealed specific contributions of glutamatergic astrocytes in cortico-hippocampal and nigrostriatal circuits during normal behaviour and pathological processes. By uncovering this atypical subpopulation of specialized astrocytes in the adult brain, we provide insights into the complex roles of astrocytes in central nervous system (CNS) physiology and diseases, and identify a potential therapeutic target.

Neural cell isolation from adult macaques for high-throughput analyses and neurosphere cultures

The low number of neural progenitor cells (NPCs) present in the adult and aged primate brains represents a challenge for generating high-yield and viable in vitro cultures of primary brain cells. Here we report a step-by-step approach for the fast and reproducible isolation of high-yield and viable primary brain cells, including mature neurons, immature cells and NPCs, from adult and aged macaques. We describe the anesthesia, transcardial perfusion and brain tissue preparation; the subsequent microdissection of the regions of interest and their enzymatic dissociation, leading to the separation of single cells. The cell isolation steps of our protocol can also be used for routine cell culturing, in particular for NPC expansion and differentiation, suitable for studies of hippocampal neurogenesis in the adult macaque brain. The purified primary brain cells are largely free from myelin debris and erythrocytes, paving the way for multiple downstream applications in vitro and in vivo. When combined with single-cell profiling techniques, this approach allows an unbiased and comprehensive mapping of cell states in the adult and aged macaque brain, which is needed to advance our understanding of human cognitive and neurological diseases. The neural cell isolation protocol requires 4 h and a team of four to six users with expertize in primary brain cell isolation to avoid tissue hypoxia during the time-sensitive steps of the procedure.

Advances in AAV technology for delivering genetically encoded cargo to the nonhuman primate nervous system

Modern neuroscience approaches including optogenetics, calcium imaging, and other genetic manipulations have facilitated our ability to dissect specific circuits in rodent models to study their role in neurological disease. These approaches regularly use viral vectors to deliver genetic cargo (e.g., opsins) to specific tissues and genetically-engineered rodents to achieve cell-type specificity. However, the translatability of these rodent models, cross-species validation of identified targets, and translational efficacy of potential therapeutics in larger animal models like nonhuman primates remains difficult due to the lack of efficient primate viral vectors. A refined understanding of the nonhuman primate nervous system promises to deliver insights that can guide the development of treatments for neurological and neurodegenerative diseases. Here, we outline recent advances in the development of adeno-associated viral vectors for optimized use in nonhuman primates. These tools promise to help open new avenues for study in translational neuroscience and further our understanding of the primate brain.

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing

Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.