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Background: While traditional histologic neuropathological assessment of neurodegenerative disease has tremendous diagnostic value, insights into neurodegeneration's pathophysiological underpinnings can be significantly enhanced with large‐scale quantitative analyses. As part of the Seattle Alzheimer's Disease Brain Cell Atlas (SEA‐AD), we present a neuropathology dataset across 84 brains spanning the spectrum of AD neuropathologic change donated by UW Alzheimer's Disease Research Center and Adult Changes in Thought study participants. Method: Human brain tissue was collected at rapid autopsy (postmortem interval <12 hours). One hemisphere (randomly selected) was embedded in alginate for uniform coronal slicing (4mm), with alternating slabs fixed in 10% neutral buffered formalin or frozen in a dry ice isopentane slurry. Superior and Middle Temporal Gyrus (MTG) was sampled from fixed slabs and subjected to standard processing, embedding, sectioning (5µm), histochemical (H&E/Luxol fast blue), and immunohistochemical (duplex pTau and pTDP‐43, Aβ and Iba1, and monoplex GFAP, a‐synuclein, and NeuN) labeling. HALO image analysis software (Indica Labs, Albuquerque NM) was used to define and quantify relevant cellular and pathological features within each cortical layer (Figures 1‐3). Result: 84 individuals were included in these analyses (Table 1). While quantitative metrics of pTau and Aβ aligned with traditional neuropathological measures, they showed substantial variability within discrete diagnostic stages (Figure 4). These findings were robust to quantification (discrete count vs. total area stained) and normalization (total nuclei vs. total area analyzed) methods, and highlight the importance of deploying highly quantitative, continuous measures of pathology in the study of neurodegeneration. This unique resource provides spatially preserved measures of pathologic burden across the spectrum of AD with potential for correlative analysis across pathologies, clinical and biomarker parameters, and omics applications to better support the identification of vulnerable cell types in early stages of AD progression, the principal goal of SEA‐AD. Conclusion: Here we present a large‐scale quantitative neuropathology dataset, which enables analysis of pathological proteins and cell types at unprecedented scale and accuracy. Little is known about the interactions of AD‐relevant cell types with pathologic peptides across disease progression. The presented analyses exemplify the potential of this unique publicly‐accessible resource to identify and quantify novel disease‐relevant relationships. [ABSTRACT FROM AUTHOR]

Comprehensive knowledge of the brain's wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease., A central principle of neuroscience is that the nervous system is a network of diverse types of neurons and supporting cells communicating with each other mainly through synaptic connections. This [...]

Enhancers integrate transcription factor signaling pathways that drive cell fate specification in the developing brain. We paired enhancer labeling and single-cell RNA-sequencing (scRNA-seq) to delineate and distinguish specification of neuronal lineages in mouse medial, lateral, and caudal ganglionic eminences (MGE, LGE, and CGE) at embryonic day (E)11.5. We show that scRNA-seq clustering using transcription factors improves resolution of regional and developmental populations, and that enhancer activities identify specific and overlapping GE-derived neuronal populations. First, we mapped the activities of seven evolutionarily conserved brain enhancers at single-cell resolution in vivo, finding that the selected enhancers had diverse activities in specific progenitor and neuronal populations across the GEs. We then applied enhancer-based labeling, scRNA-seq, and analysis of in situ hybridization data to distinguish transcriptionally distinct and spatially defined subtypes of MGE-derived GABAergic and cholinergic projection neurons and interneurons. Our results map developmental origins and specification paths underlying neurogenesis in the embryonic basal ganglia and showcase the power of scRNA-seq combined with enhancer-based labeling to resolve the complex paths of neuronal specification underlying mouse brain development. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common form of dementia. The progression of AD throughout the brain follows a stereotypical pattern that can be described by the quantification of histopathological changes in several brain regions. As part of The Seattle Alzheimer's Disease Cell Atlas (SEA‐AD, https://sea-ad.org), we previously quantified pathological proteins in the middle temporal gyrus (MTG) and used them to describe disease progression, vulnerable cell types, and the MTG molecular changes related to disease Method: In this work, we expanded our results and undertook a comparative approach. We measured a battery of neuropathological proteins (staining NeuN, AT8, IBA1, GFAP, 6e10, pTDP43, and a‐Syn immunoreactivity, and analyzing them with machine learning) in the middle temporal gyrus, the middle frontal gyrus, and medial entorhinal cortex in 84 donors. In addition, we undertook a multimodal single‐cell analysis of such regions, profiling cells using single‐cell RNA‐seq, ATAC‐seq, Multiome, and spatial transcriptomic. Borrowing from our hierarchically resolved cell types in MTG, based on the BRAIN initiative cell type reference, we used machine learning algorithms to create multimodal cell type maps across regions. We used Bayesian statistics to identify differentially accessible regulatory elements, link them to the affected genes and the regulatory transcriptional machinery binding in such elements. Result: We identified regional vulnerable neuronal populations and a core set of transcriptionally similar cell types susceptible to disease across the cortex. We created a cortex‐wide disease progression map combining neuropathological data from our three profiled regions with latent Bayesian statistical algorithms. In each area, we developed an AD pseudo‐progression timescale that describes the burden of disease in the area and, next, combined all areas to create a cortex‐wide holistic pseudo‐progression. We used the mapped cell types and our developed scale to synchronize changes occurring in each patient, describing abundances, gene expression, and chromatin accessibility modifications. Conclusion: The progression scale developed in this study serves as a reference to align changes across brain regions and, in the future, to reconcile differences across cohorts. [ABSTRACT FROM AUTHOR]

Background: The Seattle Alzheimer's Disease Cell Atlas (SEA‐AD, https://sea-ad.org) is a large‐scale effort to identify, at single cell resolution, the cellular and molecular mechanisms that cause AD and facilitate its progression. SEA‐AD brings together quantitative neuropathology (QNP) derived from classic histopathological and cell type stains with single nucleus transcriptomics, epigenetics, and spatial transcriptomics on a cohort of 84 aged donors that span the pathological and cognitive disease spectrum, including unaffected controls. Method: We ordered SEA‐AD donors based on QNP using a Bayesian latent space model to construct a model‐estimated "pseudo‐progression" (PS). We then used a general linear mixed effects model to test for gene expression changes along the PS in each of the BRAIN initiative's 139 cell types present in SEA‐AD's single nucleus RNA sequencing dataset (∼1.2 million nuclei) from the middle temporal gyrus. By separately fitting models to donors with lower and higher pathology, we obtained two beta coefficients for each gene that enabled distinction between early, late, and consistent up‐ and down‐regulation along PS. We then tested whether the betas for each gene were different across all cell types or in only certain ones to measure specificity. We curated gene modules from biological processes potentially relevant to AD, identified in gene‐set enrichment analyses and prior studies, and categorized each gene within them based on their dynamics and specificity. Result: Roughly one‐third of genes had differential expression across neuronal cell types (mean betas > 0.2), split evenly between up‐ and down‐regulation, while a smaller subset were changed in specific cell types. Modules enriched in broadly changed genes that had increased expression early in PS included those involved with the microtubule cytoskeleton, vesicle adaptors, and neurotransmitter receptors, while those with decreased expression included those involved with cholesterol synthesis, glycolysis, mitochondrial function, and neurofilaments. Among the genes changed only in specific cell types were NOTCH2 in Somatostatin and Parvalbumin interneurons selectively vulnerable to pathology, PTPRG in disease associated microglia, and COL21A1 in disease associated astrocytes. Conclusion: Broadly affected modules identified by SEA‐AD suggest most neurons are affected by disease pathology and cell type‐specific differences may provide clues to selective vulnerability. [ABSTRACT FROM AUTHOR]

Abstract Background Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts. Results By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns. Conclusions Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function.

Background: Alzheimer's disease (AD) is the most common form of dementia, representing ∼70% of all dementia cases, and affecting much of the aged population. Currently our understanding of AD neuropathology is largely centered on characteristic deposition of certain neuropathological proteins and identification of histologically defined neuronal populations. Molecular tools to characterize the transcriptome, epigenome, and spatial organization of single cells in complex brain tissues allow a more refined look at how the neurotypical brain changes in AD than had been possible previously. Linking molecular, cellular, genomic, cognitive, and pathological indicators of AD progression will be essential for understanding disease mechanisms. Methods: The Seattle Alzheimer's Disease Brain Cell Atlas (SEA‐AD) brings together experts in AD research and large‐scale molecular/anatomical brain mapping to modernize AD tissue banking methods, and to combine traditional and quantitative neuropathology with emerging genotyping, single nucleus transcriptomics, single nucleus epigenomics, and spatial transcriptomics technologies. Applied to multiple brain regions in donors spanning different stages of AD pathology, these techniques will identification of cell type specific molecular pathways and yield valuable insights into selective vulnerability or resistance to pathology. Two well characterized cohorts (Adult Changes in Thought (ACT) and the University of Washington ADRC) provided 84 subjects of varying degrees of AD severity, including cognitively normal subjects. Results: The initial focus of SEA‐AD was on integrating and interpreting relationships between all collected multimodal data in middle temporal gyrus (MTG). Identified cell types and molecular pathways of interest are presented separately and are both consistent with and expand upon results found from ROSMAP and other cohorts. The complete SEA‐AD MTG atlas is now freely and publicly available at brain‐map.org and includes access to all data and associated donor metadata, tools for visualization and exploration of molecular data, exploration of pathology images, a tool for assigning cell types to community‐based ‐omics datasets, comprehensive documentation, and user support. Conclusions: SEA‐AD has developed a high resolution, high‐quality, publicly accessible atlas of aging and AD, and is designed to better understand the complex and likely heterogenous nature of AD. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common form of dementia, which can be detected early as mild cognitive impairment but has no broadly effective treatments to halt patients' yearslong decline. Histopathology studies have long noted dramatic, progressive, and stereotyped changes across numerous brain regions, including protein aggregate formation and even selective loss of molecularly defined neuronal populations. But the underlying molecular and cellular mechanisms that cause AD and facilitate its progression remain unknown or are only coarsely understood, hampering efforts to treat or cure the disease. Method: To uncover these mechanisms, we characterized the transcriptomic and epigenetic landscapes of AD by applying single nucleus RNA and ATAC sequencing to ∼8 million nuclei isolated from 3 cortical regions (entorhinal cortex, middle temporal gyrus, and prefrontal cortex) in 84 aged donors that span the histopathological and cognitive disease spectrums (including unaffected controls) as part of a broader Seattle AD Brain Cell Atlas (SEA‐AD) effort. We identified ∼130 highly resolved transcriptional cell types from the BRAIN initiatives' neurotypical references and leveraged recently developed machine learning approaches to integrate and hierarchically classify nuclei across donors. This enabled characterization of cell type abundance, gene expression, and chromatin accessibility differences that correlate with AD neuropathology, cognition decline, and genetic background with unprecedented precision. Result: Our comprehensive molecular atlas identified specific intratelencephalic excitatory neurons, inhibitory neurons, and microglia subsets that have altered abundances, gene expression, and/or chromatin accessibility as a function of cognitive decline and quantitative neuropathology, suggesting these populations may be selectively vulnerable to AD or involved in disease etiology. Their differentially expressed genes and accessible chromatin regions include both those found by previous atlasing efforts and genome wide association studies as well as novel ones, providing new clues to the molecular pathways that underpin AD. By comparing the SEA‐AD atlas with the neurotypical references, we also identified how expression patterns of genes, chromatin accessibility, and cell‐cell interactions associated with AD are more broadly altered by the disease. Conclusion: The cell types and molecular pathways identified by our atlas provide new targets for the rational development of therapeutic interventions and as biomarkers for earlier detection of the disease. [ABSTRACT FROM AUTHOR]

The cellular components of mammalian neocortical circuits are diverse, and capturing this diversity in computational models is challenging. Here we report an approach for generating biophysically detailed models of 170 individual neurons in the Allen Cell Types Database to link the systematic experimental characterization of cell types to the construction of cortical models. We build models from 3D morphologies and somatic electrophysiological responses measured in the same cells. Densities of active somatic conductances and additional parameters are optimized with a genetic algorithm to match electrophysiological features. We evaluate the models by applying additional stimuli and comparing model responses to experimental data. Applying this technique across a diverse set of neurons from adult mouse primary visual cortex, we verify that models preserve the distinctiveness of intrinsic properties between subsets of cells observed in experiments. The optimized models are accessible online alongside the experimental data. Code for optimization and simulation is also openly distributed. [ABSTRACT FROM AUTHOR]

Despite the widespread use of current-source density ( CSD) analysis of extracellular potential recordings in the brain, the physical mechanisms responsible for the generation of the signal are still debated. While the extracellular potential is thought to be exclusively generated by the transmembrane currents, recent studies suggest that extracellular diffusive, advective and displacement currents-traditionally neglected-may also contribute considerably toward extracellular potential recordings. Here, we first justify the application of the electro-quasistatic approximation of Maxwell's equations to describe the electromagnetic field of physiological origin. Subsequently, we perform spatial averaging of currents in neural tissue to arrive at the notion of the CSD and derive an equation relating it to the extracellular potential. We show that, in general, the extracellular potential is determined by the CSD of membrane currents as well as the gradients of the putative extracellular diffusion current. The diffusion current can contribute significantly to the extracellular potential at frequencies less than a few Hertz; in which case it must be subtracted to obtain correct CSD estimates. We also show that the advective and displacement currents in the extracellular space are negligible for physiological frequencies while, within cellular membrane, displacement current contributes toward the CSD as a capacitive current. Taken together, these findings elucidate the relationship between electric currents and the extracellular potential in brain tissue and form the necessary foundation for the analysis of extracellular recordings. [ABSTRACT FROM AUTHOR]

Summary Understanding how brain activation mediates behaviors is a central goal of systems neuroscience. Here, we apply an automated method for mapping brain activation in the mouse in order to probe how sex-specific social behaviors are represented in the male brain. Our method uses the immediate-early-gene c-fos , a marker of neuronal activation, visualized by serial two-photon tomography: the c- fos -GFP+ neurons are computationally detected, their distribution is registered to a reference brain and a brain atlas, and their numbers are analyzed by statistical tests. Our results reveal distinct and shared female and male interaction-evoked patterns of male brain activation representing sex discrimination and social recognition. We also identify brain regions whose degree of activity correlates to specific features of social behaviors and estimate the total numbers and the densities of activated neurons per brain areas. Our study opens the door to automated screening of behavior-evoked brain activation in the mouse. [ABSTRACT FROM AUTHOR]

The neurogenic potential of the subgranular zone (SGZ) of the hippocampal dentate gyrus is likely to be regulated by molecular cues arising from its complex heterogeneous cellular environment. Through transcriptome analysis using laser microdissection coupled with DNA microarrays, in combination with analysis of genome-wide in situ hybridization data, we identified 363 genes selectively enriched in adult mouse SGZ. These genes reflect expression in the different constituent cell types, including progenitor and dividing cells, immature granule cells, astrocytes, oligodendrocytes and GABAergic interneurons. Similar transcriptional profiling in the rhesus monkey dentate gyrus across postnatal development identified a highly overlapping set of SGZ-enriched genes, which can be divided based on temporal profiles to reflect maturation of glia versus granule neurons. Furthermore, we identified a neurogenesis-related gene network with decreasing postnatal expression that is highly correlated with the declining number of proliferating cells in dentate gyrus over postnatal development. Many of the genes in this network showed similar postnatal downregulation in mouse, suggesting a conservation of molecular mechanisms underlying developmental and adult neurogenesis in rodents and primates. Conditional deletion of Sox4 and Sox11, encoding two neurogenesis-related transcription factors central in this network, produces a mouse with no hippocampus, confirming the crucial role for these genes in regulating hippocampal neurogenesis. [ABSTRACT FROM AUTHOR]

Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

The Cre/lox system is widely used in mice to achieve cell-type-specific gene expression. However, a strong and universally responding system to express genes under Cre control is still lacking. We have generated a set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra. The robust native fluorescence of these reporters enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo. Using these reporters and a high-throughput in situ hybridization platform, we are systematically profiling Cre-directed gene expression throughout the mouse brain in several Cre-driver lines, including new Cre lines targeting different cell types in the cortex. Our expression data are displayed in a public online database to help researchers assess the utility of various Cre-driver lines for cell-type-specific genetic manipulation. [ABSTRACT FROM AUTHOR]

The Allen Brain Atlases enable the study of spatially resolved, genome-wide gene expression patterns across the mammalian brain. Several explorative studies have applied linear dimensionality reduction methods such as Principal Component Analysis (PCA) and classical Multi-Dimensional Scaling (cMDS) to gain insight into the spatial organization of these expression patterns. In this paper, we describe a non-linear embedding technique called Barnes-Hut Stochastic Neighbor Embedding (BH-SNE) that emphasizes the local similarity structure of high-dimensional data points. By applying BH-SNE to the gene expression data from the Allen Brain Atlases, we demonstrate the consistency of the 2D, non-linear embedding of the sagittal and coronal mouse brain atlases, and across 6 human brains. In addition, we quantitatively show that BH-SNE maps are superior in their separation of neuroanatomical regions in comparison to PCA and cMDS. Finally, we assess the effect of higher-order principal components on the global structure of the BH-SNE similarity maps. Based on our observations, we conclude that BH-SNE maps with or without prior dimensionality reduction (based on PCA) provide comprehensive and intuitive insights in both the local and global spatial transcriptome structure of the human and mouse Allen Brain Atlases. [ABSTRACT FROM AUTHOR]

Summary: Although there have been major advances in elucidating the functional biology of the human brain, relatively little is known of its cellular and molecular organization. Here we report a large-scale characterization of the expression of ∼1,000 genes important for neural functions by in situ hybridization at a cellular resolution in visual and temporal cortices of adult human brains. These data reveal diverse gene expression patterns and remarkable conservation of each individual gene''s expression among individuals (95%), cortical areas (84%), and between human and mouse (79%). A small but substantial number of genes (21%) exhibited species-differential expression. Distinct molecular signatures, comprised of genes both common between species and unique to each, were identified for each major cortical cell type. The data suggest that gene expression profile changes may contribute to differential cortical function across species, and in particular, a shift from corticosubcortical to more predominant corticocortical communications in the human brain. [Copyright &y& Elsevier]

Summary: Genome-wide transcriptional profiling was used to characterize the molecular underpinnings of neocortical organization in rhesus macaque, including cortical areal specialization and laminar cell-type diversity. Microarray analysis of individual cortical layers across sensorimotor and association cortices identified robust and specific molecular signatures for individual cortical layers and areas, prominently involving genes associated with specialized neuronal function. Overall, transcriptome-based relationships were related to spatial proximity, being strongest between neighboring cortical areas and between proximal layers. Primary visual cortex (V1) displayed the most distinctive gene expression compared to other cortical regions in rhesus and human, both in the specialized layer 4 as well as other layers. Laminar patterns were more similar between macaque and human compared to mouse, as was the unique V1 profile that was not observed in mouse. These data provide a unique resource detailing neocortical transcription patterns in a nonhuman primate with great similarity in gene expression to human. [ABSTRACT FROM AUTHOR]

Summary: Availability of genome-scale in situ hybridization data allows systematic analysis of genetic neuroanatomical architecture. Within the hippocampus, electrophysiology and lesion and imaging studies demonstrate functional heterogeneity along the septotemporal axis, although precise underlying circuitry and molecular substrates remain uncharacterized. Application of unbiased statistical component analyses to genome-scale hippocampal gene expression data revealed robust septotemporal molecular heterogeneity, leading to the identification of a large cohort of genes with robust regionalized hippocampal expression. Manual mapping of heterogeneous CA3 pyramidal neuron expression patterns demonstrates an unexpectedly complex molecular parcellation into a relatively coherent set of nine expression domains in the septal/temporal and proximal/distal axes with reciprocal, nonoverlapping boundaries. Unique combinatorial profiles of adhesion molecules within these domains suggest corresponding differential connectivity, which is demonstrated for CA3 projections to the lateral septum using retrograde labeling. This complex, discrete molecular architecture provides a novel paradigm for predicting functional differentiation across the full septotemporal extent of the hippocampus. [Copyright &y& Elsevier]

The isocortex and hippocampal formation (HPF) in the mammalian brain play critical roles in perception, cognition, emotion, and learning. We profiled ∼1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and the isocortex share a common circuit organization. We also identify large-scale continuous and graded variations of cell types along isocortical depth, across the isocortical sheet, and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity, and function of these two brain structures. [Display omitted] • Single-cell transcriptomics from >1.3 million cells in the mouse cortex and hippocampus • Many neuron types specific to associational cortex and hippocampal regions are identified • Parallel cell-type and laminar organization between isocortex and hippocampal formation • Large-scale continuous neuron-type variation in isocortex and hippocampus/subiculum Single-cell transcriptomics of the entire mouse isocortex and hippocampal formation shows shared cellular and circuit organization and large-scale continuous gradients of neuron-type variation that illuminates the underlying relationship between these two critical brain structures. [ABSTRACT FROM AUTHOR]

Increasing interest in studies of prenatal human brain development, particularly using new single-cell genomics and anatomical technologies to create cell atlases, creates a strong need for accurate and detailed anatomical reference atlases. In this study, we present two cellular-resolution digital anatomical atlases for prenatal human brain at postconceptional weeks (PCW) 15 and 21. Both atlases were annotated on sequential Nissl-stained sections covering brain-wide structures on the basis of combined analysis of cytoarchitecture, acetylcholinesterase staining, and an extensive marker gene expression dataset. This high information content dataset allowed reliable and accurate demarcation of developing cortical and subcortical structures and their subdivisions. Furthermore, using the anatomical atlases as a guide, spatial expression of 37 and 5 genes from the brains, respectively, at PCW 15 and 21 was annotated, illustrating reliable marker genes for many developing brain structures. Finally, the present study uncovered several novel developmental features, such as the lack of an outer subventricular zone in the hippocampal formation and entorhinal cortex, and the apparent extension of both cortical (excitatory) and subcortical (inhibitory) progenitors into the prenatal olfactory bulb. These comprehensive atlases provide useful tools for visualization, segmentation, targeting, imaging, and interpretation of brain structures of prenatal human brain, and for guiding and interpreting the next generation of cell census and connectome studies., (© 2021 Wiley Periodicals LLC.)

Abundant evidence supports the presence of at least three distinct types of thalamocortical (TC) neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex (V1). Different types of TC neurons in mice, humans, and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of TC neurons in the primate dLGN: magnocellular (M) neurons, parvocellular (P) neurons, and two types of koniocellular (K) neurons. Despite extensively documented morphological and physiological differences between M and P neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. Likewise, the dominant feature of TC neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to the observed differences in morphology and cortical projection targets. Finally, alignment of transcriptome profiles across species highlights expanded diversity of GABAergic neurons in primate versus mouse dLGN and homologous types of TC neurons in primates that are distinct from TC neurons in mouse., Competing Interests: TB, Cv, VM, RH, ZY, TN, LG, GH, DB, JG, AY, EG, SP, TC, SS, EB, AS, BL, ND, KS, SS, AB, JP, MH, CK, GM, EL, HZ, BT No competing interests declared, (© 2021, Bakken et al.)

The advancement of single-cell RNA-sequencing technologies has led to an explosion of cell type definitions across multiple organs and organisms. While standards for data and metadata intake are arising, organization of cell types has largely been left to individual investigators, resulting in widely varying nomenclature and limited alignment between taxonomies. To facilitate cross-dataset comparison, the Allen Institute created the common cell type nomenclature (CCN) for matching and tracking cell types across studies that is qualitatively similar to gene transcript management across different genome builds. The CCN can be readily applied to new or established taxonomies and was applied herein to diverse cell type datasets derived from multiple quantifiable modalities. The CCN facilitates assigning accurate yet flexible cell type names in the mammalian cortex as a step toward community-wide efforts to organize multi-source, data-driven information related to cell type taxonomies from any organism., Competing Interests: JM, NG, BT, FC, Cv, TB, MH, HZ, EL, AB No competing interests declared, (© 2020, Miller et al.)

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type-specific dynamics. We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C , SATB2 , SOX5 , TCF4 , and TSHZ3 ) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.