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The underlying regulatory mechanisms of of human cortical diversity remains poorly understood. Here, authors profiled human brain cells to study how they use different gene programs across cortical regions, revealing molecular rules and specific transcription factors that drive functional specialization of neurons in the brain

A spatially resolved transcriptional atlas of the mid-gestational developing human brain has been created using laser-capture microdissection and microarray technology, providing a comprehensive reference resource which also enables new hypotheses about the nature of human brain evolution and the origins of neurodevelopmental disorders.

The expression of each of the roughly 22,000 genes of the mouse genome has been mapped, at cellular resolution, across all major structures of the mouse brain, revealing that 80% of all genes appear to be expressed in the brain.

A high-resolution gene expression atlas of prenatal and postnatal brain development of rhesus monkey charts global transcriptional dynamics in relation to brain maturation, while comparative analysis reveals human-specific gene trajectories; candidate risk genes associated with human neurodevelopmental disorders tend to be co-expressed in disease-specific patterns in the developing monkey neocortex.

The BRAIN Initiative Cell Census Network has constructed a multimodal cell census and atlas of the mammalian primary motor cortex in a landmark effort towards understanding brain cell-type diversity, neural circuit organization and brain function.

The affected cellular populations during Alzheimer’s disease progression remain understudied. Here the authors use a cohort of 84 donors, quantitative neuropathology and multimodal datasets from the BRAIN Initiative. Their pseudoprogression analysis revealed two disease phases.

A single-cell multiomics analysis of over 200,000 cells of the primary motor cortex of human, macaque, marmoset and mouse shows that divergence of transcription factor expression corresponds to species-specific epigenome landscapes, and conserved and divergent gene regulatory features are reflected in the evolution of the three-dimensional genome.

Delivering genes to and across the brain vasculature efficiently and specifically across species remains challenging. Here, the authors show that endothelial-specific AAVs with serotype flexibility enable redosing and transform the brain vasculature into an in vivo biofactory in genetically diverse rodents. In primates, these vectors cross the blood-brain-barrier and show broad tropism.

Laser microdissection and microarrays are used to assess 900 precise subdivisions of the brains from three healthy men with 60,000 gene expression probes; the resulting atlas allows comparisons between humans and other animals, and will facilitate studies of human neurological and psychiatric diseases.

Together with a companion paper, the generation of a transcriptomic atlas for the mouse lemur and analyses of example cell types establish this animal as a molecularly tractable primate model organism.

Together with an accompanying paper presenting a transcriptomic atlas of the mouse lemur, interrogation of the atlas provides a rich body of data to support the use of the organism as a model for primate biology and health.

Using transcriptomic data from human brain cells, the authors show that the expression patterns of the genes implicated in human cognition and brain evolution overlap in specific neuron types, and relate to cellular function and structure.

Application of multiplexed RNA in situ mapping techniques to human tissues remains challenging. Here, the authors report DART-FISH, a padlock probe-based technology capable of profiling large numbers of genes in centimetre-sized human tissue sections.

EEL FISH profiles spatial transcriptomes in single cells in large, complex tissue samples.

Analysis of single-cell expression data from the middle temporal gyrus of five primates together with analysis of network connectivity across 19 animals identifies genes with human-specific cellular expression and co-expression profiles that might contribute to evolutionary change in brain function.

Human and rodent supragranular pyramidal neurons differ in HCN channel-related properties. Comparison across primates reveals robust HCN1 expression and HCN channel-dependent physiology, with cell type dependent differences in macaques versus humans.

Combined patch clamp recording, biocytin staining and single-cell RNA-sequencing of human neurocortical neurons shows an expansion of glutamatergic neuron types relative to mouse that characterizes the greater complexity of the human neocortex.

Integration of single-cell RNA sequencing with genome-wide association data implicates specific brain cell types in schizophrenia. Gene sets previously associated with schizophrenia implicate the same cell types, which include pyramidal cells and medium spiny neurons.

An examination of motor cortex in humans, marmosets and mice reveals a generally conserved cellular makeup that is likely to extend to many mammalian species, but also differences in gene expression, DNA methylation and chromatin state that lead to species-dependent specializations.

The authors use single-nucleus RNA-seq to identify 10 GABAergic interneuron subtypes in human cortex layer 1. Molecular, morphological, and physiological evidence points to an emerging human cell type, the rosehip cell, not found in other species.

RNA-sequencing analysis of cells in the human cortex enabled identification of diverse cell types, revealing well-conserved architecture and homologous cell types as well as extensive differences when compared with datasets covering the analogous region of the mouse brain.

Analysis of ~10,000 cases of developmental delay and autism identifies 253 candidate neurodevelopmental disease genes. Network analysis highlights cell-specific enrichments of disease-related genes in the D1⁺ and D2⁺ spiny neurons of the striatum.

Little is known about von Economo neurons, which have been described in a subset of mammals and appear to be selectively lost in several human neurological diseases. Here, authors reveal the gene expression profile of these cells and show that they are likely long-distance projection neurons.

Single-cell transcriptomics of more than 20,000 cells from two functionally distinct areas of the mouse neocortex identifies 133 transcriptomic types, and provides a foundation for understanding the diversity of cortical cell types.

A complete genome sequence is presented of a female Neanderthal from Siberia, providing information about interbreeding between close relatives and uncovering gene flow events among Neanderthals, Denisovans and early modern humans, as well as establishing substitutions that became fixed in modern humans after their separation from the ancestors of Neanderthals and Denisovans.

Endocrinologists have traditionally focused on studying one hormone or organ system at a time. Here the authors use transcriptomic data from the mouse lemur to globally characterize primate hormonal signaling, describing hormone sources and targets, identifying conserved and primate specific regulation, and elucidating principles of the network.

Langseth et al. present cell type maps of human cortical tissue sections and show an efficient and robust workflow to accurately resolve anatomical organization of human brain tissue.

Using two-photon calcium imaging in vivo and intracellular recordings in vitro, the authors find that visual stimulation only weakly modifies coactivation patterns of inhibitory neurons, whereas excitatory neuron correlations are largely stimulus dependent.

This Resource describes data, code and tools developed for the Human Reference Atlas and the Human BioMolecular Atlas Program for building and navigating a multiscale human atlas.

The Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) is a multifaceted open-data resource that is designed to identify cellular and molecular pathologies that underlie Alzheimer’s disease. Integrating neuropathology, single-cell and spatial genomics, and longitudinal clinical metadata, SEA-AD is a unique resource for studying the pathogenesis of Alzheimer’s disease and related dementias.

An adversarial domain translation framework is presented for scalable integration of single-cell atlases across samples, technical platforms, data modalities and species.

Gouwens et al. established a morpho-electrical taxonomy of cell types for the mouse visual cortex via unsupervised clustering analysis of multiple quantitative features from 1,938 neurons available online at the Allen Cell Types Database.

The Human Cell Atlas (HCA) aims to characterize cells from diverse individuals across the globe to better understand human biology. Here, the authors lay out principles and action items that have been adopted to affirm HCA’s commitment to equity so that the atlas is beneficial to all of humanity.

This paper discusses how experimental and computational studies integrating multimodal data, such as RNA expression, connectivity and neural activity, are advancing our understanding of the architecture, mechanisms and function of cortical circuits.

Single-nucleus RNA sequencing analysis identifies different subclusters of oligodendroglia in white matter from individuals with multiple sclerosis compared with controls, and these differences may be important for understanding disease progression.

Timothy Yu and colleagues report that biallelic mutations in DCC cause a developmental syndrome characterized by widespread disruption of midline-bridging neuronal commissures, including agenesis of the corpus callosum, absence of hippocampal and anterior commissures, and ventral midline brainstem malformations. Clinical manifestations include horizontal gaze palsy, mirror movements, scoliosis and intellectual disability.

This resource article describes a bioinformatical tool that, accessing an extensive gene expression database, allows the definition and identification of new brain structures based on gene expression patterns.

The authors applied a correlation-based metric, ‘differential stability’ (DS), to assess reproducibility of gene expression patterning across individual brains, revealing mesoscale genetic organization. The highest DS genes were enriched for brain-related biological annotations, disease associations and drug targets, and their anatomical expression pattern correlated with resting state functional connectivity.

It is commonly thought that the dorsal hippocampus is implicated in memory and spatial navigation and the ventral hippocampus in anxiety-related behaviours. On the basis of gene expression, anatomical and electrophysiology studies, Strange and colleagues propose a new model of hippocampal functional anatomy, in which functional long-axis gradients are superimposed on discrete functional domains.

This Resource paper describes a set of five new reporter mice, derived from Rosa26, driving Cre-dependent strong and ubiquitous expression of fluorescent proteins. In particular, the new mice show clear and specific expression patterns in the adult brain. The mice are available through Jackson Laboratories, and growing expression datasets can be accessed at http://transgenicmouse.alleninstitute.org/.

In this Perspective, Teichmann and colleagues present ongoing efforts from consortia of the Human Cell Atlas to harmonize and integrate data sources into a reference cell ontology and the contributions of cell ontologies to discovery.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.