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In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli. Long-term cultures of human brain organoids display a high degree of cellular diversity, mature spontaneous neuronal networks and are sensitive to light. Enlightening organoids Three-dimensional cellular models of the human brain, or organoids, enable the in vitro study of cerebral development and disease, but exactly which cells are generated and how much of the brain's complexity they recreate is undefined. To investigate in depth the nature of cells in human cerebral organoids differentiated from pluripotent stem cells, Paola Arlotta and colleagues carried out droplet-based single-cell expression analysis on cells isolated from over 30 organoids at developmental stages ranging from 3 to 9 months and beyond. They identify a wide diversity of neurons and progenitors and show that the more mature organoids formed dendritic spines as well as electrically active networks, which responded to light stimulation. The authors suggest that organoids may facilitate the study of circuit function using physiological sensory mechanisms. Elsewhere in this issue, Sergiu Paşca and colleagues show that re-assembling ventral and dorsal forebrain spheroids obtained separately in vitro allows the migration of human interneurons and the formation of functional synapses.

Vessel loss precipitates many diseases. In particular, vessel loss resulting in hypoxia induces retinal neovascularization in diabetic retinopathy and in retinopathy of prematurity (ROP), major causes of blindness. Here we define insulin-like growth factor binding protein-3 (IGFBP3) as a new modulator of vascular survival and regrowth in oxygen-induced retinopathy. In IGFBP3-deficient mice, there was a dose-dependent increase in oxygen-induced retinal vessel loss. Subsequent to oxygen-induced retinal vessel loss, Igfbp3⁻/⁻ mice had a 31% decrease in retinal vessel regrowth versus controls after returning to room air. No difference in serum insulin-like growth factor 1 (IGF1) levels was observed among groups. Wild-type mice treated with exogenous IGFBP3 had a significant increase in vessel regrowth. This correlated with a 30% increase in endothelial progenitor cells in the retina at postnatal day 15, indicating that IGFBP3 could be serving as a progenitor cell chemoattractant. In a prospective clinical study, we measured IGFBP3 (and IGF1) plasma levels weekly and examined retinas in all premature infants born at gestational ages <32 weeks at high risk for ROP. The mean level of IGFBP3 at 30-35 weeks postmenstrual age (PMA) for infants with proliferative ROP (ROP stages 3>, n = 13) was 802 μg/liter, and for infants with no ROP (ROP stage 0, n = 38) the mean level was 974 μg/liter (P < 0.03). These results suggest that IGFBP3, acting independently of IGF1, helps to prevent oxygen-induced vessel loss and to promote vascular regrowth after vascular destruction in vivo in a dose-dependent manner, resulting in less retinal neovascularization.

The human retinal pigment epithelium (RPE) and choroid are complex tissues that provide crucial support to the retina. Disease affecting either of these supportive tissues can lead to irreversible blindness in the setting of age-related macular degeneration. In this study, single-cell RNA sequencing was performed on macular and peripheral regions of RPE-choroid from 7 human donor eyes in 2 independent experiments. In the first experiment, total RPE/choroid preparations were evaluated and expression profiles specific to RPE and major choroidal cell populations were identified. As choroidal endothelial cells represent a minority of the total RPE/choroidal cell population but are strongly implicated in age-related macular degeneration (AMD) pathogenesis, a second single-cell RNA-sequencing experiment was performed using endothelial cells enriched by magnetic separation. In this second study, we identified gene expression signatures along the choroidal vascular tree, classifying the transcriptome of human choriocapillaris, arterial, and venous endothelial cells. We found that the choriocapillaris highly and specifically expresses the regulator of cell cycle gene (RGCC), a gene that responds to complement activation and induces apoptosis in endothelial cells. In addition, RGCC was the most up-regulated choriocapillaris gene in a donor diagnosed with AMD. These results provide a characterization of the human RPE and choriocapillaris transcriptome, offering potential insight into the mechanisms of choriocapillaris response to complement injury and choroidal vascular disease in age-related macular degeneration.

The house mouse ( Mus musculus ) is an exceptional model system, combining genetic tractability with close evolutionary affinity to humans 1 , 2 . Mouse gestation lasts only 3 weeks, during which the genome orchestrates the astonishing transformation of a single-cell zygote into a free-living pup composed of more than 500 million cells. Here, to establish a global framework for exploring mammalian development, we applied optimized single-cell combinatorial indexing 3 to profile the transcriptional states of 12.4 million nuclei from 83 embryos, precisely staged at 2- to 6-hour intervals spanning late gastrulation (embryonic day 8) to birth (postnatal day 0). From these data, we annotate hundreds of cell types and explore the ontogenesis of the posterior embryo during somitogenesis and of kidney, mesenchyme, retina and early neurons. We leverage the temporal resolution and sampling depth of these whole-embryo snapshots, together with published data 4 – 8 from earlier timepoints, to construct a rooted tree of cell-type relationships that spans the entirety of prenatal development, from zygote to birth. Throughout this tree, we systematically nominate genes encoding transcription factors and other proteins as candidate drivers of the in vivo differentiation of hundreds of cell types. Remarkably, the most marked temporal shifts in cell states are observed within one hour of birth and presumably underlie the massive physiological adaptations that must accompany the successful transition of a mammalian fetus to life outside the womb. Single-cell transcriptome profiling of mouse embryos and newborn pups is combined with previously published data to construct a tree of cell-type relationships tracing development from zygote to birth.

A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce an analysis framework, named single-cell Decomposition using Hierarchical Autoencoder (scDHA), that reliably extracts representative information of each cell. The scDHA pipeline consists of two core modules. The first module is a non-negative kernel autoencoder able to remove genes or components that have insignificant contributions to the part-based representation of the data. The second module is a stacked Bayesian autoencoder that projects the data onto a low-dimensional space (compressed). To diminish the tendency to overfit of neural networks, we repeatedly perturb the compressed space to learn a more generalized representation of the data. In an extensive analysis, we demonstrate that scDHA outperforms state-of-the-art techniques in many research sub-fields of scRNA-seq analysis, including cell segregation through unsupervised learning, visualization of transcriptome landscape, cell classification, and pseudo-time inference. Accurate analysis of single-cell RNA sequencing (scRNA-seq) data is affected by issues including technical noise and high dropout rate. Here, the authors develop a hierarchical autoencoder, scDHA, which outperforms existing methods in scRNA-seq analyses such as cell segregation and classification.

Rod and cone photoreceptors are light-sensing cells in the human retina. Rods are dominant in the peripheral retina, whereas cones are enriched in the macula, which is responsible for central vision and visual acuity. Macular degenerations affect vision the most and are currently incurable. Here we report the generation, transcriptome profiling, and functional validation of cone-rich human retinal organoids differentiated from hESCs using an improved retinal differentiation system. Induced by extracellular matrix, aggregates of hESCs formed single-lumen cysts composed of epithelial cells with anterior neuroectodermal/ectodermal fates, including retinal cell fate. Then, the cysts were en bloc-passaged, attached to culture surface, and grew, forming colonies in which retinal progenitor cell patches were found. Following gentle cell detachment, retinal progenitor cells self-assembled into retinal epithelium— retinal organoid—that differentiated into stratified cone-rich retinal tissue in agitated cultures. Electron microscopy revealed differentiating outer segments of photoreceptor cells. Bulk RNA-sequencing profiling of time-course retinal organoids demonstrated that retinal differentiation in vitro recapitulated in vivo retinogenesis in temporal expression of cell differentiation markers and retinal disease genes, as well as in mRNA alternative splicing. Single-cell RNA-sequencing profiling of 8-mo retinal organoids identified cone and rod cell clusters and confirmed the cone enrichment initially revealed by quantitative microscopy. Notably, cones from retinal organoids and human macula had similar single-cell transcriptomes, and so did rods. Cones in retinal organoids exhibited electrophysiological functions. Collectively, we have established cone-rich retinal organoids and a reference of transcriptomes that are valuable resources for retinal studies.

Key Points Classification of neurons into types enables their reproducible identification across times, laboratories and conditions. Classification also facilitates genetic access for functional studies, as well as analyses of development, evolution and disease. Neuronal cell types must be defined by multiple criteria related to their morphological, physiological, molecular and connectional properties. Past efforts at neuronal classification were hindered by severe biases and under-sampling, but newly developed high-throughput techniques allow this limitation to be circumvented. For some regions of the central nervous system, particularly the retina and cerebral cortex, a complete cell census appears within reach. Principles derived from the well-developed field of species taxonomy (systematics) provide common-sense guidelines for cell-type classification. Attempts to group the cells of the nervous system into classes or types face technical and conceptual barriers. Zeng and Sanes consider the current approaches to classification and propose a strategy and set of principles to guide future classification efforts. Neurons have diverse molecular, morphological, connectional and functional properties. We believe that the only realistic way to manage this complexity — and thereby pave the way for understanding the structure, function and development of brain circuits — is to group neurons into types, which can then be analysed systematically and reproducibly. However, neuronal classification has been challenging both technically and conceptually. New high-throughput methods have created opportunities to address the technical challenges associated with neuronal classification by collecting comprehensive information about individual cells. Nonetheless, conceptual difficulties persist. Borrowing from the field of species taxonomy, we propose principles to be followed in the cell-type classification effort, including the incorporation of multiple, quantitative features as criteria, the use of discontinuous variation to define types and the creation of a hierarchical system to represent relationships between cells. We review the progress of classifying cell types in the retina and cerebral cortex and propose a staged approach for moving forward with a systematic cell-type classification in the nervous system.

Single-wavelength fluorescent reporters allow visualization of specific neurotransmitters with high spatial and temporal resolution. We report variants of intensity-based glutamate-sensing fluorescent reporter (iGluSnFR) that are functionally brighter; detect submicromolar to millimolar amounts of glutamate; and have blue, cyan, green, or yellow emission profiles. These variants could be imaged in vivo in cases where original iGluSnFR was too dim, resolved glutamate transients in dendritic spines and axonal boutons, and allowed imaging at kilohertz rates.

Inhibition of histone deacetylation allows the transcription factor Ascl1 to bind to key gene loci in Müller glia and drive the functional generation of retinal neurons in adult mice. Retina regeneration in rodents Fish, birds and reptiles maintain the capacity to regenerate functional retinal neurons after injury, yet this form of regeneration does not occur in adult mammals. Humans can suffer from a significant number of diseases involving the loss of vision due to retinal disease and damage, so understanding why adult mammals lack this regenerative capacity is crucial. Here, Thomas Reh and colleagues express transcription factor Ascl1, previously known to enhance retinal neuron regeneration in fish, in Müller glia cells of rodents. Ascl1 was only able to drive functional generation of new retinal neurons in adult mice in conjunction with the inhibition of histone deacetylase (HDAC) inhibitors. The HDAC inhibitors enabled Ascl1 to bind at key gene loci in the Müller glia, allowing for the reprogramming of these cells to retinal neurons. Many retinal diseases lead to the loss of retinal neurons and cause visual impairment. The adult mammalian retina has little capacity for regeneration. By contrast, teleost fish functionally regenerate their retina following injury, and Müller glia (MG) are the source of regenerated neurons 1 , 2 , 3 , 4 , 5 , 6 . The proneural transcription factor Ascl1 is upregulated in MG after retinal damage 1 , 7 in zebrafish and is necessary for regeneration 8 . Although Ascl1 is not expressed in mammalian MG after injury 9 , forced expression of Ascl1 in mouse MG induces a neurogenic state in vitro 10 and in vivo after NMDA ( N -methyl- d -aspartate) damage in young mice 11 . However, by postnatal day 16, mouse MG lose neurogenic capacity, despite Ascl1 overexpression 11 . Loss of neurogenic capacity in mature MG is accompanied by reduced chromatin accessibility, suggesting that epigenetic factors limit regeneration. Here we show that MG-specific overexpression of Ascl1, together with a histone deacetylase inhibitor, enables adult mice to generate neurons from MG after retinal injury. The MG-derived neurons express markers of inner retinal neurons, synapse with host retinal neurons, and respond to light. Using an assay for transposase-accessible chromatin with high-throughput sequencing (ATAC–seq), we show that the histone deacetylase inhibitor promotes accessibility at key gene loci in the MG, and allows more effective reprogramming. Our results thus provide a new approach for the treatment of blinding retinal diseases.

Retinal structure and function have been studied in many vertebrate orders, but molecular characterization has been largely confined to mammals. We used single-cell RNA sequencing (scRNA-seq) to generate a cell atlas of the chick retina. We identified 136 cell types plus 14 positional or developmental intermediates distributed among the six classes conserved across vertebrates – photoreceptor, horizontal, bipolar, amacrine, retinal ganglion, and glial cells. To assess morphology of molecularly defined types, we adapted a method for CRISPR-based integration of reporters into selectively expressed genes. For Müller glia, we found that transcriptionally distinct cells were regionally localized along the anterior-posterior, dorsal-ventral, and central-peripheral retinal axes. We also identified immature photoreceptor, horizontal cell, and oligodendrocyte types that persist into late embryonic stages. Finally, we analyzed relationships among chick, mouse, and primate retinal cell classes and types. Our results provide a foundation for anatomical, physiological, evolutionary, and developmental studies of the avian visual system. The evolutionary relationships of organisms and of genes have long been studied in various ways, including genome sequencing. More recently, the evolutionary relationships among the different types of cells that perform distinct roles in an organism, have become a subject of inquiry. High throughput single-cell RNA sequencing is a technique that allows scientists to determine what genes are switched on in single cells. This technique makes it possible to catalogue the cell types that make up a tissue and generate an atlas of the tissue based on what genes are switched on in each cell. The atlases can then be compared among species. The retina is a light-sensitive tissue that animals with a backbone, called vertebrates, use to see. The basic plan of the retina is very similar in vertebrates: five classes of neurons – the cells that make up the nervous system – are arranged into three layers. The chicken is a highly visual animal and it has frequently been used to study the development of the retina, from understanding how unspecialized embryonic cells become neurons to examining how circuits of neurons form. The structure and role of the retina have been studied in many vertebrates, but detailed descriptions of this tissue at the molecular level have been largely limited to mammals. To bridge this gap, Yamagata, Yan and Sanes generated the first cell atlas of the chicken retina. Additionally, they developed a gene editing-based technique based on CRISPR technology called eCHIKIN to label different cell types based on genes each type switched on selectively, providing a means of matching their shape and location to their molecular identity. Using these methods, it was possible to subdivide each of the five classes of neurons in the retina into multiple distinct types for a total of 136. The atlas provided a foundation for evolutionary analysis of how retinas evolve to serve the very different visual needs of different species. The chicken cell types could be compared to types previously identified in similar studies of mouse and primate retinas. Comparing the relationships among retinal cells in chickens, mice and primates revealed strong similarities in the overall cell classes represented. However, the results also showed big differences among species in the specific types within each class, and the genes that were switched on within each cell type. These findings may provide a foundation to study the anatomy, physiology, evolution, and development of the avian visual system. Until now, neural development of the chicken retina was being studied without comprehensive knowledge of its cell types or the developmentally important genes they express. The system developed by Yamagata, Yan and Sanes may be used in the future to learn more about vision and to investigate how neural cell types evolve to match the repertoire of each species to its environment.