CELL_BROWSER

snATAC-seq of human retina

Integrated multi-omics single cell atlas of the human retina

Evolution of neuronal cell classes and types in the vertebrate retina

CZ_CELLXGENE

snRNA-seq of human retina - all cells

scRNA-seq of human retina - all cells

snRNA-seq of human retina - bipolar cell subset

snRNA-seq of human retina - retinal ganglion cell subset

snRNA-seq of human retina - amacrine cell subset

scRNA-seq of human retina - bipolar cell subclass

Single-cell atlas of the human retina v1.0

Eye Network

Eye Network - Overview

The gene expression program underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of gene expression and chromatin accessibility in fetal tissues. For gene expression, we applied three-level combinatorial indexing to >110 samples representing 15 organs, ultimately profiling ~4 million single cells. We leveraged the literature and other atlases to identify and annotate hundreds of cell types and subtypes, both within and across tissues. Our analyses focused on organ-specific specializations of broadly distributed cell types (such as blood, endothelial, and epithelial), sites of fetal erythropoiesis (which notably included the adrenal gland), and integration with mouse developmental atlases (such as conserved specification of blood cells). These data represent a rich resource for the exploration of in vivo human gene expression in diverse tissues and cell types.

A human cell atlas of fetal gene expression.

Cell types in the human retina is highly heterogeneous with their abundance varies by several orders of magnitude. To decipher the complexity of gene expression and regulation of the human retinal cell types, we generated a multi-omics single-cell atlas of the adult human retina, including over 250K nuclei for single-nuclei RNA-seq and 150K nuclei for single-nuclei ATAC-seq. Over 60 cell subtypes have been identified based on their transcriptomic profiles, reaching a sensitivity of 0.01%. Integrative analysis of this single-cell multi-omics dataset identified gene regulatory elements across the genome for each cell subtype. In addition, when combined with other data modalities, such as eQTL, potential causal variants can be identified through fine mapping. Taken together, this new dataset represents the most comprehensive single-cell multi-omics profiling for the human retina that enables in-depth molecular characterization of most cell subtypes.

A multi-omics atlas of the human retina at single-cell resolution

To study the development and composition of human ocular surface, the authors performed single cell (sc) RNA-Seq at key embryonic, fetal and adult stages and generated the first atlas of the corneal and conjunctival cell types from development to adulthood.

A single cell atlas of human cornea that defines its development, limbal progenitor cells and their interactions with the immune cells.

The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single‐cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post‐mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell‐derived cone photoreceptors and an adult Müller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.

A single-cell transcriptome atlas of the adult human retina

The ciliary body is required for the maintenance of intraocular pressure and immunity as well as vision accommodation. We report a comprehensive cell atlas of human ciliary body from single-cell RNA sequencing (scRNAseq) Overall design: Ciliary body tissues from human donor eyes were dissected and dissociated to yeild single cell suspension. ScRNAseq was performed using a BD Rhapsody system, followed by analyses of cell clusters, specific gene expression profiling and ligand-receptor pairs

A single-cell transcriptomic atlas of the human ciliary body

Most irreversible blindness results from retinal disease. To advance our understanding of the etiology of blinding diseases, we used single-cell RNA-sequencing (scRNA-seq) to analyze the transcriptomes of ~85,000 cells from the fovea and peripheral retina of seven adult human donors. Utilizing computational methods, we identified 58 cell types within 6 classes: photoreceptor, horizontal, bipolar, amacrine, retinal ganglion and non-neuronal cells. Nearly all types are shared between the two retinal regions, but there are notable differences in gene expression and proportions between foveal and peripheral cohorts of shared types. We then used the human retinal atlas to map expression of 636 genes implicated as causes of or risk factors for blinding diseases. Many are expressed in striking cell class-, type-, or region-specific patterns. Finally, we compared gene expression signatures of cell types between human and the cynomolgus macaque monkey, Macaca fascicularis. We show that over 90% of human types correspond transcriptomically to those previously identified in macaque, and that expression of disease-related genes is largely conserved between the two species. These results validate the use of the macaque for modeling blinding disease, and provide a foundation for investigating molecular mechanisms underlying visual processing.

Cell Atlas of The Human Fovea and Peripheral Retina.

Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable "developed" state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.

Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution

The anterior segment of the eye consists of the cornea, iris, ciliary body, crystalline lens, and aqueous humor outflow pathways. Together, these tissues are essential for the proper functioning of the eye. Disorders of vision have been ascribed to defects in all of them; some disorders, including glaucoma and cataract, are among the most prevalent causes of blindness in the world. To characterize the cell types that compose these tissues, we generated an anterior segment cell atlas of the human eye using high-throughput single-nucleus RNA sequencing (snRNAseq). We profiled 195,248 nuclei from nondiseased anterior segment tissues of six human donors, identifying >60 cell types. Many of these cell types were discrete, whereas others, especially in the lens and cornea, formed continua corresponding to known developmental transitions that persist in adulthood. Having profiled each tissue separately, we performed an integrated analysis of the entire anterior segment, revealing that some cell types are unique to a single structure, whereas others are shared across tissues. The integrated cell atlas was then used to investigate cell type-specific expression patterns of more than 900 human ocular disease genes identified through either Mendelian inheritance patterns or genome-wide association studies.

Cell atlas of the human ocular anterior segment: Tissue-specific and shared cell types

Cis-regulatory elements (CREs) play a critical role in the development and disease-states of all human cell types. In the retina, CREs have been implicated in several inherited disorders. To better characterize human retinal CREs, we performed single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq) and single-nucleus RNA sequencing (snRNA-seq) on the developing and adult human retina and on induced pluripotent stem cell (iPSC)-derived retinal organoids. These analyses identified developmentally dynamic, cell-class-specific CREs, enriched transcription-factor-binding motifs, and putative target genes. CREs in the retina and organoids are highly correlated at the single-cell level, and this supports the use of organoids as a model for studying disease-associated CREs. As a proof of concept, we disrupted a disease-associated CRE at 5q14.3, confirming its principal target gene as the miR-9-2 primary transcript and demonstrating its role in neurogenesis and gene regulation in mature glia. This study provides a resource for characterizing human retinal CREs and showcases organoids as a model to study the function of CREs that influence development and disease.

Cell-specific cis-regulatory elements and mechanisms of non-coding genetic disease in human retina and retinal organoids

Single-cell RNA sequencing was used to determine the cell type composition of all major human organs and construct a basic scheme for the human cell landscape (HCL).

Construction of A Human Cell Landscape by Single-cell mRNA-seq

Background: Retinoblastoma (Rb) is a malignant neoplasm arising during retinal development from mutations in the RB1 gene. Loss or inactivation of both copies of RB1 results in initiation of retinoblastoma tumours, however additional genetic changes are needed for the continued growth and spread of the tumour. Ex vivo research has shown that in humans, retinoblastoma may initiate from Rb depleted cone precursors. Notwithstanding, it has not been possible to assess the full spectrum of clonal types within the tumour itself in vivo and the molecular changes occurring at the cells of origin, enabling their malignant conversion. To overcome these challenges, we have performed the first single cell (sc) RNA- and ATAC-Seq analyses of primary tumour tissues, enabling us to dissect the transcriptional and chromatin accessibility heterogeneity of proliferating cone precursors in human Rb tumours. Methods: Two Rb tumours each characterised by two pathogenic RB1 mutations were dissociated to single cells and subjected to scRNA-Seq & scATAC-Seq using the 10x Genomics platform. In addition, nine embryonic and fetal retina samples were dissociated to single cells and subjected to scRNA- and ATAC-Seq analyses. The scRNA- and ATAC-Seq data were embedded using Uniform Manifold Approximation and Projection (UMAP) and clustered using Seurat graph based-clustering. Integrated scATAC-Seq analysis of Rb tumours and human embryonic/fetal retina samples was performed to identify Rb cone enriched subsets. Pseudotime analysis of proliferating cones in the Rb samples was performed with Monocle. Ingenuity Pathway Analysis (IPA) was used to identify the signalling pathway and upstream regulators in the Rb cone enriched subclusters. Results: Our single cell analyses revealed the predominant presence of cone precursors at different stages of the cell cycle in the Rb tumours and amongst those identified the G2/M subset as the cell type of origin. scATAC-Seq analysis identified two Rb enriched cone subsets, each characterised by activation of different upstream regulators and signalling pathways, leading proliferating cone precursors to escape cell cycle arrest and/or apoptosis. Conclusions: Our study provides evidence of Rb tumor heterogeneity and defines molecular pathways that can be targeted to define new treatment strategies Overall design: Two Rb tumours each characterised by two pathogenic RB1 mutations were dissociated to single cells and subjected to scRNA-Seq & scATAC-Seq using the 10x Genomics platform. In addition, nine embryonic and fetal retina samples were dissociated to single cells and subjected to scRNA-seq.

Dissecting transcriptional and chromatin accessibility heterogeneity of proliferating cone precursors in human retinoblastoma tumours by single cell sequencing

The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs. Retinal cell types may have evolved to accommodate these varied needs, but this has not been systematically studied. Here we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a bird, a reptile, a teleost fish and a lamprey. We found high molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells (RGCs) and Müller glia), with transcriptomic variation across species related to evolutionary distance. Major subclasses were also conserved, whereas variation among cell types within classes or subclasses was more pronounced. However, an integrative analysis revealed that numerous cell types are shared across species, based on conserved gene expression programmes that are likely to trace back to an early ancestral vertebrate. The degree of variation among cell types increased from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified rodent orthologues of midget RGCs, which comprise more than 80% of RGCs in the human retina, subserve high-acuity vision, and were previously believed to be restricted to primates. By contrast, the mouse orthologues have large receptive fields and comprise around 2% of mouse RGCs. Projections of both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but are descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.

Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution.

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

mRNA profiles for thousands of cells from foveal and parafoveal retina were generated from four human donor eyes (single-cell donors 5-8) using 10X Genomics Chromium single-cell system followed by sequencing on an Illumina NovaSeq.

Human photoreceptor cells from different macular subregions have distinct transcriptional profiles

Age-related macular degeneration (AMD) is a leading cause of vision loss. To better understand disease pathogenesis and identify causal genes in GWAS loci for AMD risk, we present a comprehensive database of human retina and retinal pigment epithelium (RPE). Our database comprises macular and non-macular RNA sequencing (RNA-seq) profiles from 129 donors, a genome-wide expression quantitative trait loci (eQTL) dataset that includes macula-specific retina and RPE/choroid, and single-nucleus RNA-seq (NucSeq) from human retina and RPE with subtype resolution from more than 100,000 cells. Using NucSeq, we find enriched expression of AMD candidate genes in RPE cells. We identify 15 putative causal genes for AMD on the basis of co-localization of genetic association signals for AMD risk and eye eQTL, including the genes TSPAN10 and TRPM1. These results demonstrate the value of our human eye database for elucidating genetic pathways and potential therapeutic targets for ocular diseases.

Integration of eQTL and a Single-Cell Atlas in the Human Eye Identifies Causal Genes for Age-Related Macular Degeneration

Purpose: Single-cell RNA sequencing has revolutionized cell-type specific gene expression analysis. The goals of this study are to compare cell specific gene expression patterns between retinal cell types originating from the fovea and the periphery of human eyes.,Methods: Independent libraries were prepared for foveal and peripheral samples of neural retina from three donors using the 10x Chromium system. Libraries were sequenced on a HiSeq4000. Sequenced reads were mapped to the human genome build hg19 will CellRanger(v3.0.1) and filters removed cells likely to be doublets or cells with a high proportion of mitochondrial reads. Clustering of cells with similar expression profiles was performed with Seurat (v2.3.4).,Results: Independent libraries were prepared for foveal and peripheral samples of neural retina from three donors using the 10x Chromium system. Libraries were sequenced on a HiSeq4000. Sequenced reads were mapped to the human genome build hg19 will CellRanger(v3.0.1) and filters removed cells likely to be doublets or cells with a high proportion of mitochondrial reads. Clustering of cells with similar expression profiles was performed with Seurat (v2.3.4).,"Conclusions: Our study generates a large atlas of human retinal transcriptomes at the single cell level. We identified the majority of expected neural and supportive cell types, and describe regional differences in gene expression between the fovea and the periphery. Our results show that that single-cell RNA sequencing can be performed on human retina after cryopreservation, and that cone photoreceptors and Muller cells demonstrate region-specific patterns of gene expression."

Molecular characterization of foveal versus peripheral human retina by single-cell RNA sequencing

As the light-sensing part of the visual system, the retina is comprised of five classes of neurons, including photoreceptors, horizontal, amacrine, bipolar, and retinal ganglion cells, along with several non-neuronal cell types such as Muller glia. These major cell classes can be further classified into hundreds of distinct cell subtypes. The development of the retina is under tight temporal control where multipotent progenitor cells differentiate into specific mature cell types in a sequential, but overlapping, order. Additionally, the developmental process is under tight spatial control, with cells at the central retina developing earlier than cells at the periphery. To provide a comprehensive view of the human fetal retina at the molecular level and investigate transcriptional regulatory mechanisms controlling the differentiation process, we profiled more than 300,000 single nuclei of the human fetal retina from 12 donors spanning post conception week 10 and 23 with Multiome RNA-seq and ATAC-seq.

Single Cell Multiome Atlas of the Human Fetal Retina

As the light sensing part of the visual system, the human retina is composed of five classes of neuron, including photoreceptors, horizontal cells, amacrine, bipolar, and retinal ganglion cells. Each class of neuron can be further classified into subgroups with the abundance varying three orders of magnitude. Therefore, to capture all cell types in the retina and generate a complete single cell reference atlas, it is essential to scale up from currently published single cell profiling studies to improve the sensitivity. In addition, to gain a better understanding of gene regulation at single cell level, it is important to include sufficient scATAC-seq data in the reference. To fill the gap, we performed snRNA-seq and snATAC-seq for the retina from healthy donors. To further increase the size of the dataset, we then collected and incorporated publicly available datasets. All data underwent a unified preprocessing pipeline and data integration. Multiple integration methods were benchmarked by scIB, and scVI was chosen. To harness the power of multiomics, snATAC-seq datasets were also preprocessed, and scGlue was used to generate co-embeddings between snRNA-seq and snATAC-seq cells. To facilitate the public use of references, we employ CELLxGENE and UCSC Cell Browser for visualization. By combining previously published and newly generated datasets, a single cell atlas of the human retina that is composed of 2.5 million single cells from 48 donors has been generated. As a result, over 90 distinct cell types are identified based on the transcriptomics profile with the rarest cell type accounting for about 0.01% of the cell population. In addition, open chromatin profiling has been generated for over 400K nuclei via single nuclei ATAC-seq, allowing systematic characterization of cis-regulatory elements for individual cell type. Integrative analysis reveals intriguing differences in the transcriptome, chromatin landscape, and gene regulatory network among cell class, subgroup, and type. In addition, changes in cell proportion, gene expression and chromatin openness have been observed between different gender and over age. Accessible through interactive browsers, this study represents the most comprehensive reference cell atlas of the human retina to date. As part of the human cell atlas project, this resource lays the foundation for further research in understanding retina biology and diseases.

Single cell atlas of the human retina

Endothelial cell (EC) metabolism is an emerging target for anti-angiogenic therapy in tumor angiogenesis and choroidal neovascularization (CNV), but little is known about individual EC metabolic transcriptomes. By single-cell RNA sequencing 28,337 murine choroidal ECs (CECs) and sprouting CNV-ECs, we constructed a taxonomy to characterize their heterogeneity. Comparison with murine lung tumor ECs (TECs) revealed congruent marker gene expression by distinct EC phenotypes across tissues and diseases, suggesting similar angiogenic mechanisms. Trajectory inference predicted that differentiation of venous to angiogenic ECs was accompanied by metabolic transcriptome plasticity. ECs displayed metabolic transcriptome heterogeneity during cell-cycle progression and in quiescence. Hypothesizing that conserved genes are important, we used an integrated analysis, based on congruent transcriptome analysis, CEC-tailored genome-scale metabolic modeling, and gene expression meta-analysis in cross-species datasets, followed by in vitro and in vivo validation, to identify SQLE and ALDH18A1 as previously unknown metabolic angiogenic targets.

Single-Cell RNA Sequencing Maps Endothelial Metabolic Plasticity in Pathological Angiogenesis.

The human cortex comprises diverse cell types that emerge from an initially uniform neuroepithelium that gives rise to radial glia, the neural stem cells of the cortex. To characterize the earliest stages of human brain development, we performed single-cell RNA-sequencing across regions of the developing human brain, including the telencephalon, diencephalon, midbrain, hindbrain and cerebellum. We identify nine progenitor populations physically proximal to the telencephalon, suggesting more heterogeneity than previously described, including a highly prevalent mesenchymal-like population that disappears once neurogenesis begins. Comparison of human and mouse progenitor populations at corresponding stages identifies two progenitor clusters that are enriched in the early stages of human cortical development. We also find that organoid systems display low fidelity to neuroepithelial and early radial glia cell types, but improve as neurogenesis progresses. Overall, we provide a comprehensive molecular and spatial atlas of early stages of human brain and cortical development.

Single-cell atlas of early human brain development highlights heterogeneity of human neuroepithelial cells and early radial glia.

Genome-wide association studies (GWASs) of eye disorders have identified hundreds of genetic variants associated with ocular disease. However, the vast majority of these variants are noncoding, making it challenging to interpret their function. Here we present a joint single-cell atlas of gene expression and chromatin accessibility of the adult human retina with more than 50,000 cells, which we used to analyze single-nucleotide polymorphisms (SNPs) implicated by GWASs of age-related macular degeneration, glaucoma, diabetic retinopathy, myopia, and type 2 macular telangiectasia. We integrate this atlas with a HiChIP enhancer connectome, expression quantitative trait loci (eQTL) data, and base-resolution deep learning models to predict noncoding SNPs with causal roles in eye disease, assess SNP impact on transcription factor binding, and define their known and novel target genes. Our efforts nominate pathogenic SNP-target gene interactions for multiple vision disorders and provide a potentially powerful resource for interpreting noncoding variation in the eye.

Single-cell multiome of the human retina and deep learning nominate causal variants in complex eye diseases

Systematic characterization of how genetic variation modulates gene regulation in a cell type specific context is essential for understanding complex traits. To address this question, we profiled gene expression and chromatin state of cells from healthy retinae of 20 human donors with a single-cell multiomics approach, and performed genomic sequencing. sc-eQTLs, sc-caQTL, sc-ASCA and sc-ASE were mapped in major retinal cell types. By integrating these results, we identified and characterized regulatory elements and genetic variants effective on gene regulation in individual cell types. Most of the identified sc-eQTLs and sc-caQTLs exhibit cell type-specific effects. Interestingly, the cis-elements harboring genetic variants with cell type-specific effects tend to be accessible in multiple cell types. Lastly, we identified the enriched cell types, fine-mapped candidate causal variants and genes, and uncovered cell type-specific regulatory mechanism underlying GWAS loci.

Single-cell multiomics of the human retina reveals hierarchical transcription factor collaboration in mediating cell type-specific effects of genetic variants on gene regulation

Genome-wide association studies (GWAS) have identified genetic variants associated with age-related macular degeneration (AMD), one of the leading causes of blindness in the elderly. However, it has been challenging to identify the cell types associated with AMD given the genetic complexity of the disease. Here we perform massively parallel single-cell RNA sequencing (scRNA-seq) of human retinas using two independent platforms, and report the first single-cell transcriptomic atlas of the human retina. Using a multi-resolution network-based analysis, we identify all major retinal cell types, and their corresponding gene expression signatures. Heterogeneity is observed within macroglia, suggesting that human retinal glia are more diverse than previously thought. Finally, GWAS-based enrichment analysis identifies glia, vascular cells, and cone photoreceptors to be associated with the risk of AMD. These data provide a detailed analysis of the human retina, and show how scRNA-seq can provide insight into cell types involved in complex, inflammatory genetic diseases.

Single-cell transcriptomic atlas of the human retina identifies cell types associated with age-related macular degeneration

The goals of this study were to identify cell specific expression patterns of the retinal pigment epithelium (RPE) and a variety of choroidal cell types originating from the macula and the periphery of human donor eyes, with a particular emphasis on identifying expression signatures of choroidal endothelial cells.

Single-cell transcriptomics of the human retinal pigment epithelium and choroid in health and macular degeneration

Limbal stem cells (LSCs), known as corneal epithelial stem cells, are located at the basal epithelial layer of the corneal limbus and serve an important function in maintaining the homeostasis of the corneal epithelium. The specificity of LSC markers remains largely controversial. To address the gap in the current understanding of LSCs, the authors performed transcriptome profiling of heterogeneous corneal limbal basal cells using single-cell transcriptomics technology to identify LSCs and their exclusive markers. Single-cell transcriptomic profiles were generated from isolated limbal basal cells from two young human donors.

Single-cell transcriptomics uncovers human corneal limbal stem cells and their differentiation trajectory.

Retinoblastoma (RB) represents one of the most prevalent intraocular cancers in children. Understanding the tumor heterogeneity in RB is important to design better targeted therapies. Here we used spatial transcriptomic to profile human retina and RB tumor to comprehensively dissect the spatial cell-cell communication networks. We found high intratumoral heterogeneity in RB, consisting of 10 transcriptionally distinct subpopulations with varying levels of proliferation capacity. Our results uncovered a complex architecture of the tumor microenvironment that predominantly consisted of cone precursors, as well as glial cells and cancer-associated fibroblasts. We delineated the cell trajectory underlying malignant progression of RB, and identified key signaling pathways driving genetic regulation across RB progression. We also explored the signaling pathways mediating cell-cell communications in RB subpopulations, and mapped the spatial networks of RB subpopulations and region neighbors. Altogether, we constructed the first spatial gene atlas for RB, which allowed us to characterize the transcriptomic landscape in spatially-resolved RB subpopulations, providing novel insights into the complex spatial communications involved in RB progression.

Spatial transcriptomic profiling of human retinoblastoma

In recent years there has been tremendous progress towards deep molecular characterization of cell types using single cell transcriptome sequencing. Here we report a single cell transcriptomic atlas comprising nearly 500,000 cells from 24 different human tissues and organs. In several instances multiple organs were analyzed from the same donor. Analyzing organs from the same individual controls for genetic background, age, environment, and epigenetic effects, and enables a detailed comparison of cell types that are shared between tissues. This resource provides a rich molecular characterization of more than 400 cell types, their distribution across tissues, and detailed information about tissue specific variation in gene expression. We have used the fact that multiple tissues came from the same donor to study the clonal distribution of T cells between tissues, to understand the tissue specific mutation rate in B cells, and to analyze the cell cycle state and proliferative potential of shared cell types across tissues. Finally, we have also used this data to characterize cell type specific RNA splicing and how such splicing varies across tissues within an individual.

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans

Although the visual system extends through the brain, most vision loss originates from defects in the eye. Its central element is the neural retina, which senses light, processes visual signals, and transmits them to the rest of the brain through the optic nerve (ON). Surrounding the retina are numerous other structures, conventionally divided into anterior and posterior segments. Here, we used high-throughput single-nucleus RNA sequencing (snRNA-seq) to classify and characterize cells in six extraretinal components of the posterior segment: ON, optic nerve head (ONH), peripheral sclera, peripapillary sclera (PPS), choroid, and retinal pigment epithelium (RPE). Defects in each of these tissues are associated with blinding diseases—for example, glaucoma (ONH and PPS), optic neuritis (ON), retinitis pigmentosa (RPE), and age-related macular degeneration (RPE and choroid). From ~151,000 single nuclei, we identified 37 transcriptomically distinct cell types, including multiple types of astrocytes, oligodendrocytes, fibroblasts, and vascular endothelial cells. Our analyses revealed a differential distribution of many cell types among distinct structures. Together with our previous analyses of the anterior segment and retina, the data presented here complete a “Version 1” cell atlas of the human eye. We used this atlas to map the expression of >180 genes associated with the risk of developing glaucoma, which is known to involve ocular tissues in both anterior and posterior segments as well as the neural retina. Similar methods can be used to investigate numerous additional ocular diseases, many of which are currently untreatable.

Eye Network

Network Description

Network Coordinators