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

snRNA-seq of human retina - bipolar cell subset

snRNA-seq of human retina - amacrine cell subset

snRNA-seq of human retina - retinal ganglion cell subset

scRNA-seq of human retina - all cells

scRNA-seq of human retina - bipolar cell subclass

Single-cell atlas of the human retina v1.0

Eye Network

Single-cell atlas of the human retina v1.0 - Overview

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

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

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

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

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

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.

Atlas Name	Tissue	Disease	Cells	Explore
snRNA-seq of human retina - all cells	4 tissues	normal	3.2M	CZ CELLxGENE
snRNA-seq of human retina - bipolar cell subset	4 tissues	normal	691.0k	CZ CELLxGENE
snRNA-seq of human retina - amacrine cell subset	4 tissues	normal	571.6k	CZ CELLxGENE
snRNA-seq of human retina - retinal ganglion cell subset	4 tissues	normal	399.6k	CZ CELLxGENE
scRNA-seq of human retina - all cells	5 tissues	normal	265.8k	CZ CELLxGENE
scRNA-seq of human retina - bipolar cell subclass	5 tissues	normal	72.8k	CZ CELLxGENE
snATAC-seq of human retina	--	normal	354.8k	UCSC Cell Browser

Single-cell atlas of the human retina v1.0

Atlas Description

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Overview

HCA Biological Network Atlases

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CZ CELLxGENE Collection

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