Cell atlas of the human fovea and peripheral retina
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA623011 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR11478908.fastq.gz | Fastqsanger.gz | |||
| SRR11478910.fastq.gz | Fastqsanger.gz | |||
| SRR11478923.fastq.gz | Fastqsanger.gz |
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Project description:This SuperSeries is composed of the SubSeries listed below. 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.
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Project description: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 reti-na of seven adult human donors. Utilizing computational methods, we identified 58 cell types within 6 classes: photoreceptor, horizontal, bipolar, amacrine, retinal gangli-on and non-neuronal cells. Nearly all types are shared between the two retinal re-gions, 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 dis-eases. Many are expressed in striking cell class-, type-, or region-specific patterns. Fi-nally, 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 pro-vide a foundation for investigating molecular mechanisms underlying visual pro-cessing.
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Project description:Cell types in the human retina are 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.
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Project description: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.
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Project description:The human neural retina is enriched for alternative splicing, and it is estimated that more than 10% of variants associated with inherited retinal diseases (IRDs) alter splicing. Previous research mainly used short-read RNA-sequencing techniques to investigate retina-specific splicing and splicing factors. However, this technique provides limited information about transcript isoforms. To gain a deeper understanding of the human neural retina and its isoforms, we generated a proteogenomic atlas that combined PacBio long-read RNA-sequencing data with mass-spectrometry and whole-genome sequencing data from three healthy human neural retina samples. RNA-sequencing revealed that one-third of all transcripts were novel, and for IRD-associated genes, even 43% were novel. The most common novel elements of these transcripts were alternative poly(A) sites, exon elongation, and intron retention. Some novel elements affect the non-coding region but for more than 50% of the novel transcripts a novel open reading frame was predicted. Using proteomics, ten novel peptides confirmed novel isoforms in five genes. Additionally, we found novel isoforms of IMPDH1, an IRD-associated gene, with supporting peptide evidence. This study provides a comprehensive overview of the transcript and protein isoforms expressed in the healthy human neural retina. Moreover, it highlights the importance of studying tissue specific transcriptomes in greater detail to better understand tissue-specific regulation and to identify disease-causing variants.
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