June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Single cell atlas of the human retina
Author Affiliations & Notes
  • Jin Li
    Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
    Human Genomics Sequencing Center, Baylor College of Medicine, Houston, Texas, United States
  • Jun Wang
    Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
    Human Genomics Sequencing Center, Baylor College of Medicine, Houston, Texas, United States
  • Xuesen Cheng
    Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
    Human Genomics Sequencing Center, Baylor College of Medicine, Houston, Texas, United States
  • Ignacio Ibarra
    Institute of Computational Biology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Neuherberg, Germany
  • Malte Luecken
    Institute of Computational Biology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Neuherberg, Germany
  • Qingnan Liang
    Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
  • Fabian Theis
    Institute of Computational Biology, Helmholtz Zentrum Munchen, German Research Center for Environmental Health, Neuherberg, Neuherberg, Germany
  • Margaret M DeAngelis
    Department of Ophthalmology, Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York, United States
  • Yumei Li
    Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
    Human Genomics Sequencing Center, Baylor College of Medicine, Houston, Texas, United States
  • Rui Chen
    Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, United States
    Human Genomics Sequencing Center, Baylor College of Medicine, Houston, Texas, United States
  • Footnotes
    Commercial Relationships   Jin Li None; Jun Wang None; Xuesen Cheng None; Ignacio Ibarra None; Malte Luecken None; Qingnan Liang None; Fabian Theis None; Margaret DeAngelis None; Yumei Li None; Rui Chen None
  • Footnotes
    Support  CZF2019-002425, CZF2021-237885, CZF2021-1239847
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 3268. doi:
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    • Get Citation

      Jin Li, Jun Wang, Xuesen Cheng, Ignacio Ibarra, Malte Luecken, Qingnan Liang, Fabian Theis, Margaret M DeAngelis, Yumei Li, Rui Chen; Single cell atlas of the human retina. Invest. Ophthalmol. Vis. Sci. 2023;64(8):3268.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : 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.

Methods : 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 employed CELLxGENE for visualization and cell annotation.

Results : 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.

Conclusions : 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.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

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