Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Single cell-based analysis of human trabecular meshwork tissue provides a comprehensive cellular and molecular classification, identifying cell-type and region-specific expression of genes
Author Affiliations & Notes
  • Gaurang Patel
    Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States
  • Wen Fury
    Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States
  • Hua Yang
    Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States
  • Ying Hu
    Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States
  • Daniel Stamer
    Duke University, Durham, North Carolina, United States
  • Carl Romano
    Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States
  • Footnotes
    Commercial Relationships   Gaurang Patel, Regeneron Pharmaceuticals, Inc (E); Wen Fury, Regeneron Pharmaceuticals, Inc (E); Hua Yang, Regeneron Pharmaceuticals, Inc (E); Ying Hu, Regeneron Pharmaceuticals, Inc (E); Daniel Stamer, Regeneron Pharmaceuticals, Inc (C); Carl Romano, Regeneron Pharmaceuticals, Inc (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 2329. doi:
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      Gaurang Patel, Wen Fury, Hua Yang, Ying Hu, Daniel Stamer, Carl Romano; Single cell-based analysis of human trabecular meshwork tissue provides a comprehensive cellular and molecular classification, identifying cell-type and region-specific expression of genes. Invest. Ophthalmol. Vis. Sci. 2020;61(7):2329.

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

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Abstract

Purpose : Human Trabecular meshwork (TM) tissue is architecturally complex and TM cells display different morphologies based on their location, cell behavior, and function. Significant impact of TM cells in outflow and IOP regulation makes it an amenable target for gene therapy and editing. However, unknown are unique molecular identities or markers of each TM cell subtype, and how many distinct cell types populate the TM tissue. The purpose of this study was to identify cell types in the TM by generating gene expression profiles. We also aimed to examine the expression pattern of glaucoma-associated genes from human donor eyes by single cell RNAseq

Methods : Human TM tissue was dissected via blunt dissection approach from 8 human donor eyes obtained from 4 individuals (aged 55-85). TM single cells obtained after collagenase digestion were loaded on a Single Cell Instrument (10X Genomics). After sequencing, data analyses were performed using Seurat 2.3 software. We also performed in situ hybridization using RNAscope on human eye tissue sections to identify the location of the some of the major cell types identified in TM

Results : After rigorous QC, data filtering, we obtained 17757 genes, 8758 cells. Upon clustering analysis, TM preparations resolved into 12 distinct cell type clusters (tSNE plot). These were characterized as Schwann like scleral spur cells, fibroblast like (TM1 cells), myofibroblast like (TM2 cells), smooth muscle cell, lymphatic- vascular endothelium cell (Schlemm’s canal), macrophages, pericyte, epithelium, melanocyte, and T/NK cell. We identified genes that are specific to each cluster. We also observed high expression level of glaucoma associated genes like MYOC and ANGPTL7 in some clusters. Finally, RNAscope localized cell type-specific genes to different regions of TM. This indicated that only a few of the bioinformatically identified cell types are found in the anatomically defined TM, others reflect cells from neighboring tissues.

Conclusions : With sc-RNAseq, we have identified 12 distinct cell types in and around human TM. Our findings deepen our understanding of TM cell biology. This new information will be useful for identifying TM cells in vitro, for designing TM cell specific promoters, and allow us to study how different cell types in TM are regulated during health and disease

This is a 2020 ARVO Annual Meeting abstract.

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