Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties

Mol Vis. 2020 Nov 27:26:766-779. eCollection 2020.

Abstract

Purpose: To better characterize retinal endothelial barrier properties through analysis of individual transcriptomes of primary bovine retinal microvascular endothelial cells (RMECs).

Methods: Individual RMECs were captured on the Fluidigm C1 system, cDNA libraries were prepared using a Nextera XT kit, and sequencing was performed on a NextSeq system (Illumina). Data analysis was performed using R packages Scater, SC3, and Seurat, and the browser application Automated Single-cell Analysis Pipeline (ASAP). Alternative splicing events in single cells were quantified with Outrigger. Cytoscape was used for network analyses.

Results: Application of a single-cell RNA sequencing (scRNA-seq) analysis workflow showed that RMECs form a relatively homogeneous population in culture, with the main differences related to proliferation status. Expression of markers from along the arteriovenous tree suggested that most cells originated from capillaries. Average gene expression levels across all cells were used to develop an in silico model of the inner blood-retina barrier incorporating junctional proteins not previously reported within the retinal vasculature. Correlation of barrier gene expression among individual cells revealed a subgroup of genes highly correlated with PECAM-1 at the center of the correlation network. Numerous alternative splicing events involving exons within microvascular barrier genes were observed, and in many cases, individual cells expressed one isoform exclusively.

Conclusions: We optimized a workflow for single-cell transcriptomics in primary RMECs. The results provide fundamental insights into the genes involved in formation of the retinal-microvascular barrier.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alternative Splicing / genetics
  • Animals
  • Biomarkers / metabolism
  • Blood-Retinal Barrier / metabolism*
  • Cattle
  • Computer Simulation
  • Endothelial Cells / metabolism*
  • Gene Expression Profiling*
  • Models, Biological
  • Reproducibility of Results
  • Single-Cell Analysis*

Substances

  • Biomarkers