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RETINA Publication-derived

Deconstructing Retinal Organoids: Single Cell RNA-Seq Analysis of Human Pluripotent Stem Cell-Derived Retina

Source Collin et al., 2018 · Newcastle University, Institute of Genetic Medicine · 10.1002/stem.2963

👤 Joseph Collin, Rachel Queen, Darin Zerti, Birthe Dorgau, Rafiqul Hussain, Jonathan Coxhead, Simon Cockell, Majlinda Lako ⏱ 200 days 📋 6 phases 🧫 Human ESC (H9 line)

Abstract

This protocol describes the generation and single cell RNA-sequencing (scRNA-Seq) analysis of retinal organoids derived from human embryonic stem cells (hESCs) at three differentiation time points (days 60, 90, and 200). The method uses high-throughput Integrated Fluidic Circuits (IFC) to partition organoid cells into single cells for mRNA-Seq, enabling unbiased identification and temporal tracking of retinal cell types including photoreceptors, retinal pigment epithelium, retinal ganglion cells, and Müller glia.

Cell source
Human ESC (H9 line)
Application
Characterization and cell type identification of retinal organoids via single cell RNA sequencing

Protocol overview

22 steps across 6 phases

Retinal Organoid Differentiation Day 0–200
  1. 1 Culture and differentiate hESC (H9 line) to retinal organoids
  2. 2 Collect organoid samples at specified time points
Single Cell Dissociation and Partitioning Day of sample collection
  1. 3 Dissociate organoids into single cell suspension
  2. 4 Load cells onto the integrated fluidic circuit designated Fluidigm C1 Single-Cell mRNA-Seq HT for single-cell partitioning. Use this IFC to separate the cell suspension into individual cells.
Single Cell mRNA Library Preparation and Sequencing Same day as cell partitioning
  1. 5 Process partitioned cells for scRNA-Seq
  2. 6 Quality control and filtering of sequencing data
  3. 7 Normalize scRNA-Seq data
Cell Type Clustering and Identification Post-sequencing analysis
  1. 8 Merge data from all time points using Seurat
  2. 9 Identify cell clusters using Seurat findCluster function
  3. 10 Identify marker genes for each cluster
  4. 11 Assign cell types to clusters based on marker gene expression
Temporal Analysis of Cell Type Emergence Post-sequencing analysis
  1. 12 Perform individual clustering analysis for each time point
  2. 13 Compare individual time point clusters to combined dataset clusters
  3. 14 Quantify cell type proportion changes over differentiation
  4. 15 Perform pseudo-time analysis using Monocle
  5. 16 Interpret pseudo-time trajectory and cell ordering
Validation by Immunohistochemistry Parallel to or post scRNA-Seq analysis
  1. 17 Perform immunohistochemical staining of retinal organoid sections
  2. 18 Stain for proliferation and mitotic cell markers
  3. 19 Stain for photoreceptor precursor and mature photoreceptor markers
  4. 20 Stain for retinal ganglion cell and amacrine/bipolar cell markers
  5. 21 Stain for Müller glia and RPE markers
  6. 22 Visualize organoid structure and morphology

Full SOP

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Attribution

This SOP was authored by Organthis based on the published method in Collin et al., 2018. The originating laboratory holds no rights in this SOP and has not endorsed it unless marked Verified.

This wording is awaiting legal review.

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