Understanding the complexity of retina and pluripotent stem cell derived retinal organoids with single cell RNA sequencing: current progress, remaining challenges and future prospective

Abstract

Single-cell sequencing technologies have emerged as a revolutionary tool with transformative new methods to profile genetic, epigenetic, spatial, and lineage information in individual cells. Single-cell RNA sequencing (scRNA-Seq) allows researchers to collect large datasets detailing the transcriptomes of individual cells in space and time and is increasingly being applied to reveal cellular heterogeneity in retinal development, normal physiology, and disease, and provide new insights into cell-type specific markers and signaling pathways. In recent years, scRNA-Seq datasets have been generated from retinal tissue and pluripotent stem cell-derived retinal organoids. Their cross-comparison enables staging of retinal organoids, identification of specific cells in developing and adult human neural retina and provides deeper insights into cell-type sub-specification and geographical differences. In this article, we review the recent rapid progress in scRNA-Seq analyses of retina and retinal organoids, the questions that remain unanswered and the technical challenges that need to be overcome to achieve consistent results that reflect the complexity, functionality, and interactions of all retinal cell types.

Transplantation of miPSC/mESC-derived retinal ganglion cells into healthy and glaucomatous retinas

“…For RGCs derived from human iPSCs, attempts have been made to explore RGC subtype diversity within the organoids themselves by single-cell RNA-seq, though, until recently, attempts along those lines were hindered by the lack of appropriate reference datasets and sample numbers remained low, limiting conclusions. 49 , 56 , 57 , 58 , 59 …”

Naught all zeros in sequence count data are the same

“…Such condition-specific zero-inflation is commonly used in a number of popular software packages [33] , [20] , [25] , [16] , [27] . Moreover, the zero-inflated model we use here has been used in multiple studies to conduct differential expression analysis [50] , [51] , [52] , [53] . We refer to these two models respectively as the Zero-Inflated Negative Binomial (ZINB) and Negative Binomial (NB) models (see Section 6 for more details).…”

Pluripotent stem cell-derived retinal organoids for disease modeling and development of therapies

“…However, faithfulness of subtype diversification, molecular marker expression within subtypes and relative proportions of various types are still largely missing. Several recent studies took advantage of the advances in single‐cell transcriptional profiling to fill this gap 21,79‐82 . First studies with a relatively small number of cells demonstrated robust specification into photoreceptors and Müller glia 21,79 .…”