Transcriptomic Analysis of the Developmental Similarities and Differences Between the Native Retina and Retinal Organoids

Abstract

PURPOSE. We performed a bioinformatic transcriptome analysis to determine the alteration of gene expression between the native retina and retinal organoids in both mice and humans. METHODS. The datasets of mouse native retina (GSE101986), mouse retinal organoids (GSE102794), human native retina (GSE104827), and human retinal organoids (GSE119320) were obtained from Gene Expression Omnibus. After normalization, a principal component analysis was performed to categorize the samples. The genes were clustered to classify them. A functional analysis was performed using the bioinformatics tool Gene ontology enrichment to analyze the biological processes of selected genes and cellular components. RESULTS. The development of retinal organoids is slower than that in the native retina. In the early stage, cell proliferation predominates. Subsequently, neural differentiation is dominant. In the later stage, the dominant differentiated cells are photoreceptors. Additionally, the fatty acid metabolic process and mitochondria-related genes are upregulated over time, and the glycogen catabolic process and activin receptors are gradually downregulated in human retinal organoids. However, these trends are opposite in mouse retinal organoids. There are two peaks in mitochondria-related genes, one in the early development period and another during the photoreceptor development period. It takes about five times longer for human retinal development to achieve similar levels of mouse retinal development. CONCLUSIONS. Our study reveals the similarities and differences in the developmental features of retinal organoids as well as the corresponding relationship between mouse and human retinal development.

Retinoblastoma: Etiology, Modeling, and Treatment

“…Cone signal circuitry and the glial tumor microenvironment remain in organoids, and the drug responses of organoids mimic those of tumor cells in advanced disease [ 48 ]. Additionally, human retinal organoids generated from induced pluripotent stem cells (iPSCs), or embryonic stem cells (ESCs), are alternatives to the fetal retina which has limited availability [ 98 , 99 , 100 , 101 , 102 ]. The retinal organoids made deficient for RB1 may provide a model to examine the initiation and development of tumors, such as the cancer cell-of-origin [ 17 , 26 ].…”

Boolean Implication Analysis Improves Prediction Accuracy of In Silico Gene Reporting of Retinal Cell Types

“…36,37 Single-cell RNA sequencing (scRNA-seq) is increasingly common today and is one the most detailed methods to profile transcriptomes of retinal cell types and subtypes. 2,8,13,22,[38][39][40][41][42][43][44][45][46][47][48] Most studies on retinal cell types have relied upon murine models, but many increasingly study human donor retinas 6,30,31,[48][49][50] , especially in order to profile retinal disease. 31,43,[50][51][52][53] Glaucoma, age-related macular dystrophy and retinal light damage have also been studied in murine models.…”

“…10, 13, 14, 17, 24, 29-31, 39, 41, 46, 47, 53, 56, 59 In single-cell analysis, dimension reduction through Principal Component Analysis to reduce the size of data and allow visualization is often performed before hierarchical clustering identify cell clusters. 2,7,30,41,42,49,56,60 Cell clusters can be assigned to different cell types or subtypes based on the expression of key marker genes. 48 AI-guided identification of cell clusters has recently been investigated.…”

“…63 Correlational methods for ranking gene expression are also widely used, bypassing the need to discover cell clusters and identifying co-expressed genes in complex cultures, including developing retinal organoids. 2,8,23,27,49,64 Identifying relationships between genes has led towards broader goals of graph 47,60 and networkbased analysis. 9,10,17,25,27,31,60,65 Gene expression networks can be used to identify transitions between phenotypes and disease states, paving the way for clinical target identification.…”

Retinal organoids: a window into human retinal development

“…This also highlights the existence of greater redundancy and plasticity in signalling pathways governing NR specification than initially deciphered from classical studies. Transcriptomic analysis of retinal organoids has identified this plasticity in the existence of cell cluster transition zones in early postmitotic cell fate specification between progenitors and differentiated neurons ( Collin et al, 2019a ; Cui et al, 2020 ; Sridhar et al, 2020 ). Signalling pathways and novel genes involved in RPC commitment were also identified in organoids, with single-cell RNA sequencing (scRNAseq) distinguishing two distinct RPC subtypes ( Mao et al, 2019 ).…”