Using single cell transcriptomics to study the complexity of human retina
Daniel Urrutia-Cabrera and Raymond Ching-Bong Wong
Neural Regeneration Research, 15(11):2045-2046
Abstract
The human retina is a specialized multilayered structure composed of numerous cell types. The process of vision relies on a robust network integrated by rod photoreceptors, cone photoreceptors, bipolar cells, horizontal cells, amacrine cells and retinal ganglion cells, which detect, process and relay the visual information to the brain. Additionally, structural and metabolic support is provided by Müller glia, retinal astrocytes and microglia. Over 200 genes have been implicated in inherited retinal diseases (RetNet: https://sph.uth.edu/retnet/). However, in many cases, the retinal cell types that express these disease-associated genes remain to be identified. The complexity of the human retina represents a major challenge for the molecular profiling of all retinal cell types. Many previous studies utilised bulk RNA-seq to profile the whole human adult retina, which only analysed the averaged gene expression levels across all retinal cell types. As such, knowledge of the transcriptome profile in specific cell types within the retina would help us to unravel the heterogeneity of retinal cells, advance understanding of the pathogenesis of inherited retinal diseases, and to develop gene therapies that could improve treatment options.
Single cell RNA sequencing (scRNA-seq) is a powerful technique that enables a thorough analysis of the gene expression profile at a single cell level, thus fostering the understanding of the complex biological diversity of tissues at an unprecedented resolution. Using scRNA-seq, we recently reported the generation of a single cell transcriptome atlas of the human adult neural retina, by profiling 20,009 neural retinal cells from three healthy donors (Lukowski et al., 2019). This work was conducted as part of the Human Cell Atlas Project (Regev et al., 2017) and the Australia and New Zealand Human Eye Cell Atlas Consortium. Notably, our human retina transcriptome atlas identified the transcriptome of all major neural retinal cells, including rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes and microglia. This dataset can be accessed through the EMBL Single Cell Expression Atlas or the Human Cell Atlas Data Portal (https://data.humancellatlas.org/explore/projects/8185730f-4113-40d3-9cc3-929271784c2b). Collectively, this gene atlas provide unprecedented insights into the gene expression that enable the specialised function of individual cells in the retina and contribute to healthy vision.
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