A single cell sequencing approach to determine the heterogeneity, dynamics and cell fate decisions of retinal progenitor cells in vivo and in vitro

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Being told that you have a visual impairment that can't be treated can be difficult to accept but this is the burden that 285 million people worldwide must bear. 26% of global blindness is caused by dysfunction of the retina, which is the innermost, light sensitive tissue that lines the back of the eye and is vital for light sensing and image processing. Dysfunction of retina and subsequent vision loss can occur through the effect of faulty genes we inherit from our parents as well as the accumulation of damage and the effect of various diseases throughout our lives. Our ability to prevent and treat vision loss is closely linked to our knowledge of "how our retinas form" and when and what is likely to go wrong. Our retinas develop mostly before birth; hence the availability of tissue to study from this time period is very limited. My group is in a unique position to bridge this gap, having access to human retinas through close and well established collaborations with the Human Developmental Biology Resource, which collects samples from aborted embryos and fetuses with the mother's consent. We also have the advantage of creating in the lab three-dimensional structures called "retinal organoids", which resemble the formation of human retina during development and contain the key retinal cell types. Our aim is to use both of these unique resources to understand how and when the retina forms and the role of genes that cause loss of vision when faulty.Retina is a complex tissue and is composed of seven cell types: these emerge at different points during our development from a pool of progenitor cells, which in itself is heterogeneous with various subsets suggested to give rise to the different cell types in a concise progression through time. For this reason, it has been difficult to pinpoint the progenitor cells which give rise to all the cell types that make up the human retina with the traditional research methods that rely on studies of cell mixtures. Here we propose to use an important new technology called single cell analysis which allows us to look at which genes are turned on in each cell in the population. Gene expression at the single cell level is a very reliable tool for the precise categorisation of cells and allows us to identify types of cells that are not noticeable when looking under the microscope at their shape or position. We will use this as a first step to explore the molecular differences of individual retinal cells in both developing retinas and the retinal organoids generated in our lab. The use of advanced data analysis techniques will then allow us to build a catalogue of cell types and the genes that characterise them, to match the progenitors to the various cell types across development, to predict their ultimate fate and to assess how closely the lab generated retinal organoids mimic the development of human retina. Second, we will use the single cell sequencing data to reconstruct a lineage tree using bioinformatics tools. This approach organises cells in 'pseudo-time', predicting the order and mode in which cell fate decisions are made, enabling us to predict genes that occupy special positions around branch points of the tree. Third, we will apply a new approach, which allows us to correlate the gene expression profile of individual cells with their location in the retina, thus creating a spatial map of our retinas as they develop. This spatial map will allow us to validate the expression of key genes that are found near the branch points which may be important to understand the decision that progenitor cells make towards their final trip to become retinal cells. Finally, we will assess whether genes expressed around branch points play an active role in controlling cell fate decisions by manipulating their expression. The information will be available to all scientists and clinicians to help their understanding of retinal development and disease.