Cells in the chicken retina with the nuclei (the part of the cell that contains the DNA) in blue, specific interneuron types in green and other neurons in red. Image credit: Masahito Yamagata (CC BY 4.0)
The evolutionary relationships of organisms and of genes have long been studied in various ways, including genome sequencing. More recently, the evolutionary relationships among the different types of cells that perform distinct roles in an organism, have become a subject of inquiry. High throughput single-cell RNA sequencing is a technique that allows scientists to determine what genes are switched on in single cells. This technique makes it possible to catalogue the cell types that make up a tissue and generate an atlas of the tissue based on what genes are switched on in each cell. The atlases can then be compared among species.
The retina is a light-sensitive tissue that animals with a backbone, called vertebrates, use to see. The basic plan of the retina is very similar in vertebrates: five classes of neurons – the cells that make up the nervous system – are arranged into three layers. The chicken is a highly visual animal and it has frequently been used to study the development of the retina, from understanding how unspecialized embryonic cells become neurons to examining how circuits of neurons form. The structure and role of the retina have been studied in many vertebrates, but detailed descriptions of this tissue at the molecular level have been largely limited to mammals.
To bridge this gap, Yamagata, Yan and Sanes generated the first cell atlas of the chicken retina. Additionally, they developed a gene editing-based technique based on CRISPR technology called eCHIKIN to label different cell types based on genes each type switched on selectively, providing a means of matching their shape and location to their molecular identity. Using these methods, it was possible to subdivide each of the five classes of neurons in the retina into multiple distinct types for a total of 136.
The atlas provided a foundation for evolutionary analysis of how retinas evolve to serve the very different visual needs of different species. The chicken cell types could be compared to types previously identified in similar studies of mouse and primate retinas. Comparing the relationships among retinal cells in chickens, mice and primates revealed strong similarities in the overall cell classes represented. However, the results also showed big differences among species in the specific types within each class, and the genes that were switched on within each cell type.
These findings may provide a foundation to study the anatomy, physiology, evolution, and development of the avian visual system. Until now, neural development of the chicken retina was being studied without comprehensive knowledge of its cell types or the developmentally important genes they express. The system developed by Yamagata, Yan and Sanes may be used in the future to learn more about vision and to investigate how neural cell types evolve to match the repertoire of each species to its environment.
