Published April 8, 2023 | Submitted + Supplemental Material
Discussion Paper Open

Evolution of neuronal cell classes and types in the vertebrate retina

Abstract

The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs (Baden et al., 2020). One might expect that retinal cell types evolved to accommodate these varied needs, but this has not been systematically studied. Here, we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a teleost fish, a bird, a reptile and a lamprey. Molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells [RGCs] and Müller glia) is striking, with transcriptomic differences across species correlated with evolutionary distance. Major subclasses are also conserved, whereas variation among types within classes or subclasses is more pronounced. However, an integrative analysis revealed that numerous types are shared across species based on conserved gene expression programs that likely trace back to the common ancestor of jawed vertebrates. The degree of variation among types increases from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified mammalian orthologs of midget RGCs, which comprise >80% of RGCs in the human retina, subserve high-acuity vision, and were believed to be primate-specific (Berson, 2008); in contrast, the mouse orthologs comprise <2% of mouse RGCs. Projections both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.

Additional Information

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. This work was supported by the NIH (K99EY033457, R00EY028625, R21EY028633, U01MH105960 and T32GM007103), the Chan-Zuckerberg Initiative (CZF-2019-002459), the Glaucoma Research Foundation (K.S.), startup funds from the UC Berkeley (K.S.), an award from Research to Prevent Blindness and a Klingenstein-Simons Fellowship Award (Y.R.P.), a Wellcome Trust Investigator Award (210684/Z/18/Z) (R.J.L.), an ARCS Foundation Scholarship and a Society for Developmental Biology Emerging Models grant (A.M.R.), and grants from Children's Glaucoma Foundation and NSF (1827647) to James Lauderdale and Douglas B. Menke. We thank James D. Lauderdale and Douglas B. Menke (University of Georgia) for supervision of A.M.R.; Mallory Laboulaye and Rebecca Schaffer for assistance; Joseph Wekselblatt for tree-shrew tissue.; Guoping Feng for marmoset tissue; Hopi Hoekstra for peromyscus tissue; and Steve Van Hooser for ferret tissue. Icons for species in the figures were obtained from BioRender.com. Code Availability. scRNA-seq data clustering, integration, and visualization was performed in the R statistical language, and heavily relied on the Seurat package (https://satijalab.org/seurat/). All scripts are available at https://github.com/shekharlab/RetinaEvolution including R markdown notebooks. FLDA analysis was performed in Python, and the code and documentation are available at https://github.com/muqiao0626/FLDA. The authors have declared no competing interest.

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Submitted - nihpp-2023.04.07.536039v1.pdf

Supplemental Material - media-1.xlsx

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Additional details

Created:
August 20, 2023
Modified:
February 1, 2025