A single-nucleus RNA sequencing atlas of the postnatal retina of the shark Scyliorhinus canicula

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The retina, whose basic cellular structure is highly conserved across vertebrates, constitutes an accessible system for studying the central nervous system. In recent years, single-cell RNA sequencing studies have uncovered cellular diversity in the retina of a variety of species, providing new insights on retinal evolution and development. However, similar data in cartilaginous fishes, the sister group to all other extant jawed vertebrates, are still lacking. Here, we present a single-nucleus RNA sequencing atlas of the postnatal retina of the catshark Scyliorhinus canicula, consisting of the expression profiles for 17,438 individual cells from three female, juvenile catshark specimens. Unsupervised clustering revealed 22 distinct cell types comprising all major retinal cell classes, as well as retinal progenitor cells (whose presence reflects the persistence of proliferative activity in postnatal stages in sharks) and oligodendrocytes. Thus, our dataset serves as a foundation for further studies on the development and function of the catshark retina. Moreover, integration of our atlas with data from other species will allow for a better understanding of vertebrate retinal evolution.

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Vidal-Vázquez, N., Hernández-Núñez, I., Carballo-Pacoret, P. et al. A single-nucleus RNA sequencing atlas of the postnatal retina of the shark Scyliorhinus canicula. Sci Data 12, 228 (2025). https://doi.org/10.1038/s41597-025-04547-2

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This work was supported by grant ED431C 2021/18 funded by Xunta de Galicia to E.C., and grant PID2020-115121GB-I00 funded by MICIU/AEI/10.13039/501100011033 to A.B.-I. N.V.-V. was supported by grant FPU21/03076 funded by Ministerio de Ciencia, Innovación y Universidades. D.R. was supported by the Axencia Galega the Innovación (GAIN, Xunta de Galicia) as part of the Oportunius programme, and by BBSRC Institute Strategic Grants to the Roslin Institute (BBS/E/20002172, BBS/E/D/30002275, BBS/E/D/10002070 and BBS/E/RL/230002 A). S.S. gratefully acknowledges an NSERC PDF award. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (VerteBrain to H.K., grant agreement no. 101019268). This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/), and by the Galician Supercomputing Center (CESGA). The supercomputer FinisTerrae III has been funded by the NextGeneration EU 2021 Plan de Recuperación, Transformación y Resiliencia (ICT2021-006904), by the Programa Operativo Plurirregional de España 2014–2020 of the European Regional Development Fund (ERDF) (ICTS-2019-02-CESGA-3), and by the Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia del Plan Estatal de Investigación Científica y Técnica y de Innovación 2013–2016 (1) Subprograma estatal de infraestructuras científicas y técnicas y equipamiento of ERDF (CESG15-DE-3114).

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© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Attribution 4.0 International