Single-cell and spatial transcriptomics
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Abstract
Abstract
Most genetic risk variants linked to ocular diseases are nonprotein coding and presumably contribute to disease through dysregulation of gene expression; however, understanding their mechanisms has been impeded by incomplete annotation of transcriptional regulatory elements across retinal cell types. To address this, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome, and three-dimensional (3D) chromatin architecture in human retina, macula, and retinal pigment epithelium/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 retinal cell types. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the advancements in deep-learning techniques, we developed sequence-based predictors to interpret noncoding risk variants of retinal diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases and provides a resource for studying the gene regulatory programs of the human retina and ocular diseases.
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@article{Yuan2026Single,
title = {Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina},
author = {Ying Yuan and Pooja Biswas and Nathan R. Zemke and Kelsey Dang and Yue Wu and Matteo D’Antonio and Yang Xie and Qian Yang and Keyi Dong and Pik Ki Lau and Daofeng Li and Chad Seng and Weronika M. Bartosik and Justin Buchanan and Lin Lin and Ryan Lancione and Kangli Wang and Seo Yeon Lee and Zane A. Gibbs and Bing Yang and Joseph R. Ecker and Kelly A. Frazer and Ting Wang and Sebastian Preißl and Allen Wang and Radha Ayyagari and Bing Ren},
journal = {Science Advances},
year = {2026},
doi = {10.1126/sciadv.adv9162},
url = {https://doi.org/10.1126/sciadv.adv9162}
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