A single‐cell transcriptome atlas of the adult human retina

Samuel W. Lukowski(The University of Queensland), Camden Lo(Monash University), Alexei A. Sharov(National Institutes of Health), Quan Nguyen(The University of Queensland), Lyujie Fang(Jinan University), Sandy Hung(The University of Melbourne), Ling Zhu(The University of Sydney), Ting Zhang(The University of Sydney), Ulrike Grünert(The University of Sydney), Tu Nguyen(The University of Melbourne), Anne Senabouth(Garvan Institute of Medical Research), Jafar S. Jabbari(AGRF Ltd), Emily Welby(Great Ormond Street Hospital), Jane C. Sowden(Great Ormond Street Hospital), Hayley S. Waugh(Lions Eye Institute), Adrienne Mackey(Lions Eye Institute), Graeme S. Pollock(Lions Eye Institute), Trevor D. Lamb(Australian National University), Peng‐Yuan Wang(Shenzhen Institutes of Advanced Technology), Alex W. Hewitt(University of Tasmania), Mark C. Gillies(The University of Sydney), Joseph E Powell(Garvan Institute of Medical Research), Raymond C.B. Wong(The University of Melbourne)
The EMBO Journal
August 22, 2019
Cited by 346Open Access
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Abstract

The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Müller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Müller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.


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