Cited by 665Retinal Development and DisordersSingle-cell and spatial transcriptomicsRetinal Diseases and Treatments

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Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution

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Cowan, Cameron S., Renner, Magdalena, De Gennaro, Martina, Gross-Scherf, Brigitte, Goldblum, David, Hou, Yanyan, Munz, Martin, Rodrigues, Tiago M., Krol, Jacek, Szikra, Tamas, Cuttat, Rachel, Waldt, Annick, Papasaikas, Panagiotis, Diggelmann, Roland, Patino-Alvarez, Claudia P., Galliker, Patricia, Spirig, Stefan E., Pavlinic, Dinko, Gerber-Hollbach, Nadine, Schuierer, Sven, Srdanovic, Aldin, Balogh, Marton, Panero, Riccardo, Kusnyerik, Akos, Szabo, Arnold, Stadler, Michael B., Orgül, Selim, Picelli, Simone, Hasler, Pascal W., Hierlemann, Andreas, Scholl, Hendrik P.N., Roma, Guglielmo, Nigsch, Florian, Roska, Botond·2020·Cell

DOI 10.1016/j.cell.2020.08.013PMC PMC7505495

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Abstract

Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable "developed" state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.

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Figure 1 Multilayered Human Retinal Organoids Produced in Quantity (A) Timeline of the AMASS organoid protocol with example bright-field images at important stages. Red arrowhead, pigment epithelium; red arrow, outer segments. EB, embryoid body. (B) Variability of embryoid body diameter with different generation methods. Bars, average coefficient of variation. Error bars, SD. (C) Embryoid body diameter (day 7) versus the number of cells seeded per microwell. Points, average diameter of embryoid bodies (n = 12) within an independent experiment. Line, quadratic fit. (D) Percentage of all organoids that were retinal organoids (week 6) versus embryoid body diameter (day 7). Points, experiments. Line, quadratic fit. (E) Schematic visualizing how AMASS improves yield from iPSCs using microwell array seeding and checkerboard scraping. (F) Comparison of organoid yield per well of iPSCs using different methods, weeks 20–38. Points, experiments. (G) Bright-field image of an organoid. OS, outer segment; ONL, outer nuclear layer; OPL, outer plexiform layer; INL, inner nuclear layer. (H) Confocal images. Left: adult retina. Right: organoid. Green, antibody against Bassoon (synaptic marker); white, Hoechst (nucleus marker). IPL, inner plexiform layer; GCL, ganglion cell layer. (I) Bright-field image of organoid pigment epithelial cells with black pigmentation. (J) Confocal image of pigment epithelial cells (maximum intensity projection). Magenta, MITF antibody; green, ZO-1 antibody (pigment epithelial cell markers). (K) Illustration of photoreceptor subcellular compartments. OS, outer segment; CC, connecting cilium; IS, inner segment; AT, axon terminal. (L–T) Organoid photoreceptors. (L–N) Outer segment. (L) Bright-field image. (M) Confocal images. Magenta, ARR3 antibody (cone marker); green, L/M opsin antibody (cone outer segment marker); white, Hoechst (nucleus marker). (N) Electron microscope image. Diagonal section of membrane discs. (O–Q) Connecting cilium. (O and P) Confocal images. Magenta, ARR3 antibody; green, ARL13B antibody (cilium marker). (P) Maximum intensity projection showing organoid surface. (Q) Electron microscope image. (R and S) Inner segment. (R) Confocal image. Magenta, L/M opsin antibody; green, TOMM1 antibody (mitochondrion marker). (S) Electron microscope image. (T) Axon terminal. Confocal image. Magenta, ARR3 antibody; green, RIBEYE antibody (ribbon synapse marker). All data from F49B7 organoids. See also Figure S1, Table S1, and Video S1.CC BY · PubMed Central

Figure S1 Characterization of F49B7 iPSCs and Retinal Organoids from Several iPSC Lines, Related to Figures 1, 2, and 3 and Table S1 (A) Bright-field image of F49B7 iPSC colony. (B) Bright-field image of iPSC colony. Blue stain, alkaline phosphatase (pluripotency marker). (C – F) Confocal images of iPSCs. Green, antibody for pluripotency markers; white, Hoechst (nucleus marker). (C) SOX2, (D) NANOG, (E) OCT4 and (F) SSEA4. (G – I) Confocal images of iPSCs directly differentiated into the three germ layers. White, Hoechst. (G) Ectoderm; magenta, Nestin; green, PAX6 (ectoderm markers). (H) Endoderm; magenta, SOX17; green, FOXA2 (endoderm markers). (I) Mesoderm; magenta, NCAM; green, Brachyury (mesoderm markers). (J) G-banded karyotyping of F49B7 iPSCs. (K) Different iPSC lines generating 5-layered retinal organoids. Confocal images. Green, Bassoon antibody (synaptic marker); white, Hoechst (nucleus marker). Boxed area, outline of F49B7 image shown cropped in Figure 1. (L) Retinal neuroepithelium (arrows) on a five-week old organoid. (M) Embryoid body diameter (day 7) versus the number of cells seeded per microwell. Points, mean diameter of embryoid bodies (n = 12) within an independent experiment. Line, quadratic fit. (N) Percentage of all organoids that were retinal organoids (week 6) versus embryoid body diameter (day 7). Points, experiments. Line, quadratic fit. (O) Confocal image. Green, RHO antibody (rod outer segment marker); white, Hoechst (nucleus marker). OS, outer segment; ONL, outer nuclear layer. (P – S) Electron microscope images of photoreceptor outer segment (OS; P, Q, S), inner segment (IS; P, R, S) and connecting cilium (CC; P, R, S). P and S are from serial sections. (T) Confocal image. Magenta, TRPM1 antibody (ON bipolar cell marker); green, GFP antibody (GCaMP6s); white, Hoechst (nucleus marker). (U) Scheme of the time course with which organoids were sampled for single-cell RNA sequencing. Data in A – J, K, L, O, P – S and T are from F49B7 organoids, data in K, M and N are from IMR90.4 organoids.CC BY · PubMed Central

Figure 2 Organoids Are Light-Responsive and Contain Functional Synapses (A–E) Synapses in organoids. (A, B, D, and E) Cone axon terminals. Confocal images. White, ARR3 (cone marker). Green, antibody against Bassoon (ribbon synapse marker); RIBEYE (ribbon synapse marker). Magenta, antibody against RIBEYE; PSD95 (postsynaptic marker); TRPM1 (ON bipolar cell marker); PV (horizontal cell marker). (C) Electron microscope image. AT, photoreceptor axon terminal; RS, ribbon synapse. (F) Schematic of organoid infection with adeno-associated viral vectors (AAV) expressing the calcium sensor GCaMP6s under the promotor EF1α. (G and H) Organoids expressing GCaMP6s. (G) Confocal image. Green, antibody against GFP detecting GCaMP6s. White, Hoechst (nucleus marker). C, cell with cone morphology; HC, cell with horizontal cell morphology; AC, cell with amacrine cell morphology; MC, Müller cell confirmed by counter-stain. (H) Two-photon microscope image. Optical cross-section of living organoid. Green, GCaMP6s. ONL, outer nuclear layer; INL, inner nuclear layer; GCL, ganglion cell layer. (I) Organoid calcium activity during background illumination and light stimulation. Top, cells from ONL. Bottom, cells from INL/GCL. Black lines, peri-stimulus calcium activity (dF/F0); line segments, individual trials. Red lines, scale bars. (J) Quantification of light responsive cells in ONL and INL/GCL. Error bars, 95% binomial confidence interval. (K and L) Organoid calcium activity during pharmacological block of glutamatergic synaptic transmission. CPP, (3-[(R)-2-carboxypiperazin-4-yl]-propyl-1-phosphonic acid); NBQX (2,3-dioxo-6-nitro-7-sulfamoyl-benzo[f]quinoxaline); APB, (2-amino-4-phosphonobutyric acid). (K) Responses from individual cells, as in (I). (L) Quantification of light responsive cells in ONL and INL/GCL, as in (J). All significance values from χ2 test. All data from F49B7 organoids. See also Figure S1.CC BY · PubMed Central

Figure 3 Organoid Transcriptome Stabilizes In Vitro with a Development Rate that Matches that of the Retina In Vivo (A) Retinal organoid single-cell sequencing. (B) Left: scVis map of cells across weeks 6–38. Each point represents the transcriptome of a single cell. Black line, isodensity contour. Middle: scVis map with transcript counts of a single gene (here, mitosis marker MKI67) color-coded; colormap at bottom. Right: heatmap of relative transcript density for MKI67; colormap at right. (C) Cell classes marked on scVis map according to (D). Arrows, inferred developmental trajectories. (D) Heatmap of relative transcript density for genes marking mitotic cells, retinal cell classes, and retinal precursors. (E) Left: scVis map of cells across all ages. Middle: a black point represents a cell from an organoid of a specific age (here week 38). Right: heatmap of relative cell density at week 38; colormap at right. (F) Heatmap of relative cell density at six different ages. (G) Black line, Jensen-Shannon divergence (DJS) of organoid transcriptomes at adjacent ages. Red dots, comparison of individual organoids from the same age and batch. (H–J) Correlation in gene expression at different ages. Each point is a correlation coefficient between two samples. Point size and color, correlation strength; scale at right. (H) Developing organoid versus developing retina. (I) Retina versus retina. (J) Organoid versus organoid. (K) A model, trained to predict retina age based on retinal transcriptome data, is applied to predict retina-equivalent age of organoid samples. (L) Red line, model-predicted retina-equivalent age of organoids versus their age in culture (mean ± 3 SEM). Black points, model-predicted age of retinas versus their developmental age. Dashed gray line, one-to-one correspondence between age and model-predicted age. All organoid data from F49B7 organoids. See also Figures S1 and S2.CC BY · PubMed Central

Figure S2 Reproducibility of Organoids, Firing Rate Statistics of Adult Retinal Ganglion Cells, Infomap Clustering Quality, and Sources of Variability in Adult Retinal UMAP Maps, Related to Figures 3, 4, and 5 Location of transcripts of (A) neurogenic and neuronal marker NEUROD1 (60 × upregulated, p = 1.8 × 10−308) and (B) gliogenic marker PAX2 (37 × upregulated, p = 5.8 × 10−12) in two pools of mitotic progenitor cells on organoid scVis map. Circles, cells expressing mitotic markers; color, transcript count; colormap at right. (C) Expression of cell type markers in week 38 (left) and week 46 (right) organoids. Colormap and legend at right. (D) Cell type composition in organoids at week 46 compared to other ages. Legend at right. (E) Heatmap of relative cell density in 28 different samples with indicators for organoid age (row), pooling method (top, pool; bottom, individual), batch (blue bar), and replicates from the same organoid (red bar). (F, G) Scatterplots comparing the correlation in ganglion cell firing rates across stimulus repetitions to their (F) average firing rate and (G) peak firing rate. Red, cells significantly light responsive (p < 0.01). Black, cells not light responsive (p ≥ 0.01). (H – J) Cluster quality was evaluated in a bootstrap process to evaluate the Infomap clusters of (H) peripheral retina, (I) foveal retina and (J) developed organoids. Light gray bars, cluster purity. Dark gray bars, cluster stability. (K) Peripheral retinal cell transcriptomes in scVis map, variation across donors. Points, single cell transcriptomes. Color, donor. (L) UMAP map of developed organoids labeled according to cell line. (M – R) The peripheral (left) and foveal (right) UMAP maps labeled according to (M – N) donor identity and sex; M, male; F, female, (O – P) 10x Chromium lane and (Q – R) cell class annotation used during subclustering.CC BY · PubMed Central

Figure 4 Post Mortem Adult Retina with Light Responses (A) Schematic of the procedure to obtain adult retinas for single-cell RNA sequencing and electrophysiology. (B) Vertical lines, action potentials fired by five example ganglion cells (horizontal boxes) during five repetitions (rows within boxes) of a light stimulus (at bottom). (C) scVis map of light responses from a sample of ganglion cells at the same retinal location; each point represents the firing rate characteristics of an individual cell in response to visual stimulation. Colors, Infomap clusters. Labels at the two axes, response characteristics of cells in that region of the scVis map. (D) Colored lines, normalized firing rate of cells within each cluster during the stimulus. Shaded regions, ±1 SD. Colors, Infomap clusters as in (C). See also Figure S2.CC BY · PubMed Central

Figure 5 Cell Types of the Adult Human Retina and Its Organoids (A) Single cells sequenced from peripheral retina, foveal retina, and developed retinal organoids (weeks 30 and 38). (B–D) UMAP maps of transcriptomic cell types within (B) peripheral retina, (C) foveal retina, and (D) developed organoids. Points, transcriptome of single cell. Abbreviations/colors, cell classes, and types as in (G). (E and F) Expression of known marker genes (rows) within Infomap clusters (columns) for (E) adult retina, both peripheral and foveal and (F) developed organoids. Dot size, percent of cells expressing. Dot color, mean transcripts per cell. Legend and colormap at bottom right of F. U, uncertainty coefficient. (G) Illustration, retinal cell classes, and types. Color bar, cell types; shades of the same color, cell types within the same cell class. (H–J) Subclustering of bipolar cells in peripheral retina, foveal retina, and retinal organoid. Points, single bipolar cells. (H) Color, bipolar cell type. Peripheral and foveal retina. (I) Color, region of origin. (J) Color, tissue of origin. All organoid data from F49B7 and IMR90.4 organoids. See also Figures S2, S3, S4, S5, and S6 and Table S2.CC BY · PubMed Central

Figure S3 Identification of Retinal Cell Types, Related to Figure 5 and Table S2 (A – I) UMAP map of cell types, colored according to cell type (left), region of origin (middle), and tissue of origin (right). (A) Rods. (B) Cones. (C) Horizontal cells. (D) Amacrine cells. (E) Ganglion cells. (F) Macroglia. (G) Pigmented cells. (H) Vascular-associated cells and fibroblasts. (I) Immune cells. (J – O) Expression of known cell type marker genes (columns) by Infomap cell types (rows). (J) Cones. (K) Horizontal Cells. (L) Bipolar cells. (M) Amacrine cells. (N) Ganglion cells. (O) Macroglia. Dot size, percent of cells expressing. Dot color, mean transcripts per cell. Colormap and legend, right of panel K. Cell type acronyms as in Figure 5. ∗, cell-type markers not previously known. (P) Expression of retinoic acid pathway genes, implicated in patterning the fovea (da Silva and Cepko, 2017). Genes for retinoic acid synthesis (ALDH1A1, ALDH1A3) and catabolism (CYP26A1), expression levels in selected cell types. CYP26A1 was expressed in foveal Müller cells and was significantly upregulated relative to the periphery (Mann-Whitney U test, CYP26A1: 6.3 × upregulated, p = 6 × 10−176). ALDH1A3 alone was expressed in pigment epithelial cells, where it was highly upregulated in the periphery relative to the fovea (630 × upregulated, p = 2.5 × 10−29). Dot size, percent of cells expressing. Dot color, mean transcripts per cell. Right, colormap and legend. Cell type acronyms are from Figures 5B–5G. ∗, cell type not present in tissue.CC BY · PubMed Central

Figure S4 Convergence of Organoid Cell Types to Those of the Adult Peripheral Retina, Cell-Type Expression of Genes Associated with Retinoic-Acid, Age-Related Macular Degeneration, and Usher Syndrome, Related to Figures 5 and 7 and Table S2 (A) Comparison of developed organoid cell type composition to that of peripheral retina (left) and foveal retina (right). Color, cell type as in Figures 5B–5G. RS, Spearman correlation. Cell types shared between organoid and adult retina. (B – C) Predictions from a classifier trained to predict the region of origin (peripheral, −1.0; foveal, +1.0) of (B) Müller cells and (C) pigment epithelial cells based on their transcriptome. Green bars, peripheral cells held out from training; purple bars, foveal cells held out from training; red bars, developed organoid cells; R2, coefficient of determination. (D – E) In situ hybridization against regional marker genes. Rows, tissue of origin. (D) Left, confocal images; Magenta, COL2A1 (peripheral Müller cell marker); Green, RLBP1, (Müller cell marker); White, DAPI (nucleus marker). Right, relative marker expression in cells. Points, cells. Color, retinal layer; legend at top right. ONL, outer nuclear layer; INL, inner nuclear layer; GCL, ganglion cell layer. (E) Confocal images. Magenta, RHCG (foveal Müller cell marker); Green, RLBP1; White, DAPI. (F) Comparison of regional marker in situ hybridization and transcriptome findings. Rows, tissue / region of origin. Columns, marker genes. Top, in situ hybridization. Bottom, single cell RNA sequencing. Dot size, percent of cells expressing. Dot color, mean transcripts per cell. Legends and colormap at right. (G) Comparison of transcriptomes in all organoid cells and adult cones by principal component analysis. Scatterplot axes are the first two principal components (PC1, PC2). Each point is the transcriptome of a cell. From left to right, panels contain cells from organoids of increasing age. Red, peripheral cones; black, developed organoid cones; gray, other organoid cells. (H) Genes from the age-related macular degeneration associated loci 1q31.3 (CFH and CFHR1, expressed by DBC_05) and 10q26.13 (HTRA1, expressed by horizontal cells and types of amacrine and ganglion cells) (Fritsche et al., 2016). Dot size, percent of cells expressing. Dot color, mean transcripts per cell. Right, colormap and legend. Cell type acronyms are from Figures 5B–5G. ∗, cell type not present in tissue. (I – M) Genes associated with type I (USH1G, USH1C, CDH23) and type III (CLRN1) Usher syndromes which had no consensus for the cell type of origin in the human retina as their expression varies across species (Mathur and Yang, 2015; Sahly et al., 2012; Siegert et al., 2012) are expressed in Müller cells of the adult peripheral and foveal retina and developed organoids. (I – J) Confocal images. In situ hybridization. Magenta, CDH23 or USH1G (Usher disease genes); green, RLBP1 (Müller cell marker); white, DAPI (nuclear marker). (K) Relative marker expression. Points, cells. Color, retinal layer. ONL, outer nuclear layer; INL, inner nuclear layer; GCL, ganglion cell layer. (L – M) Comparison of regional marker (L) in situ hybridization and (M) transcriptome findings. Rows, tissue / region of origin. Columns, marker genes. Legends and colormaps at bottom.CC BY · PubMed Central

Figure S5 Per Cell-Type Marker Gene Expression Difference between Organoid and Peripheral Retina, Related to Figures 5 and S4 and Table S2 Panels, cell types. Points, top 200 marker genes for each cell type. Labels, top 10 marker genes with the largest expression differences for that cell type. Axes; x, distance from organoid gene expression to adult z-scored using distribution of differences for the same 200 genes in peripheral retina; y, relative expression of gene in organoid compared to peripheral retina. Colormap, log2 relative expression of gene in organoid compared to peripheral retina.CC BY · PubMed Central

Figure 6 Comparison of Cell Types in Adult Human Retina and Organoids (A) Distance of organoid cell types from the peripheral retina. Distances, Z scored Euclidean distance relative to adult cell type’s distribution using 200 cell-type marker genes. Points, single cells. Cell type colors and acronyms according to Figures 5B–5G. (B–H) Cell type markers in adult retinas (left column), F49B7 organoids (middle), and IMR90.4 organoids (right). Left and middle sub-columns, confocal images. White, Hoechst (nucleus marker). Green, antibody against (B) NRL (rod marker); (C) ARR3 (cone marker); (D) PV (horizontal cell marker); (E) PRKCA (rod bipolar cell marker); (F) TRPM1 (ON bipolar cell marker); (G) CHAT (starburst amacrine cell marker); (H) RLBP1 (Müller cell marker). (B–H) Right sub-column, location within retinal layers of cells expressing marker. Points, cells. See also Figures S4, S5, and S6 and Table S2.CC BY · PubMed Central

Figure S6 Ischemia Rapidly Alters Gene Expression, Characterization of Cell Types, and Structures in Developed Organoids, Related to Figures 5 and 6 (A) Longitudinal sampling of post mortem human peripheral retina with different durations of ischemia and storage temperatures (n = 2 eyes from 1 donor). Filled circle, sample perfused with oxygenated medium until dissociation. Empty circle, sample not perfused to mimic delayed retrieval. (B – C) Time course of ischemia-induced gene expression changes in cell classes of the (B) retina kept at 20°C, (C) retina transferred to 4°C after three hours. Distance, z-scored Euclidean distance relative to the earliest time point (20 minutes) using 200 cell class specific genes. ∗, significant change in gene expression (p < 0.01, Mann-Whitney U with Bonferroni correction). (D – E) Principal component analysis of horizontal cells. Color; Left, duration of ischemia; Right, expression of LHX1 (HC_02 marker). (D) Samples stored at 20°C. (E) Samples moved to 4°C at 3 hours post-mortem. (F – M) ON bipolar cell types not expressing cell type marker PCP2. Samples stored at 20°C. (F – I) Principal component analysis of the 3 ON bipolar types not expressing PCP2. Color, (F) duration of ischemia; (G) expression of CCDC136 (DBC_03 marker); (H) expression of STX18 (DBC_04 marker); (I) expression of CFH (DBC_05 marker). (J – M) z-scored distances; (J) distance between cell types at 20 minutes. (K – M) gene expression distance versus ischemia duration. Distance, z-scored Euclidean distance from the earliest time point. (N) MALAT1 expression in rods. Rows, duration of ischemia. Right, colormap and legend. (O) Histogram of MALAT1 expression in rods. Color, duration of hypoxia. (P – X) Confocal images. (P) Magenta, S opsin antibody (blue cone marker); green, L / M opsin antibody (red/green cone marker); white, Hoechst (nucleus marker). (Q) Confocal image. Green, PRKCA antibody; white, Hoechst. (R – T) Green, TH (amacrine cell marker); white, Hoechst. (R) Adult retina, (S) F49B7 Organoid, (T) IMR90.4 Organoid. (U) Green, RLBP1 antibody (Müller cell marker); white, Hoechst. (V) Boxed area from U. ILM, inner limiting membrane. (W) Magenta, ZO-1 antibody (outer limiting membrane marker); green, rhodopsin antibody (RHO, rod outer segment marker). OS, outer segment; OLM, outer limiting membrane. (X) Top view of ZO-1 rings, maximum intensity projection. Magenta, ZO-1 antibody; green, PNA (cone outer segment marker); white, Hoechst. (Y) Quantifications of cell soma diameter of rods (RHO), cones (ARR3), horizontal cells (PV), rod bipolar cells (PRKCA), on bipolar cells (TRPM1) and amacrine cells (CHAT). Dots, cells. Error bars, SD. ∗, significant change in soma diameter (p < 0.01, Mann-Whitney U with Bonferroni correction). Data in P – S, U – Y are from F49B7 organoids, data in T and Y from IMR90.4 organoids.CC BY · PubMed Central

Figure 7 Disease Map for Adult Human Retinas and Developed Organoids (A and B) Normalized expression of disease genes (rows) within cell types (columns) of (A) peripheral retina and (B) developed organoid. Left, names of diseases and associated genes; colormap at bottom left of (A), level of intra-gene normalized expression. Filled circle, gene significantly cell type specific (p < 0.01); empty circle, gene not cell type specific (p ≥ 0.01). Cell type colors and acronyms are according to Figure 5G. (C) Organoid age (columns) dependence of disease gene (rows) expression within organoids. Colormap at bottom, level of min-max normalized expression. Organoid data from F49B7 and IMR90.4 in (B), data from F49B7 organoids in (C). See also Figures S4 and S7 and Tables S2 and S4.CC BY · PubMed Central

Figure S7 Disease Map for the Peripheral and Foveal Retina and Retinal Organoids; Stargardt Disease Gene ABCA4 Is Overexpressed in Foveal Pigment Epithelial Cells and Rods but Not Cones, Related to Figure 7 and Table S2 (A – E) Disease gene expression in retinal and organoid cell types. (A – C, E) Normalized expression of disease genes (rows) within cell types (columns) in (A) peripheral, (B, E) foveal retina and (C) retinal organoids. Left, names of diseases and associated genes. Colormap at bottom of B, level of intra-gene normalized expression. Filled circle, gene significantly cell type specific (p < 0.01); empty circle, gene not cell type specific (p ≥ 0.01). Cell type colors and acronyms are according to Figures 5B–5G. (D) Age (columns) dependence of disease gene (rows) expression within organoids. Colormap at bottom of D, level of min-max normalized expression. (F – K) Expression of Stargardt disease-associated gene ABCA4 in photoreceptors and pigment epithelial cells of the peripheral and foveal retina as well as in photoreceptors of developed organoids. (F – H) Confocal images. Green, ABCA4 antibody used in (F) peripheral retina, (G) foveal retina and (H) developed organoid; white, Hoechst (nucleus marker). OS, outer segment; RPE, retinal pigment epithelial cells. F49B7 organoid. (I) Expression level of ABCA4 within cell types and regions in adult retina and developed organoids. Legend, top left. Error bars, ± three SEM. ∗p < 1 × 10-2 by Mann-Whitney U with Bonferroni correction. Without a bracket, ∗ indicates significant test result versus peripheral and foveal retina. (J) Comparison of peripheral retina (green) and foveal retina (blue) ABCA4 expression levels in rods, cones, and pigment epithelial cells. Probability densities are generated using a Gaussian kernel density estimate with bandwidth set by Scott’s rule. (K) Violin plots show the ABCA4 transcript counts in pigment epithelial cells. Expression is subdivided by the eye ID and region of origin. No foveal choroidal / pigment epithelial sample was available for eye IDs one and two. Eye five came from a different donor than eyes three and four.CC BY · PubMed Central

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Items 401–500 of 665

Progress of iPSC-derived retinal organoids in the study of inherited retinal diseases
Liu, B., Liu, Y., Zhang, H., Huang, J., & Liu, G. (2025) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-025-04059-7 · Cited by 4
Organoids in Cancer Research and Regenerative Medicine: Current Status, Challenges, and Future Prospects
Li, R., Wu, Y., Zheng, Z., Zhou, F., Xu, K., & Su, J. (2026) · MedComm · doi:10.1002/mco2.70575 · Cited by 4
A cell fate specification and transition mechanism for human foveolar cone subtype patterning
Hussey, K. A., Eldred, K. C., Guy, B., Santiago, C. P., Zhang, J. S., Glass, I. A., Reh, T. A., Blackshaw, S., Goff, L. A., & Johnston, R. J. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2510799123 · Cited by 4
Mitochondrial dysfunction in neurodegenerative disorders: mechanisms and therapeutic advances
Tong, Y., He, J. N., Zhou, L., Zhang, J., Ho, B. M., Du, L., Yip, Y. W. Y., Bisnauthsing, H., Chan, P. P. M., Tham, C. C. Y., et al. (2026) · Molecular Biomedicine · doi:10.1186/s43556-026-00480-x · Cited by 5
Disruption of common ocular developmental pathways in patient-derived optic vesicle models of microphthalmia
Eintracht, J., Owen, N., Harding, P., & Moosajee, M. (2024) · Stem Cell Reports · doi:10.1016/j.stemcr.2024.05.001 · Cited by 4
Assembling Retinal Organoids with Microglia
Xu, J., Yu, S., & Jin, Z. (2024) · Journal of Visualized Experiments · doi:10.3791/67016 · Cited by 4
Variant-specific disruption to notch signalling in PAX6 microphthalmia and aniridia patient-derived hiPSC optic cup-like organoids
Harding, P., Owen, N., Eintracht, J., Cunha, D. L., Chan, B. H. K., Rainger, J., & Moosajee, M. (2025) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2025.167869 · Cited by 4
Development of Retinal Astroglia
Kay, J. N., Valdez‐Lopez, J. C., Dembla, E., & Miltner, A. M. (2025) · Annual Review of Vision Science · doi:10.1146/annurev-vision-121423-013153 · Cited by 4
A scRNA-seq reference contrasting living and early post-mortem human retina across diverse donor states
Yang, L., Tao, Y., Pan, Q., Cai, T., Ye, Y., Liu, J., Zhou, Y., Shao, Y., Yi, Q., Lu, Z. H., et al. (2025) · Human Genomics · doi:10.1186/s40246-025-00796-9 · Cited by 4
Disrupted transcriptional networks regulated by CHD1L during neurodevelopment underlie the mirrored neuroanatomical and growth phenotypes of the 1q21.1 copy number variant
Lemée, M. V., Loviglio, M. N., Ye, T., Tilly, P., Keime, C., Weber, C., Petrova, A., Klein, P., Morlet, B., Wendling, O., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf934 · Cited by 5
Single-Cell and Spatial Analysis of Emergent Organoid Platforms
Kumar, A., Cai, S., Allam, M., Henderson, S., Ozbeyler, M., Saiontz, L., & Coskun, A. F. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-3163-8_22 · Cited by 4
Autozygome‐guided exome‐first study in a consanguineous cohort with early‐onset retinal disease uncovers an isolated RIMS2 phenotype and a retina‐enriched RIMS2 isoform
Pozo‐Valero, M. D., Almoallem, B., Rey, A. D., Mahieu, Q., Heetvelde, M. V., Jeddawi, L., Bauwens, M., & Baere, E. B. W. D. (2024) · Clinical Genetics · doi:10.1111/cge.14517 · Cited by 4
High-fat diet alters retinal lipid composition and gene expression networks in mice
Zou, R., Cai, J., Chen, T., Mo, W., Qian, H., Zhu, X., & Zhang, L. (2025) · BMC Biology · doi:10.1186/s12915-025-02212-z · Cited by 4
Single-cell RNA sequencing in the study of human retinal organoids
Chen, Y., Xu, H., Xiao, L., Zhang, M., & Yan, N. (2025) · Experimental Eye Research · doi:10.1016/j.exer.2025.110417 · Cited by 4
Progress in the application of organoids for exploring the relationship between macrophages and various lung diseases
Jiawang, W., Liu, T., Zhang, X., Qu, C. F., Wu, J., Xu, S., Yang, J., & Xing, X. (2025) · Biofabrication · doi:10.1088/1758-5090/adde15 · Cited by 4
SUMOylation is a Translatable Target in Hypoxic MNPs Regulating Retinal Vasculopathy
Zhong, Z., Liang, G., Yu, H., Li, J., Wang, R., Ma, X., Zhou, Z., Zhao, Y., Sun, F., & Sun, X. (2025) · Advanced Science · doi:10.1002/advs.202503505 · Cited by 4
Single-cell RNA sequencing reveals the role of heat shock protein 90AA1 in Müller cell proliferation via the Necroptosis/MAPK pathway in diabetic retinopathy
Yan, Y., Yang, H., Wei, Q., Yu, D., Gao, C., Diao, B., Song, Y., & Chen, X. (2025) · Experimental Eye Research · doi:10.1016/j.exer.2025.110508 · Cited by 4
Utilization of the retinal organoid model to evaluate the feasibility of genetic strategies to ameliorate retinal disease(s)
Kelley, R. A., & Wu, Z. (2023) · Vision Research · doi:10.1016/j.visres.2023.108269 · Cited by 4
Patient stem cell-derived in vitro disease models for developing novel therapies of retinal ciliopathies
Kruczek, K., & Swaroop, A. (2023) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/bs.ctdb.2023.09.003 · Cited by 4
Physiology, Night Vision
Mehra, D., & Le, P. H. (2019) · StatPearls · Cited by 4
[Study on the measurement of ambient ammonia in urban area based on open-path DOAS technique].
Wang, J., Xie, P.-H., Qin, M., Ling, L.-Y., Ye, C.-L., Liu, J., & Liu, W. (2012) · PubMed · Cited by 4
Gene Therapy for Rhodopsin MutationsPreprint
Lewin, A. S., & Smith, W. C. (2022) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a041283 · Cited by 6
Human photoreceptor cell transplants integrate into human retina organoidsPreprint
Wagner, F., Carrera, R., Kurth, T., Michalakis, S., Naumann, R., Žužić, M., Neumann, K., Goureau, O., Busskamp, V., & Karl, M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.09.500037 · Cited by 6
Photoreceptor Cell Replacement Using Pluripotent Stem Cells: Current Knowledge and Remaining QuestionsPreprint
Monville, C., Goureau, O., & M’Barek, K. B. (2022) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a041309 · Cited by 4
Cell fate specification and conversion generate foveolar cone subtype patterning in human retinal organoidsPreprint
Hussey, K. A., Eldred, K. C., Guy, B., Santiago, C. P., Glass, I. A., Reh, T. A., Blackshaw, S., Goff, L. A., & Johnston, R. J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.28.526051 · Cited by 4
A single-nucleus RNA sequencing atlas of the postnatal retina of the shark Scyliorhinus canicula
Vidal-Vázquez, N., Hernández‐Núñez, I., Carballo-Pacoret, P., Salisbury, S. J., Villamayor, P. R., Hervas-Sotomayor, F., Yuan, X., Lamanna, F., Schneider, C., Schmidt, J., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-04547-2 · Cited by 4
Exploratory analysis of a Novel RACK1 mutation and its potential role in epileptic seizures via Microglia activation
Zhang, S., Dong, Z., Guo, J., Li, Z., Wu, H., Zhang, L., Min, F., & Zeng, T. (2025) · Journal of Neuroinflammation · doi:10.1186/s12974-025-03350-5 · Cited by 3
Robust generation of photoreceptor-dominant retinal organoids from porcine induced pluripotent stem cells
Edwards, K. L., Moore, B. M., Ganser, T.-S., Susaimanickam, P. J., Sovell, K., Martin, Y., Jager, L. D., Willes, A. M., Moyer, T. H., Bowar, L., et al. (2025) · Stem Cell Reports · doi:10.1016/j.stemcr.2025.102425 · Cited by 4
Optogenetic tools and their applications for therapeutic intervention in end-stage inherited retinal diseases
Podoliak, E., Guzman, G., & Busskamp, V. (2025) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2025.101388 · Cited by 3
Engineering infrared light detection in blind human retina using ultrasensitive human TRPV1 channels
Chevalier, M., Fadel, F., Májer, T., Magda, D. P., Gerendás, L., Kilin, F., Nagy, Z. Z., Szabó, A., Roska, B., & Testa-Silva, G. (2025) · Trends in biotechnology · doi:10.1016/j.tibtech.2025.07.033 · Cited by 3
Self-citation
Revealing immune cell secretion crosstalk in pulmonary pathogenesis: A microfluidic lung-on-a-chip approach
Wu, J. ‐., Fu, Y., Wang, X., Liu, T., Zhang, X., Qu, C., Zhang, Q., Xu, S., Yang, J., & Xing, X. (2025) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2025.126203 · Cited by 3
USH2A -Mutated Human Retinal Organoids Model Rod–Cone Dystrophy
Ashworth, K. E., Zhang, J., D’Amata, C., Héon, E., & Ballios, B. G. (2025) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.66.14.2 · Cited by 3
A deep learning-based computational pipeline predicts developmental outcome in retinal organoids
Afting, C., Bhatti, N., Schlagheck, C., Salvador, E. S., Herrera, M., Agarwal, R., Suzuki, R., Hackert, N. S., Lorenz, H., Žílová, L., et al. (2026) · PLoS Biology · doi:10.1371/journal.pbio.3003597 · Cited by 3
Gene regulatory roles of growth and differentiation factors in retinal development
Luo, Z., Shah, S. H., Tanasă, B., Chang, K., & Goldberg, J. L. (2024) · iScience · doi:10.1016/j.isci.2024.110100 · Cited by 3
In vivo mechanism of the interaction between trimethylamine lyase expression and glycolytic pathways
Li, Q., Wu, D., Song, Y., Zhang, L., Wang, T., Chen, X., & Zhang, M. (2024) · Food & Function · doi:10.1039/d4fo03809f · Cited by 3
Integrated analysis of single-cell RNA-seq and ATAC-seq in lens epithelial cells: Unveiling the role of ATF6 as a key transcription factor
Lu, H., Liu, X., Zhou, Q., Li, R., Zuo, H., Hu, K., Tian, M., Wang, H., Li, J., Li, N., et al. (2025) · Genes & Diseases · doi:10.1016/j.gendis.2025.101610 · Cited by 3
Application of hiPSC as a Drug Tester Via Mimicking a Personalized Mini Heart
Wei, L., Xia, S., Li, Y., Qi, Y., Wang, Y., Zhang, D., Hua, Y., & Luo, S. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.891159 · Cited by 3
Comparison of the Response to the CXCR4 Antagonist AMD3100 during the Development of Retinal Organoids Derived from ES Cells and Zebrafish Retina
Wu, Y., Qiu, J., Chen, S., Chen, X., Zhang, J., Zhuang, J., Liu, S., Yang, M., Zhou, P., Chen, H., et al. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23137088 · Cited by 3
A minimal-complexity light-sheet microscope maps network activity in 3D neuronal systems
Wysmolek, P. M., Kiessler, F., Salbaum, K. A., Shelton, E., Sonntag, S. M., & Serwane, F. (2022) · Scientific Reports · doi:10.1038/s41598-022-24350-y · Cited by 5
Retinogenesis in a Dish: Bibliometric Analysis and Visualization of Retinal Organoids From 2011 to 2022
Shen, W., Shao, A., Zhou, W., Lou, L., Grzybowski, A. E., Jin, K., & Ye, J. (2023) · Cell Transplantation · doi:10.1177/09636897231214321 · Cited by 4
RNA fusion in human retinal development
Wang, W., Zhang, X., Zhao, N., Xu, Z.-H., Jin, K., & Jin, Z. (2024) · eLife · doi:10.7554/elife.92523 · Cited by 3
In a century from agitated cells to human organoids
Layer, P. G. (2024) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2024.110083 · Cited by 3
Comprehensive Characterization of a Subfamily of Ca2+-Binding Proteins in Mouse and Human Retinal Neurons at Single-Cell Resolution
Liu, J.-B., Yuan, H.-L., Zhang, G., & Ke, J.-B. (2024) · eNeuro · doi:10.1523/eneuro.0145-24.2024 · Cited by 3
Iso-Seq enables discovery of novel isoform variants in human retina at single cell resolutionPreprint
Wang, L., Urrutia-Cabrera, D., Hung, S. S. C., Hewitt, A. W., Lukowski, S. W., Foord, C., Wang, P., Tilgner, H., & Wong, R. C. B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.08.607267 · Cited by 3
Zebrafish models of human-duplicated SRGAP2 reveal novel functions in microglia and visual system developmentPreprint
Uribe‐Salazar, J. M., Kaya, G., Weyenberg, K., Radke, B., Hino, K., Soto, D. C., Shiu, J.-L., Zhang, W., Ingamells, C., Haghani, N. K., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.11.612570 · Cited by 3
Deep learning predicts tissue outcomes in retinal organoidsPreprint
Afting, C., Bhatti, N., Schlagheck, C., Salvador, E. S., Herrera, M., Agarwal, R., Suzuki, R., Hackert, N. S., Lorenz, H., Žílová, L., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.19.639061 · Cited by 3
Connectome of a human foveal retinaPreprint
Kim, Y. J., PACKER, O. S., Macrina, T., Pollreisz, A., Curcio, C. A., Lee, K., Kemnitz, N., Ih, D., Nguyen, T., Lu, R., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.05.647403 · Cited by 3
RetiGene, a comprehensive gene atlas for inherited retinal diseases (IRDs)Preprint
Quinodoz, M., Çelik, E., Kamdar, D., Cancellieri, F., Kamińska, K., Ullah, M., Barberán-Martínez, P., Bouckaert, M., Cortón, M., Delanote, E., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.08.653722 · Cited by 3
Unified Generation of Regionalized Neural Organoids from Single-Lumen NeuroepitheliumPreprint
Rao, J., He, Z., Loskarn, S., Bender, A., Jo, Y., Lückel, J., Curcio, M., Cubela, I., Camp, J. G., Treutlein, B., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.18.689013 · Cited by 4
Retinal cytoarchitecture is preserved in an organotypic perfused human and porcine eye model
Chan, D. W.-H., Zhang, J. W., Won, G.-J., & Sivak, J. M. (2024) · Acta Neuropathologica Communications · doi:10.1186/s40478-024-01892-y · Cited by 2
Recreating pathophysiology of CLN2 disease and demonstrating reversion by TPP1 gene therapy in hiPSC-derived retinal organoids and retina-on-chip
Corti, S., Kim, K. H., Chen, T., Botezatu, A., Cora, V., Ma, K., Pashkovskaia, N., Vergara, A. B., Sperlich, D., Dave, K., et al. (2025) · Cell Reports Medicine · doi:10.1016/j.xcrm.2025.102244 · Cited by 5
Organoids: their emerging essential role in pathological mechanisms and drug discovery of diabetes and its complications
Xu, X., Zhang, Y., Geng, Y., Luo, Y., & Sun, X. (2025) · Frontiers in Pharmacology · doi:10.3389/fphar.2025.1650200 · Cited by 3
Organoids in Genetic Disorders: from Disease Modeling to Translational Applications
Zhu, Y., Lin, N., Li, J., Zhang, H., Zhang, P., Cheng, X., Yang, Q., & Liu, L. (2025) · Stem Cell Reviews and Reports · doi:10.1007/s12015-025-10973-x · Cited by 2
The genesis of neurons and glia in the developing retina
Kaplan, L., Wohlschlegel, J., & Reh, T. A. (2025) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/bs.ctdb.2025.05.001 · Cited by 2
CRISPR/Cas-mediated activation of genes associated with inherited retinal dystrophies in human cells for diagnostic purposes
Weber, V. J., Reschigna, A., Gerhardt, M. J., Heigl, T., Hinrichsmeyer, K. S., van den Engel, S., Otify, D. Y., Gavrilov, Z., Blaser, F., Meneau, I., et al. (2025) · JCI Insight · doi:10.1172/jci.insight.189615 · Cited by 2
Organoid-derived photoreceptor precursors enriched by CD9⁻CD81mid sorting restore visual function in RCS rats
Wang, C., Chen, M., Fang, Y., Fu, Y., Lv, Y., Zhang, X., Li, B., Bai, Y., Li, Q., Zeng, Y., et al. (2025) · Stem Cell Research & Therapy · doi:10.1186/s13287-025-04848-8 · Cited by 2
Human pluripotent stem cell-derived retinal ganglion cells: advances in differentiation and translational applications
Ma, J. Y. W., Daniszewski, M., & Pébay, A. (2025) · Molecular Medicine · doi:10.1186/s10020-025-01405-0 · Cited by 3
Retinal organoids in age-related macular degeneration: Promise, pitfalls, and progress
Palakkan, A. A., & Kumar, G. S. (2025) · Experimental Eye Research · doi:10.1016/j.exer.2025.110831 · Cited by 2
Single-Cell Transcriptomics on PRPF31-Mutated Retinal Organoids Reveal Early Müller Glial Activation and Progressive Photoreceptor Degeneration
Bellapianta, A., Qi, J., Giugliano, M., Ouaidat, S., Rawas, R. E., Bolz, M., & Salti, A. (2025) · Biomedicines · doi:10.3390/biomedicines14010045 · Cited by 2
Transcriptome analysis and RT-qPCR validation of mitophagy-related key genes in the progression of diabetic retinopathy
Zhang, Y., Niu, L., Xia, H., & Wang, J. (2026) · Frontiers in Endocrinology · doi:10.3389/fendo.2025.1733368 · Cited by 2
Clonally expanded HSP-specific T cells contribute to glaucomatous neurodegeneration via the mTORC1 pathway
Wang, Z., Chen, G., Chen, G., Zhao, C., Wang, C., Shi, J., & Chen, H. (2026) · Journal of Neuroinflammation · doi:10.1186/s12974-026-03693-7 · Cited by 3
Healing of ischemic injury in the retina
Becker, S., L'Ecuyer, Z., Allen, J., Saeid, S., Sturgis, L., Adderley, A., Koskelainen, A., & Vinberg, F. (2026) · Science Advances · doi:10.1126/sciadv.adx7204 · Cited by 2
Advances in Quality Control of Tumor Organoid Living Biobanks
Fan, R., Zhou, S., An, P., Ye, X., Yu, M., Wang, Y., & Wu, C. (2026) · Biopreservation and Biobanking · doi:10.1177/19475535261416482 · Cited by 2
Development of a 3D-printed microfluidic chip for retinal organoid–endothelial co-culture
Abdalkader, R., Kawakami, S., Takashima, Y., & Fujita, T. (2026) · Lab on a Chip · doi:10.1039/d5lc00939a · Cited by 5
Organoid–microglia system for modeling the immune microenvironment of the brain and retina
Yu, J., Tang, B., Gu, Z., Wang, G., & Liu, A. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1747589 · Cited by 2
Protocol for quality control screening of brain organoid morphology
Chiaradia, I., Jérôme Boulanger, A., Elmkvist, S. B., Larsen, M. R., & Lancaster, M. A. (2026) · STAR Protocols · doi:10.1016/j.xpro.2026.104423 · Cited by 2
Organoid models: Regulations and prospects for the development of investigational new drugs
Li, H., Pan, Y., Zheng, Z., Lin, R., Pan, Y., Lin, L., Quan, M., Lu, H., Hu, Z., Zheng, M., et al. (2026) · Chinese Medical Journal · doi:10.1097/cm9.0000000000004067 · Cited by 4
Retinal organoids: current status of development and new avenues for application in disease modeling, drug discovery and therapeutics
Agarwal, R., Iezhitsa, I. N., Hombrebueno, J. R., & Agarwal, P. (2026) · International Journal of Retina and Vitreous · doi:10.1186/s40942-026-00846-x · Cited by 2
Revisiting retinal and macular degeneration in the genomics era
Swaroop, A., & Roska, B. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-026-00960-4 · Cited by 2
Self-citation
The Analysis of Embryoid Body Formation and Its Role in Retinal Organoid Development
Berzal, A. H., Wagstaff, E. L., ten Asbroek, A. L. M. A., ten Brink, J. B., Bergen, A. A. B., & Boon, C. J. F. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25031444 · Cited by 2
Exploring the Cocktail Factor Approach to Generate Salivary Gland Progenitors through Co-Culture Techniques
Zhang, Y., Yan, S., Mei, Z., Zhang, H., Ding, C., Zhang, S., & Wei, S. (2024) · Tissue Engineering and Regenerative Medicine · doi:10.1007/s13770-024-00632-6 · Cited by 2
Non-Canonical Wnt Pathway Expression in the Developing Mouse and Human Retina
Campos, R. C., Matsunaga, K., Reid, M. W., Fernández, G. E., Stepanian, K., Bharathan, S. P., Li, M., Thornton, M. E., Grubbs, B. H., & Nagiel, A. (2023) · Experimental Eye Research · doi:10.1016/j.exer.2024.109947 · Cited by 3
Morphogenetic Designs, and Disease Models in Central Nervous System Organoids
Bock, M., Hong, S. J., Zhang, S., Yu, Y., Lee, S., Shin, H.-E., Choi, B. H., & Han, I. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25147750 · Cited by 3
PHLDA1-PRDM1 mediates the effect of lentiviral vectors on fate-determination of human retinal progenitor cells
Hu, X., Chen, J., Dai, W., Xiao, Y., Chen, X., Chen, Z., Zhang, S., & Hu, Y. (2024) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-024-05279-z · Cited by 2
Advances in Organ-on-a-chip Technologies for Biomedical Research and Applications
Zhu, Q., Liao, M., Hu, Y., & Chai, R. (2025) · Materials Lab · doi:10.54227/mlab.20240006 · Cited by 2
3D Quantification of Viral Transduction Efficiency in Living Human Retinal Organoids
Rogler, T. S., Salbaum, K. A., Brinkop, A. T., Sonntag, S. M., James, R. E., Shelton, E., Thielen, A., Rose, R., Babutzka, S., Klopstock, T., et al. (2025) · Small Methods · doi:10.1002/smtd.202401050 · Cited by 2
Investigation of ABCA4 Missense Variants and Potential Small Molecule Rescue in Retinal Organoids
Piccolo, D., Sladen, P. E., Guarascio, R., Ziaka, K., & Cheetham, M. E. (2025) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.66.9.58 · Cited by 2
SOX2-driven enhancer landscape defines the transcriptional architecture of retinogenesis
Bian, F., Golestaneh, K., Davis, E., Khan, A., Nicholson, B., Daghsni, M., Flohr, K., Liu, S., da Silva, S., Pennacchio, L. A., et al. (2025) · Development · doi:10.1242/dev.204986 · Cited by 3
Numb deficiency impairs retinal structure and visual function in mice
Yan, J., Li, Y., Zhang, T., & Shen, Y. (2022) · Experimental Eye Research · doi:10.1016/j.exer.2022.109066 · Cited by 2
Leveraging neural crest pluripotency to extend retinal and craniofacial niches for building neurovascular organoids—a theranostic and drug development perspective
Sharma, M., Jangra, S., Dhiman, S., Yangzes, S., Tiwari, A., Patro, S. K., Sharma, K., Rathore, S., Ramavat, A. S., Chhabra, S., et al. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-99987-8.00007-2 · Cited by 2
Modeling Retinitis Pigmentosa with Patient-Derived iPSCs
Leong, Y. C., & Sowden, J. C. (2023) · Advances in experimental medicine and biology · doi:10.1007/978-3-031-27681-1_81 · Cited by 2
Extensive incorporation, polarisation and improved maturation of transplanted human cones in a murine cone degeneration modelPreprint
Gasparini, S. J., Tessmer, K., Reh, M., Wieneke, S., Carido, M., Völkner, M., Borsch, O., Swiersy, A., Žužić, M., Goureau, O., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.26.457641 · Cited by 2
Gene Regulatory Networks Controlling Temporal Patterning, Neurogenesis, and Cell Fate Specification in the Mammalian RetinaPreprint
Lyu, P., Hoang, T. V., Santiago, C. P., Thomas, E. D., Timms, A. E., Appel, H., Gimmen, M. Y., Le, N., Jiang, L., Kim, D. W., et al. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3921283 · Cited by 3
Editorial: Hereditary Optic Neuropathies: A New Perspective
Carelli, V., Karanjia, R., & Morgia, C. L. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.742484 · Cited by 2
Scale Invariance of Mechanical Properties in the Developing Mammalian RetinaPreprint
Shelton, E., Frischmann, M., Brinkop, A. T., James, R. E., Hüttl, L. M., & Serwane, F. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.21.619491 · Cited by 2
Putative Role of Norrin in Neuroretinal Differentiation Revealed by bulk and scRNA Sequencing of Human Retinal OrganoidsPreprint
Maggi, K., Atac, D., Maggi, J., Feil, S., Koller, S., & Berger, W. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.15.623746 · Cited by 2
Developmental wave of programmed ganglion cell death in human retinal organoidsPreprint
Brooks, T., Park, Y. K., Vielle, A., Ha, M., Rio‐Tsonis, K. D., Robinson, M. L., & Vergara, M. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.25.666895 · Cited by 2
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Authors: Cowan, C. S., Renner, M., De Gennaro, M., Gross-Scherf, B., Goldblum, D., Hou, Y., Munz, M., Rodrigues, T. M., Krol, J., Szikra, T., Cuttat, R., Waldt, A., Papasaikas, P., Diggelmann, R., Patino-Alvarez, C. P., Galliker, P., Spirig, S. E., Pavlinic, D., Gerber-Hollbach, N., Schuierer, S., Srdanovic, A., Balogh, M., Panero, R., Kusnyerik, A., Szabo, A., Stadler, M. B., Orgül, S., Picelli, S., Hasler, P. W., Hierlemann, A., Scholl, H. P. N., Roma, G., Nigsch, F., & Roska, B.
Affiliations: Institute of Molecular and Clinical Ophthalmology Basel (CH)
University of Basel (CH)
Novartis Institutes for BioMedical Research (CH)
SIB Swiss Institute of Bioinformatics (CH)
ETH Zurich (CH)
Friedrich Miescher Institute (CH)
Johns Hopkins University (US)
Novartis (Switzerland) (CH)
Corresponding author: Roma, Guglielmo
Nigsch, Florian
Roska, Botond
ORCID: Cowan, Cameron S.
Renner, Magdalena
Goldblum, David
Hou, Yanyan
Munz, Martin
Rodrigues, Tiago M.
Cuttat, Rachel
Waldt, Annick
Papasaikas, Panagiotis
Diggelmann, Roland
Spirig, Stefan E.
Schuierer, Sven
Srdanovic, Aldin
Panero, Riccardo
Stadler, Michael B.
Orgül, Selim
Picelli, Simone
Hasler, Pascal W.
Hierlemann, Andreas
Scholl, Hendrik P.N.
Roma, Guglielmo
Nigsch, Florian
Roska, Botond
Venue: Cell
Publisher: Elsevier BV
Published: 2020-09
Volume: 182
Issue: 6
Pages: 1623-1640.e34
ISSN: 0092-8674 (ISSN-L)
DOI: 10.1016/j.cell.2020.08.013
PMC: PMC7505495
OpenAlex: W3087102910
Cited by: 654
References: 94
Citations by year: 2026: 79 · 2025: 118 · 2024: 118 · 2023: 113 · 2022: 123 · 2021: 74 · 2020: 23
FWCI: 26.98
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Cell (publishedVersion, cc-by)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
The Novartis Repository (Novartis) (submittedVersion, cc-by)
Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
ETH Zürich Research Collection (cc-by)
Funders: European Research Council
Topics: Health Sciences › Medicine › Ophthalmology › Retinal Development and Disorders
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
Keywords: retinal cell types, single-cell transcriptomics, retinal development, photosensitivity, retinal pigment epithelium, choroid, fovea, macular degeneration, cell type specificity, retinal repair
MeSH terms: Cell Differentiation, Cell Line, Electrophysiology, Female, Multigene Family, Humans, Microscopy, Electron, Naphthoquinones, Organoids, Retina, Synapses, In Situ Hybridization, Gene Expression Regulation, Developmental, Cell Culture Techniques, Genetic Predisposition to Disease, Induced Pluripotent Stem Cells, Single-Cell Analysis, Transcriptome

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Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution

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