Dataset Information

3D epigenomic landscape of human retinal pigment epithelium [ChIATAC]

ABSTRACT: Retinal pigment epithelium (RPE) serves as a vital guardian of visual function, with its dysfunction driving pathogenesis in various retinal diseases, including age-related macular degeneration and inherited retinal disorders. While ongoing RPE cells transplantation clinical trials worldwide, the absence of standardized quality metrics for stem cell-derived RPE represents a significant gap. In this study, we aim to systematically dissect epigenomic divergence among human primary RPE (hRPE), induced pluripotent stem cell-derived RPE (iPSC-RPE), and immortalized ARPE-19 cells through multi-omic analyses. Our study elucidated the distinct functional characteristics of the three types of RPE and their underlying epigenetic regulatory mechanisms, with a particular focus on the development and functional maturation of iPSC-RPE. We further revealed cell-type-specific regulatory blueprints: hRPE exhibits strong extracellular matrix (ECM) organization capacity through 3D-epigenomic (3D genome folding and epigenomic state) regulation, as exemplified by the enrichment of the RUNX1 motif, whereas iPSC-RPE retains signatures of RPE development and weak ECM function, marked by transcription factors such as Hand1, OTX2, PAX6, and ECM-associated genes. On the other hand, ARPE-19 exhibits greater cell proliferation ability and specifically regulated by transcription factors such as KLF5. Together, our data greatly advance our understanding of RPE biology and provide a robust foundation for optimizing iPSC-RPE differentiation protocols and developing innovative therapeutic strategies for retinal diseases.

ORGANISM(S): Homo sapiens

PROVIDER: GSE307361 | GEO | 2026/07/26

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:The therapeutic potential of pluripotent stem cells is great as they promise to Q7 usher in a new era of medicine where cells or organs may be prescribed to replace dysfunctional tissue. At the forefront are efforts in the eye to develop Q8 this technology as it lends itself to in vivo monitoring and sophisticated imaging modalities. In the retina, retinal pigment epithelium (RPE) is the most promising replacement cell as it has a single layer, is relatively simple to transplant, and is associated with dozens of eye diseases. However, after transplantation, they may transform and cause complications. This transformation may be partially due to incomplete maturation. With the goal of learning how to mature RPE, we compared iPSC-RPE with adult primary RPE and the immortalized ARPE-19 line. We cultured ARPE-19, iPSC-RPE, and adult human RPE for one month, evaluating morphology, RPE marker staining, and transepithelial electrical resistance as quality control indicators. We then isolated RNA for bulk RNAsequencing and DNA for genotyping. We genotyped adult RPE lines for the top age-related macular degeneration (AMD) and proliferative vitreoretinopathy (PVR) risk allele polymorphisms. Transcriptome data verified that both adult and iPSC-RPE exhibit similar RPE gene expression signatures, significantly more than ARPE-19. In addition, in iPSC-RPE, gene networks relating to epithelial to mesenchymal transition (EMT), stem cell maintenance, retina development, and muscle contraction were significantly elevated compared to those of adult RPE. We compared adult human RPE to iPSC-RPE in a model of EMT and observed an increased sensitivity of iPSC-RPE to producing contractile aggregates in vitro which resembles incident reports upon transplantation. P38 inhibition was capable of inhibiting iPSC-RPE–derived aggregates. In summary, we find that the transcriptomic signature of iPSC-RPE conveys an immature RPE state which may be ameliorated by targeting “immature” gene regulatory networks.

Dataset Information

3D epigenomic landscape of human retinal pigment epithelium [ChIATAC]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets