Редактирование: Шаблон:Medline-entry

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{{medline-entry
|title=Transcriptomic Profiling of Human Pluripotent Stem Cell-derived Retinal Pigment Epithelium over Time.
|pubmed-url=https://pubmed.ncbi.nlm.nih.gov/33307245
|abstract=Human pluripotent stem cell (hPSC)-derived progenies are immature versions of cells, presenting a potential limitation to the accurate modelling of diseases associated with maturity or age. Hence, it is important to characterise how closely cells used in culture resemble their native counterparts. In order to select appropriate time points of retinal pigment epithelium ([[RPE]]) cultures that reflect native counterparts, we characterised the transcriptomic profiles of the hPSC-derived [[RPE]] cells from 1- and 12-month cultures. We differentiated the human embryonic stem cell line H9 into [[RPE]] cells, performed single-cell RNA-sequencing of a total of 16,576 cells to assess the molecular changes of the [[RPE]] cells across these two culture time points. Our results indicate the stability of the [[RPE]] transcriptomic signature, with no evidence of an epithelial-mesenchymal transition, and with the maturing populations of the [[RPE]] observed with time in culture. Assessment of Gene Ontology pathways revealed that as the cultures age, [[RPE]] cells upregulate expression of genes involved in metal binding and antioxidant functions. This might reflect an increased ability to handle oxidative stress as cells mature. Comparison with native human [[RPE]] data confirms a maturing transcriptional profile of [[RPE]] cells in culture. These results suggest that long-term in vitro culture of [[RPE]] cells allows the modelling of specific phenotypes observed in native mature tissues. Our work highlights the transcriptional landscape of hPSC-derived [[RPE]] cells as they age in culture, which provides a reference for native and patient samples to be benchmarked against.
|mesh-terms=* Aging
* Longevity
|keywords=* Aging
* Human embryonic stem cell
* Human pluripotent stem cell
* Retinal pigment epithelium
* Single-cell RNA sequencing
|full-text-url=https://sci-hub.do/10.1016/j.gpb.2020.08.002
}}
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