Transcriptomics

Dataset Information

0

Single cell RNA-seq of CRX+ cells obtained at day 90 of retinal organoid differentiation


ABSTRACT: Death of photoreceptors and/or Retinal Pigment Epithelium (RPE) cells is a common cause of age related and inherited retinal dystrophies, thus their replenishment from renewable stem cell sources is a well sought therapeutic goal. Human pluripotent stem cells provide a useful cell source in view of their limitless self-renewal capacity and potential to differentiate into all key retinal cell types either in isolation or as part of three dimensional retinal organoids. Photoreceptor precursors have been isolated from differentiating human pluripotent stem cells either through application of cell surface markers or fluorescent reporter approaches and shown to share a transcriptional profile akin to foetal photoreceptors. In this study we investigated the transcriptional profile of CRX+ photoreceptor precursors derived from human embryonic stem cells (hESC) using single cell RNA sequencing and their engraftment capacity in an animal model of retinitis pigmentosa (C3H/rd1). Single cell RNA seq analysis revealed the presence of dominant cell cluster which displayed the hallmarks of early cone photoreceptor expression. When transplanted subretinally into the C3H/rd1 mice, the Crx positive cells settled next to the inner nuclear layer of host retina, matured into cone photoreceptors and made connections with the inner neurones of the host retina. Cellular transfer between the host retina and donor photoreceptors was investigated and shown to be minimal. Together our data provide valuable molecular insights into the transcriptional profile of human pluripotent stem cells derived CRX+ photoreceptor precursors and indicate their usefulness as a source of transplantable cone photoreceptors.

ORGANISM(S): Homo sapiens

PROVIDER: GSE112507 | GEO | 2019/04/01

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2015-08-03 | GSE67645 | GEO
2006-08-18 | GSE5338 | GEO
2008-06-13 | E-GEOD-5338 | biostudies-arrayexpress
2015-08-03 | E-GEOD-67645 | biostudies-arrayexpress
2012-11-02 | E-GEOD-41821 | biostudies-arrayexpress
2010-12-25 | E-GEOD-25607 | biostudies-arrayexpress
2023-05-10 | GSE197847 | GEO
2012-11-02 | GSE41821 | GEO
2018-04-20 | E-MTAB-6057 | biostudies-arrayexpress
2023-01-01 | GSE207802 | GEO