The platform will undergo maintenance on Sep 14 at about 7:45 AM EST and will be unavailable for approximately 2 hours.
2017
DOI: 10.1016/j.stemcr.2017.10.018
|View full text |Cite
|
Sign up to set email alerts
|

Isolation and Comparative Transcriptome Analysis of Human Fetal and iPSC-Derived Cone Photoreceptor Cells

Abstract: SummaryLoss of cone photoreceptors, crucial for daylight vision, has the greatest impact on sight in retinal degeneration. Transplantation of stem cell-derived L/M-opsin cones, which form 90% of the human cone population, could provide a feasible therapy to restore vision. However, transcriptomic similarities between fetal and stem cell-derived cones remain to be defined, in addition to development of cone cell purification strategies. Here, we report an analysis of the human L/M-opsin cone photoreceptor trans… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

11
105
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
6
2

Relationship

2
6

Authors

Journals

citations
Cited by 91 publications
(124 citation statements)
references
References 51 publications
11
105
0
Order By: Relevance
“…Correlation matrix to benchmark hiPSC‐derived cone photoreceptors (week 15 and week 20; Welby et al , ), fetal cone photoreceptors (Welby et al , ), adult retina (Phillips et al , ), and the human Müller glia cell line MIO‐M1 against all retinal cell types identified in this human neural retina atlas.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Correlation matrix to benchmark hiPSC‐derived cone photoreceptors (week 15 and week 20; Welby et al , ), fetal cone photoreceptors (Welby et al , ), adult retina (Phillips et al , ), and the human Müller glia cell line MIO‐M1 against all retinal cell types identified in this human neural retina atlas.…”
Section: Resultsmentioning
confidence: 99%
“… Correlation analysis of scRNA‐seq data of hiPSC‐derived cone photoreceptors (week 15) against fetal cone photoreceptors (Welby et al , ), as well as adult cone and rod photoreceptors from this human neural retina atlas. Principal component analysis to assess transcriptome similarity of hiPSC‐derived cone photoreceptors to fetal and adult photoreceptors. t‐SNE analysis of the human Müller glia cell line MIO‐M1 with the retinal cell types identified in this human neural retina atlas. Correlation analysis of MIO‐M1 with all major human retinal cell types. Top ranked differentially expressed genes identified in MIO‐M1 compared to other retinal cell types based on logistic regression score. …”
Section: Resultsmentioning
confidence: 99%
“…For the comparison of retinal datasets, differential expression output data was obtained from each report (Kim et al, 2016;Mo et al, 2016;Welby et al). The data was cross-referenced to the genes obtained in the analysis from this paper and are detailed in Supp.…”
Section: Data Comparisonsmentioning
confidence: 99%
“…To demonstrate the use of our dataset as a benchmarking reference, we compared the scRNA-seq profiles of distinct cell types generated using alternative methods, including fetal human cone photoreceptors, human induced pluripotent stem cell derived-cone photoreceptors (hiPSC-cone; (Welby et al, 2017), and a sample of adult human retina with 139 cells (Phillips et al, 2018). Correlation analysis demonstrated that the adult human retina sample showed highest similarity to rod photoreceptor (0.63, Supplementary figure 10), which is expected as rod photoreceptors represent the majority of the cells in the retina.…”
Section: Using the Human Neural Retina Transcriptome Atlas For Benchmmentioning
confidence: 99%
“…Phillips et al have profiled a total of 139 adult retina cells using the C1 Fluidigm platform (Phillips et al, 2018), but the limited number of profiled cells presents challenges in the annotation and accurate identification of individual retinal cell types. Moreover, a flow cytometry approach was used to isolate 65 human fetal cone photoreceptors followed by scRNA-seq profiling (Welby et al, 2017).…”
Section: Introductionmentioning
confidence: 99%