2022
DOI: 10.3390/life12010067
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Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Abstract: Skin is a complex and heterogeneous organ at the cellular level. This complexity is beginning to be understood through the application of single-cell genomics and computational tools. A large number of datasets that shed light on how the different human skin cell types interact in homeostasis—and what ceases to work in diverse dermatological diseases—have been generated and are publicly available. However, translation of these novel aspects to the clinic is lacking. This review aims to summarize the state-of-t… Show more

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Cited by 7 publications
(4 citation statements)
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References 127 publications
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“…Although the new approach is enabled by the recent scRNA-seq technology, the limitations of the new technology should be carefully considered for translating the results into biologic understandings ( 61 ). Current single-cell technologies offer limited number of cells that can be processed at a time and a limited number of mRNA molecules can be captured per cell ( 62 , 63 ).…”
Section: Discussionmentioning
confidence: 99%
“…Although the new approach is enabled by the recent scRNA-seq technology, the limitations of the new technology should be carefully considered for translating the results into biologic understandings ( 61 ). Current single-cell technologies offer limited number of cells that can be processed at a time and a limited number of mRNA molecules can be captured per cell ( 62 , 63 ).…”
Section: Discussionmentioning
confidence: 99%
“…It is currently being used extensively in the field of keloid research ( Onoufriadis et al, 2018 ; Matsumoto et al, 2020 ). Single-cell RNA sequencing (RNA-seq) allows the transcriptome level of a large number of cells to be studied at single-cell resolution and has been applied to the study of the mechanisms of keloid formation ( Xie et al, 2021a ; Ascensión et al, 2022 ). A recent study used the single cell transcriptome to identify four main subpopulations of keloid fibroblasts, secretory papillae, secretory reticulocytes, mesenchymal cells and pro-inflammatory cells.…”
Section: Introductionmentioning
confidence: 99%
“…Biologically, this is mostly due to posttranslational modifications, RNA silencing or different half‐lives of proteins and RNA that affect cell physiology, and transcriptomics analyses are blind to them. A mechanistic understanding of both mRNA and protein is needed to interpret such data as best as possible [131]. The scarce nature of datasets and the massive amount of data make the computational aspect challenging.…”
Section: The Trade‐offs Of Single‐cell Sequencingmentioning
confidence: 99%