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Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data

Tissue development and homeostasis require coordinated cell–cell communication. Recent advances in single-cell sequencing technologies have emerged as a revolutionary method to reveal cellular heterogeneity with unprecedented resolution. This offers a great opportunity to explore cell–cell communica...

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Autores principales: Jin, Suoqin, Ramos, Raul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022991/
https://www.ncbi.nlm.nih.gov/pubmed/35191953
http://dx.doi.org/10.1042/BST20210863
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author Jin, Suoqin
Ramos, Raul
author_facet Jin, Suoqin
Ramos, Raul
author_sort Jin, Suoqin
collection PubMed
description Tissue development and homeostasis require coordinated cell–cell communication. Recent advances in single-cell sequencing technologies have emerged as a revolutionary method to reveal cellular heterogeneity with unprecedented resolution. This offers a great opportunity to explore cell–cell communication in tissues systematically and comprehensively, and to further identify signaling mechanisms driving cell fate decisions and shaping tissue phenotypes. Using gene expression information from single-cell transcriptomics, several computational tools have been developed for inferring cell–cell communication, greatly facilitating analysis and interpretation. However, in single-cell transcriptomics, spatial information of cells is inherently lost. Given that most cell signaling events occur within a limited distance in tissues, incorporating spatial information into cell–cell communication analysis is critical for understanding tissue organization and function. Spatial transcriptomics provides spatial location of cell subsets along with their gene expression, leading to new directions for leveraging spatial information to develop computational approaches for cell–cell communication inference and analysis. These computational approaches have been successfully applied to uncover previously unrecognized mechanisms of intercellular communication within various contexts and across organ systems, including the skin, a formidable model to study mechanisms of cell–cell communication due to the complex interactions between the different cell populations that comprise it. Here, we review emergent cell–cell communication inference tools using single-cell transcriptomics and spatial transcriptomics, and highlight the biological insights gained by applying these computational tools to exploring cellular communication in skin development, homeostasis, disease and aging, as well as discuss future potential research avenues.
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spelling pubmed-90229912022-05-03 Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data Jin, Suoqin Ramos, Raul Biochem Soc Trans Review Articles Tissue development and homeostasis require coordinated cell–cell communication. Recent advances in single-cell sequencing technologies have emerged as a revolutionary method to reveal cellular heterogeneity with unprecedented resolution. This offers a great opportunity to explore cell–cell communication in tissues systematically and comprehensively, and to further identify signaling mechanisms driving cell fate decisions and shaping tissue phenotypes. Using gene expression information from single-cell transcriptomics, several computational tools have been developed for inferring cell–cell communication, greatly facilitating analysis and interpretation. However, in single-cell transcriptomics, spatial information of cells is inherently lost. Given that most cell signaling events occur within a limited distance in tissues, incorporating spatial information into cell–cell communication analysis is critical for understanding tissue organization and function. Spatial transcriptomics provides spatial location of cell subsets along with their gene expression, leading to new directions for leveraging spatial information to develop computational approaches for cell–cell communication inference and analysis. These computational approaches have been successfully applied to uncover previously unrecognized mechanisms of intercellular communication within various contexts and across organ systems, including the skin, a formidable model to study mechanisms of cell–cell communication due to the complex interactions between the different cell populations that comprise it. Here, we review emergent cell–cell communication inference tools using single-cell transcriptomics and spatial transcriptomics, and highlight the biological insights gained by applying these computational tools to exploring cellular communication in skin development, homeostasis, disease and aging, as well as discuss future potential research avenues. Portland Press Ltd. 2022-02-28 2022-02-22 /pmc/articles/PMC9022991/ /pubmed/35191953 http://dx.doi.org/10.1042/BST20210863 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Review Articles
Jin, Suoqin
Ramos, Raul
Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
title Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
title_full Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
title_fullStr Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
title_full_unstemmed Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
title_short Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
title_sort computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9022991/
https://www.ncbi.nlm.nih.gov/pubmed/35191953
http://dx.doi.org/10.1042/BST20210863
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