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Respiratory epithelial cell types, states and fates in the era of single-cell RNA-sequencing.
Dudchenko, Oleksandr; Ordovas-Montanes, Jose; Bingle, Colin D.
Afiliación
  • Dudchenko O; Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Sheffield, South Yorkshire, U.K.
  • Ordovas-Montanes J; Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, MA, U.S.A.
  • Bingle CD; Programme in Immunology, Harvard Medical School, Boston, MA, U.S.A.
Biochem J ; 480(13): 921-939, 2023 07 12.
Article en En | MEDLINE | ID: mdl-37410389
Standalone and consortia-led single-cell atlases of healthy and diseased human airways generated with single-cell RNA-sequencing (scRNA-seq) have ushered in a new era in respiratory research. Numerous discoveries, including the pulmonary ionocyte, potentially novel cell fates, and a diversity of cell states among common and rare epithelial cell types have highlighted the extent of cellular heterogeneity and plasticity in the respiratory tract. scRNA-seq has also played a pivotal role in our understanding of host-virus interactions in coronavirus disease 2019 (COVID-19). However, as our ability to generate large quantities of scRNA-seq data increases, along with a growing number of scRNA-seq protocols and data analysis methods, new challenges related to the contextualisation and downstream applications of insights are arising. Here, we review the fundamental concept of cellular identity from the perspective of single-cell transcriptomics in the respiratory context, drawing attention to the need to generate reference annotations and to standardise the terminology used in literature. Findings about airway epithelial cell types, states and fates obtained from scRNA-seq experiments are compared and contrasted with information accumulated through the use of conventional methods. This review attempts to discuss major opportunities and to outline some of the key limitations of the modern-day scRNA-seq that need to be addressed to enable efficient and meaningful integration of scRNA-seq data from different platforms and studies, with each other as well as with data from other high-throughput sequencing-based genomic, transcriptomic and epigenetic analyses.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Análisis de la Célula Individual / COVID-19 Límite: Humans Idioma: En Revista: Biochem J Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Análisis de la Célula Individual / COVID-19 Límite: Humans Idioma: En Revista: Biochem J Año: 2023 Tipo del documento: Article