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RNA splicing programs define tissue compartments and cell types at single-cell resolution.
Olivieri, Julia Eve; Dehghannasiri, Roozbeh; Wang, Peter L; Jang, SoRi; de Morree, Antoine; Tan, Serena Y; Ming, Jingsi; Ruohao Wu, Angela; Quake, Stephen R; Krasnow, Mark A; Salzman, Julia.
  • Olivieri JE; Institute for Computational and Mathematical Engineering, Stanford University, Stanford, United States.
  • Dehghannasiri R; Department of Biomedical Data Science, Stanford University, Stanford, United States.
  • Wang PL; Department of Biochemistry, Stanford University, Stanford, United States.
  • Jang S; Department of Biomedical Data Science, Stanford University, Stanford, United States.
  • de Morree A; Department of Biochemistry, Stanford University, Stanford, United States.
  • Tan SY; Department of Biochemistry, Stanford University, Stanford, United States.
  • Ming J; Department of Biochemistry, Stanford University, Stanford, United States.
  • Ruohao Wu A; Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, United States.
  • Quake SR; Academy for Statistics and Interdisciplinary Sciences, Faculty of Economics and Management,East China Normal University, Shanghai, China.
  • Krasnow MA; Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China.
  • Salzman J; Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
Elife ; 102021 09 13.
Article en En | MEDLINE | ID: mdl-34515025
ABSTRACT
The extent splicing is regulated at single-cell resolution has remained controversial due to both available data and methods to interpret it. We apply the SpliZ, a new statistical approach, to detect cell-type-specific splicing in >110K cells from 12 human tissues. Using 10X Chromium data for discovery, 9.1% of genes with computable SpliZ scores are cell-type-specifically spliced, including ubiquitously expressed genes MYL6 and RPS24. These results are validated with RNA FISH, single-cell PCR, and Smart-seq2. SpliZ analysis reveals 170 genes with regulated splicing during human spermatogenesis, including examples conserved in mouse and mouse lemur. The SpliZ allows model-based identification of subpopulations indistinguishable based on gene expression, illustrated by subpopulation-specific splicing of classical monocytes involving an ultraconserved exon in SAT1. Together, this analysis of differential splicing across multiple organs establishes that splicing is regulated cell-type-specifically.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Empalme del ARN / Cheirogaleidae / Análisis de la Célula Individual / Ratones Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Empalme del ARN / Cheirogaleidae / Análisis de la Célula Individual / Ratones Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Año: 2021 Tipo del documento: Article