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Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns.
Enge, Martin; Arda, H Efsun; Mignardi, Marco; Beausang, John; Bottino, Rita; Kim, Seung K; Quake, Stephen R.
Afiliación
  • Enge M; Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA.
  • Arda HE; Department of Developmental Biology, Stanford University School of Medicine, CA 94305, USA.
  • Mignardi M; Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA; Department of Information Technology, Uppsala University, Sweden and SciLifeLab, Uppsala, Sweden SE-751 05.
  • Beausang J; Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA.
  • Bottino R; Institute of Cellular Therapeutics, Allegheny Health Network, 320 East North Avenue, Pittsburgh, PA 15212, USA.
  • Kim SK; Department of Developmental Biology, Stanford University School of Medicine, CA 94305, USA.
  • Quake SR; Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA; Institute of Cellular Therapeutics, Allegheny Health Network, 320 East North Avenue, Pittsburgh, PA 15212, USA. Electronic address: quake@stanford.edu
Cell ; 171(2): 321-330.e14, 2017 Oct 05.
Article en En | MEDLINE | ID: mdl-28965763
ABSTRACT
As organisms age, cells accumulate genetic and epigenetic errors that eventually lead to impaired organ function or catastrophic transformation such as cancer. Because aging reflects a stochastic process of increasing disorder, cells in an organ will be individually affected in different ways, thus rendering bulk analyses of postmitotic adult cells difficult to interpret. Here, we directly measure the effects of aging in human tissue by performing single-cell transcriptome analysis of 2,544 human pancreas cells from eight donors spanning six decades of life. We find that islet endocrine cells from older donors display increased levels of transcriptional noise and potential fate drift. By determining the mutational history of individual cells, we uncover a novel mutational signature in healthy aging endocrine cells. Our results demonstrate the feasibility of using single-cell RNA sequencing (RNA-seq) data from primary cells to derive insights into genetic and transcriptional processes that operate on aging human tissue.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Páncreas / Envejecimiento / Senescencia Celular / Análisis de la Célula Individual / Mutación Límite: Adult / Child / Child, preschool / Humans / Infant / Middle aged Idioma: En Año: 2017 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Páncreas / Envejecimiento / Senescencia Celular / Análisis de la Célula Individual / Mutación Límite: Adult / Child / Child, preschool / Humans / Infant / Middle aged Idioma: En Año: 2017 Tipo del documento: Article