Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns

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...

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Vydané v:Cell Ročník 171; číslo 2; s. 321
Hlavní autori: Enge, Martin, Arda, H Efsun, Mignardi, Marco, Beausang, John, Bottino, Rita, Kim, Seung K, Quake, Stephen R
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 05.10.2017
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ISSN:1097-4172, 1097-4172
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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.
AbstractList 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.
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.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.
Author Beausang, John
Mignardi, Marco
Quake, Stephen R
Enge, Martin
Bottino, Rita
Arda, H Efsun
Kim, Seung K
Author_xml – sequence: 1
  givenname: Martin
  surname: Enge
  fullname: Enge, Martin
  organization: Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA
– sequence: 2
  givenname: H Efsun
  surname: Arda
  fullname: Arda, H Efsun
  organization: Department of Developmental Biology, Stanford University School of Medicine, CA 94305, USA
– sequence: 3
  givenname: Marco
  surname: Mignardi
  fullname: Mignardi, Marco
  organization: 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
– sequence: 4
  givenname: John
  surname: Beausang
  fullname: Beausang, John
  organization: Department of Bioengineering and Applied Physics, Stanford University, Stanford, CA 94305, USA
– sequence: 5
  givenname: Rita
  surname: Bottino
  fullname: Bottino, Rita
  organization: Institute of Cellular Therapeutics, Allegheny Health Network, 320 East North Avenue, Pittsburgh, PA 15212, USA
– sequence: 6
  givenname: Seung K
  surname: Kim
  fullname: Kim, Seung K
  organization: Department of Developmental Biology, Stanford University School of Medicine, CA 94305, USA
– sequence: 7
  givenname: Stephen R
  surname: Quake
  fullname: Quake, Stephen R
  email: quake@stanford.edu
  organization: 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
BackLink https://www.ncbi.nlm.nih.gov/pubmed/28965763$$D View this record in MEDLINE/PubMed
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Keywords insulin
mutational signatures
human aging
transcriptional instability
glucagon
single-cell RNA-seq
islet
somatic variation
human pancreas
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Snippet As organisms age, cells accumulate genetic and epigenetic errors that eventually lead to impaired organ function or catastrophic transformation such as cancer....
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SubjectTerms Adult
Aging - pathology
Cellular Senescence
Child
Child, Preschool
Humans
Infant
Middle Aged
Mutation
Pancreas - cytology
Pancreas - pathology
Pancreas - physiology
Polymorphism, Single Nucleotide
Sequence Analysis, RNA
Single-Cell Analysis
Transcription, Genetic
Title Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns
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