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
Predmet:
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
insulin
mutational signatures
human aging
transcriptional instability
glucagon
single-cell RNA-seq
islet
somatic variation
human pancreas
ISSN:1097-4172, 1097-4172
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1097-4172
1097-4172
DOI:10.1016/j.cell.2017.09.004