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

Abstract

SUMMARY 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.

Tissue aging: the integration of collective and variant responses of cells to entropic forces over time

“…The magnitude of response of the genes that are crucial for activation in naïve CD4 T-cells was found to be age-dependent, with reduced activation in older mice and increased cell-to-cell transcriptional variability with age[37]. In a human cohort whose ages ranged across six decades, pancreatic cells had increased transcriptional variation in the older subjects independent of cell composition, and these cells underwent fate drift where fractions of α- and β-cells with atypic hormone expression increased with age[38]. Increases in transcriptional variability (Figure 2b) and in compositional variability, either via shift in lineage bias or fate drift (Figure 2c), and the loss of stratification via aberrant timing and/or spatial localization of expression (Figure 2d, bottom panel) with age illustrate how increases in molecular noise can lead to aberrant phenotypes and function.…”

A Chromatin Basis for Cell Lineage and Disease Risk in the Human Pancreas

“…Recent progress has been made in identifying human pancreatic cell transcriptomes and epigenetic features like histone modifications (Arda et al, 2016; Bramswig et al, 2013; Enge et al 2017; Gaulton et al, 2010; Parker et al, 2013; Pasquali et al, 2014; Thurner et al, 2018; Varshney et al, 2017; reviewed by Grapin-Botton and Serup, 2017). The advances in those studies derive from powerful high-throughput sequencing approaches like RNA-Seq (Mortazavi et al, 2008), ChIP-Seq (Johnson et al, 2007) and ATAC-Seq (Buenrostro et al, 2013).…”

Northstar enables automatic classification of known and novel cell types from tumor samples

“…Briefly, tumors were surgically resected at Stanford hospital from patients with diagnosed pancreatic cancer and dissociated into single-cell suspensions (see Methods ). Single cells were isolated by fluorescence-activated cell sorting (FACS) into 96-or 384-well microtiter plates and processed as described previously [5,17] .…”

“…Single-cell approaches are also transforming our understanding of disease and physiological perturbations [2] . As atlas data across species [3] , tissues [4][5][6][7][8] , development [9] , and aging [5,10] are being amassed, there is growing demand for computational tools that leverage cell atlases to guide the analysis of new single-cell datasets. In particular, there is an unmet need for annotation tools that classify new cells based on cell type annotations found in a cell atlas.…”