Single-cell transcriptomics of the aged mouse brain reveals convergent, divergent and unique aging signatures

Abstract

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how the brain is affected with aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide a comprehensive dataset of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell type specific manner, even at times in opposite directions. Thus, our data reveals that aging, rather than inducing a universal program drives a distinct transcriptional course in each cell population. These data provide an important resource for the aging community and highlight key molecular processes, including ribosomal biogenesis, underlying aging. We believe that this large-scale dataset, which is publicly accessible online (aging-mouse-brain), will facilitate additional discoveries directed towards understanding and modifying the aging process.

Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures Revision 1

“…Perhaps more strikingly, a bimodal pattern is apparent, in the sense that the aging-related genes tend to have a consistent direction of change during aging across most tissue-cell types. Interestingly, it was also recently reported in other studies that many shared aging-related genes exhibit consistent direction of change during aging across mouse tissues and cell types, including the brain 66 , kidney, lung, and spleen 23 .…”

The variability of expression of many genes and most functional pathways is observed to increase with age in brain transcriptome data

“…Hypothesis-driven studies mostly show an increase in variability for the genes measured [7,8,16], whereas Warren et al [20] suggests this might be specific only to the nonrenewing tissues. Similarly, Ximerakis et al [14] shows that change in transcription variability is in different directions in different cell types of mouse brain. The reports also vary in terms of the functional association of this variability.…”

“…The change in variability could also stem from the change in gene expression levels. Although not replicated in mouse brain [14], Davie et al [12] shows that ageing leads to an overall decrease in the RNA content, which could also be the reason for such a global increase in the expression variability. However, we apply log2 transformation, which attempts to correct the meanvariability dependence.…”

“…Researchers have observed an age-related increase in variability in the epigenome [4,5] and transcriptome [6] of genetically identical samples, which may underlie the phenotypic differences. Age-related expression variability has been detected in many different cell and tissue types including mice stem cells, cardiomyocytes and immune cells [7][8][9], rat neural retina [10], fruit-fly, mice and human brain [6,[11][12][13][14] as well as human pancreas, lung, blood, skin, fat and human fibroblasts in vitro [13,[15][16][17]. Despite these reports, there is no agreement on the underlying mechanisms, extent and functional consequences.…”

A Microglial Subset at the Tumor-Stroma Interface of Glioma

“…Microglial transcriptomes are known to be influenced by aging, and P2RY12 has been shown to be significantly downregulated with age, however, direct phenotypic effects of these changes have not been adequately studied [64][65][66] . As age is a primary clinical covariate in HGG, the patterns and consequences of microglial P2RY12 expression and resulting GAM phenotypes need further investigation 67,68 .…”