Single-cell transcriptomic profiling of the aging mouse brain

The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets 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. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process. Total of 16 mice brains with raw data for 50,212 single cells and processed data for 37,089 single cells哺乳动物大脑结构极为复杂，多种细胞类型各司其职，执行多样且迥异的生物学功能，但目前学界仍在很大程度上不明了每种细胞类型具体如何在衰老过程中受到影响。本研究对年轻与年老小鼠的大脑开展了单细胞转录组分析，构建了覆盖几乎所有脑细胞类型的衰老相关基因、信号通路以及配体-受体相互作用的综合数据集。本研究的分析结果鉴定出了在不同细胞类型间协同变化的基因特征，以及以细胞类型特异性方式调控的基因集，部分情况下二者的变化方向甚至截然相反。本数据集揭示，衰老并非诱导统一的转录调控程序，而是在每种细胞群中驱动独特的转录进程；同时还明确了脑衰老背后的关键分子过程，其中包括核糖体生物发生。总体而言，本套大规模数据集为神经科学领域提供了宝贵的研究资源，将助力后续探索与解析衰老过程的相关发现，并推动靶向调控衰老进程的研究。本研究共纳入16份小鼠脑组织样本，包含50212个单细胞的原始测序数据以及37089个单细胞的处理后数据。