生物
转录组
电池类型
细胞
计算生物学
疾病
染色质
人口
发病机制
阿尔茨海默病
遗传学
神经科学
生物信息学
基因
基因表达
病理
免疫学
医学
环境卫生
作者
Andras Sziraki,Ziyu Lu,Jasper Lee,Gábor Bányai,Sonya Anderson,Abdulraouf Abdulraouf,Eli Metzner,Andrew Liao,Jason R. Banfelder,Alexander E. Epstein,Chloe Schaefer,Zihan Xu,Zehao Zhang,Li Gan,Peter T. Nelson,Wei Zhou,Junyue Cao
出处
期刊:Nature Genetics
[Nature Portfolio]
日期:2023-11-30
卷期号:55 (12): 2104-2116
被引量:78
标识
DOI:10.1038/s41588-023-01572-y
摘要
Conventional methods fall short in unraveling the dynamics of rare cell types related to aging and diseases. Here we introduce EasySci, an advanced single-cell combinatorial indexing strategy for exploring age-dependent cellular dynamics in the mammalian brain. Profiling approximately 1.5 million single-cell transcriptomes and 400,000 chromatin accessibility profiles across diverse mouse brains, we identified over 300 cell subtypes, uncovering their molecular characteristics and spatial locations. This comprehensive view elucidates rare cell types expanded or depleted upon aging. We also investigated cell-type-specific responses to genetic alterations linked to Alzheimer's disease, identifying associated rare cell types. Additionally, by profiling 118,240 human brain single-cell transcriptomes, we discerned cell- and region-specific transcriptomic changes tied to Alzheimer's pathogenesis. In conclusion, this research offers a valuable resource for probing cell-type-specific dynamics in both normal and pathological aging.
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