TY - JOUR TI - Mouse aging cell atlas analysis reveals global and cell type-specific aging signatures AU - Zhang, Martin Jinye AU - Pisco, Angela Oliveira AU - Darmanis, Spyros AU - Zou, James A2 - Han, Jing-Dong Jackie A2 - Tyler, Jessica K A2 - Hou, Lei VL - 10 PY - 2021 DA - 2021/04/13 SP - e62293 C1 - eLife 2021;10:e62293 DO - 10.7554/eLife.62293 UR - https://doi.org/10.7554/eLife.62293 AB - Aging is associated with complex molecular and cellular processes that are poorly understood. Here we leveraged the Tabula Muris Senis single-cell RNA-seq data set to systematically characterize gene expression changes during aging across diverse cell types in the mouse. We identified aging-dependent genes in 76 tissue-cell types from 23 tissues and characterized both shared and tissue-cell-specific aging behaviors. We found that the aging-related genes shared by multiple tissue-cell types also change their expression congruently in the same direction during aging in most tissue-cell types, suggesting a coordinated global aging behavior at the organismal level. Scoring cells based on these shared aging genes allowed us to contrast the aging status of different tissues and cell types from a transcriptomic perspective. In addition, we identified genes that exhibit age-related expression changes specific to each functional category of tissue-cell types. Altogether, our analyses provide one of the most comprehensive and systematic characterizations of the molecular signatures of aging across diverse tissue-cell types in a mammalian system. KW - single cell KW - aging KW - computation JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -