Deciphering the age-dependent changes of pulmonary fibroblasts in mice by single-cell transcriptomics

In brief, lung resident cells were isolated from lung of mice and 10x Genomics single cell RNAseq was applied to identify distinct cell populations. Low quality cells and outliers were discarded, and only ~22,826 viable cells were used for downstream analysis. These included ~5,237 cells – NB(10days mice); ~4,804 cells – Adult-M(2months mice); ~6,561cells-SD-10M (10month mice) ; ~6,224cells-SD-1d5Y (18month mice). Unsupervised clustering and gene expression were visualized with the Seurat 2.0 on R studio, and assignment of cell clusters was based on expression of validated marker genes. Subsequent in-depth analysis was assisted by GENE DENOVO Inc (Guangzhou, China). Overall, we found that a specific lung fibroblast population, We present a single-cell transcriptomic atlas encompassing lung tissues derived from mice at various stages of aging, uncovering substantial shifts in fibroblast differentiation and immune regulation throughout the aging process. Overall design: Lung biopsies were collected from 4 groups, including – NB(10days mice); – Adult-M(2months mice); SD-10M (10month mice) ; SD-1d5Y (18month mice) C57BL/6 mice.