Senescent cells, induced by various stressors, present a heterogenous population of irreversibly cell cycle arrested cells. They release pro-inflammatory compounds into surrounding tissue, collectively known as senescence associated secretory phenotype (SASP). Higher frequency of senescent cells is present during the developmental phase, regeneration and in aged organisms. Their accumulation during the ageing process increases risk and severity of age-related pathologies and is associated with formation of chronic wounds. Skin is a heterogenous organ and markers of senescence have been detected in several types of cells including keratinocytes, fibroblasts and melanocytes. As drugs targeting senescent cells show specificity towards selected pathways, that are known to be more active in some types of skin cells over others, it is of primary importance to decipher common and differential signatures of senescence in different populations of skin cells.
Here we present our preliminary in silico results on defining and characterizing phenotypes of senescent skin cells. We generated a database consisting of 19 studies with publicly available 10x genomics single-cell-RNA-sequencing (sc-RNA-seq) datasets of mouse skin from the developmental stage (embryonic), regeneration (wounded/unwounded) and the aging process (young, adult, old). To our knowledge this is the biggest sc-RNA seq dataset of mouse skin generated to date. Our dataset was created by harmonising and clustering readouts from all the studies (78 samples comprising 406.563 cells) in order to identify specific cell types. This dataset was used to unravel the phenotypic characteristics related to cellular senescence of different populations of mouse skin cells. Moreover, by splitting the dataset based on the presence of a known senescence marker we generated a list of gene ontology terms associated with senescent cells in skin development, homeostasis, wounding and ageing.