555 Dermal single-cell atlas: a novel tool to explore fibroblast heterogeneity

Dermal fibroblasts are transcriptomically heterogeneous. In spite of numerous single-cell RNA sequencing (scRNAseq) studies dedicated to decipher fibroblast heterogeneity, previous approaches lack sufficient insight and do not establish a bridge between mouse human data. We aimed obtain comprehensive map mouseskin from pre-existing To this end, 30 independent scRNAseq datasets (22 including dermal 8 skin) were subjected customized computational pipeline robust cell subpopulations that constant across datasets, alongside their marker genes. analysis, we defined total 15 populations divided into 5 main axes (A-E) in 17 (a-e) datasets. Interestingly, most these clusters consistent, meaning they appeared throughout the with no meaningful population remaining unlabelled. Further, comparison reveals that, despite intrinsic differences rodent skin, many cases one-to-one correspondence species may be found partial overlap cluster-defining markers, perhaps suggesting comparable functionsof particular species. Thereby, able capture discrete heterogeneity fibroblasts, using specific markers. This atlas is useful tool for establishing detailed annotation subpopulations, as well deepening functions each subtype advantage providing tools cross-species comparisons.