Niche signals maintain stem cells in a prolonged quiescence or transiently activate them for proper regeneration¹. Altering balanced niche signalling can lead to regenerative disorders. Melanocytic skin nevi in human often display excessive hair growth, suggesting hair stem cell hyperactivity. Here, using genetic mouse models of nevi^2,3, we show that dermal clusters of senescent melanocytes drive epithelial hair stem cells to exit quiescence and change their transcriptome and composition, potently enhancing hair renewal. Nevus melanocytes activate a distinct secretome, enriched for signalling factors. Osteopontin, the leading nevus signalling factor, is both necessary and sufficient to induce hair growth. Injection of osteopontin or its genetic overexpression is sufficient to induce robust hair growth in mice, whereas germline and conditional deletions of either osteopontin or CD44, its cognate receptor on epithelial hair cells, rescue enhanced hair growth induced by dermal nevus melanocytes. Osteopontin is overexpressed in human hairy nevi, and it stimulates new growth of human hair follicles. Although broad accumulation of senescent cells, such as upon ageing or genotoxic stress, is detrimental for the regenerative capacity of tissue⁴, we show that signalling by senescent cell clusters can potently enhance the activity of adjacent intact stem cells and stimulate tissue renewal. This finding identifies senescent cells and their secretome as an attractive therapeutic target in regenerative disorders.

Lateral flight membranes, or patagia, have evolved repeatedly in diverse mammalian lineages. While little is known about patagium development, its recurrent evolution may suggest a shared molecular basis. By combining transcriptomics, developmental experiments, and mouse transgenics, we demonstrate that lateral Wnt5a expression in the marsupial sugar glider ( Petaurus breviceps ) promotes the differentiation of its patagium primordium. We further show that this function of Wnt5a reprises ancestral roles in skin morphogenesis predating mammalian flight and has been convergently used during patagium evolution in eutherian bats. Moreover, we find that many genes involved in limb development have been redeployed during patagium outgrowth in both the sugar glider and bat. Together, our findings reveal that deeply conserved genetic toolkits contribute to the evolutionary transition to flight in mammals.

Tissue development and homeostasis require coordinated cell–cell communication. Recent advances in single-cell sequencing technologies have emerged as a revolutionary method to reveal cellular heterogeneity with unprecedented resolution. This offers a great opportunity to explore cell–cell communication in tissues systematically and comprehensively, and to further identify signaling mechanisms driving cell fate decisions and shaping tissue phenotypes. Using gene expression information from single-cell transcriptomics, several computational tools have been developed for inferring cell–cell communication, greatly facilitating analysis and interpretation. However, in single-cell transcriptomics, spatial information of cells is inherently lost. Given that most cell signaling events occur within a limited distance in tissues, incorporating spatial information into cell–cell communication analysis is critical for understanding tissue organization and function. Spatial transcriptomics provides spatial location of cell subsets along with their gene expression, leading to new directions for leveraging spatial information to develop computational approaches for cell–cell communication inference and analysis. These computational approaches have been successfully applied to uncover previously unrecognized mechanisms of intercellular communication within various contexts and across organ systems, including the skin, a formidable model to study mechanisms of cell–cell communication due to the complex interactions between the different cell populations that comprise it. Here, we review emergent cell–cell communication inference tools using single-cell transcriptomics and spatial transcriptomics, and highlight the biological insights gained by applying these computational tools to exploring cellular communication in skin development, homeostasis, disease and aging, as well as discuss future potential research avenues.

Single-cell technologies have become essential to driving discovery in both basic and translational investigative dermatology. Despite the multitude of available datasets, a central reference atlas of normal human skin, which can serve as a reference resource for skin cell types, cell states, and their molecular signatures, is still lacking. For any such atlas to receive broad acceptance, participation by many investigators during atlas construction is an essential prerequisite. As part of the Human Cell Atlas project, we have assembled a Skin Biological Network to build a consensus Human Skin Cell Atlas and outline a roadmap toward that goal. We define the drivers of skin diversity to be considered when selecting sequencing datasets for the atlas and list practical hurdles during skin sampling that can result in data gaps and impede comprehensive representation and technical considerations for tissue processing and computational analysis, the accounting for which should minimize biases in cell type enrichments and exclusions and decrease batch effects. By outlining our goals for Atlas 1.0, we discuss how it will uncover new aspects of skin biology.