An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome
Hormones mediate long-range cell communication in multicellular organisms and play vital roles in normal physiology, metabolism, and health. Using the newly-completed organism-wide single cell transcriptional atlas of a non-human primate, the mouse lemur (Microcebus murinus), we have systematically identified hormone-producing and -target cells for 84 classes of hormones, and have created a browsable atlas for hormone signaling that reveals previously unreported sites of hormone regulation and species-specific rewiring. Hormone ligands and receptors exhibited cell-type-dependent, stereotypical expression patterns, and their transcriptional profiles faithfully classified the molecular cell type identities, despite their comprising less than 1% of the transcriptome. Cells of similar cell types further display stage, subtype or organ-dependent specification of hormonal signaling, reflecting the precise control of global hormonal regulation. By linking ligand-expressing cells to the cells expressing the corresponding receptor, we constructed an organism-wide map of the hormonal cell communication network. This network was remarkably densely and robustly connected and included a myriad of feedback circuits. Although it includes classical hierarchical circuits (e.g. pituitary [->] peripheral endocrine gland [->] diverse cell types), the hormonal network is overall highly distributed without obvious network hubs or axes. Cross-species comparisons among humans, lemurs, and mice suggest that the mouse lemur better models human hormonal signaling, than does the mouse. Hormonal genes show a higher evolutionary conservation between human and lemur vs. human and mouse at both the genomic level (orthology-mapping and sequence identity) and the transcriptional level (cell type expression patterns). This primate hormone atlas provides a powerful resource to facilitate discovery of regulation on an organism-wide scale and at single-cell resolution, complementing the single-site-focused strategy of classical endocrine studies. The network nature of hormone regulation and the principles discovered here further emphasize the importance of a systems approach to understanding hormone regulation.