GSE192807
Age-dependent cell stemness plasticity orchestrates postnatal functional maturity of ruminants
Newborn ruminants are considered as functionally monogastric animals. The poorly understanding of tremendous cellular differences between newborn and completely ruminating stages hinders the improvement of health and performance of domestic ruminants. Here, unbiased single-cell RNA sequencing was performed on the rumen, reticulum, omasum, abomasum, duodenum, jejunum, ileum, cecum, colon, rectum, salivary gland, liver, and mammary gland from newborn and adult cattle. We created a comprehensive single-cell transcriptomic compendium covering 235,941 high-quality single cells and 78 cell types. The age-state cell atlases for each tissue type were also constructed to delineate the cell type composition dynamics at newborn and adult stages. We further created the Cattle Cell Landscape database (http://cattlecelllandscape.zju.edu.cn) to detailly display the informative results and to facilitate in effectively annotation of cattle cell type/subtypes for the broad research community. By measuring stemness states of epithelial cells across multiple tissue types, we revealed a multi-tissue representation of paradigm of cell stemness plasticity: the newborn forestomach (rumen, reticulum, and omasum) epithelial cells are more transcriptionally indistinct and stochastic compared with adult stage, which contrary to that of abomasum and intestinal tissues. Moreover, the rapid forestomach development during the early life of calves was driven by the epithelial progenitor-like cells with high activities of epigenetic modifying. A novel cell type STOML3+ cell was found to be newborn cattle-specific that plays an important role in stemness maintenance of its own and cholangiocyte in the hepatic microenvironment. These results provide novel insights into the cellular biology and postnatal ruminating maturity of ruminants Overall design: Construction of the age-state cell atlases for 13 tissue types of cattle covering 30 single-cell RNA sequencing datasets.