Interactions between thymic epithelial cells (TEC) and developing thymocytes are essential for T cell development, but molecular insights on TEC and thymus homeostasis are still lacking. Here we identify distinct transcriptional programs of TEC that account for their age-specific properties, including proliferation rates, engraftability and function. Further analyses identify Myc as a regulator of fetal thymus development to support the rapid increase of thymus size during fetal life. Enforced Myc expression in TEC induces the prolonged maintenance of a fetal-specific transcriptional program, which in turn extends the growth phase of the thymus and enhances thymic output; meanwhile, inducible expression of Myc in adult TEC similarly promotes thymic growth. Mechanistically, this Myc function is associated with enhanced ribosomal biogenesis in TEC. Our study thus identifies age-specific transcriptional programs in TEC, and establishes that Myc controls thymus size.

Alternative splicing contributes to phenotypic diversity at multiple biological scales, and its dysregulation is implicated in both ageing and age-associated diseases in human. Cross-tissue variability in splicing further complicates its links to age-associated phenotypes and elucidating these links requires a comprehensive map of age-associated splicing changes across multiple tissues. Here, we generate such a map by analyzing ~8500 RNA-seq samples across 48 tissues in 544 individuals. Employing a stringent model controlling for multiple confounders, we identify 49,869 tissue-specific age-associated splicing events of 7 distinct types. We find that genome-wide splicing profile is a better predictor of biological age than the gene and transcript expression profiles, and furthermore, age-associated splicing provides additional independent contribution to age-associated complex diseases. We show that the age-associated splicing changes may be explained, in part, by concomitant age-associated changes of the upstream splicing factors. Finally, we show that our splicing-based model of age can successfully predict the relative ages of cells in 8 of the 10 paired longitudinal data as well as in 2 sets of cell passage data. Our study presents the first systematic investigation of age-associated splicing changes across tissues, and further strengthening the links between age-associated splicing and age-associated diseases.