The longitudinal single-cell panorama of cynomolgus monkey ovary throughout lifespan revealed a conserved ovarian clock between primates

Abstract

AbstractOvarian function is critical for female fertility and impacts reproductive longevity. It is of great importance to accurately predict the aging process within the ovary for fertility assessment and disease diagnosis. However, cell metrics for evaluating the ovarian aging rate are still in urgent need, and molecular insights into ovarian development and dysfunction during the primate life course are also limited. Here, we reported large-scale ovarian cell atlas of consecutive development of cynomolgus monkeys across 22 years with 20 time points, covering the foetal, newborn, prepubertal, pubertal, adult, perimenopausal and menopausal stages. We characterized and validated distinct molecular signatures of each cluster of cells within primate ovaries, and uncovered a previously undocumented RHOXF1-positive oocyte type during primordial follicle assembly in primates. Furthermore, the constitution and developmental trajectories of primate germ cells, granulosa cells and stromal / theca cells were also elucidated, and their precursors were identified. More importantly, dynamics of cellular compositions were unravelled through the ovarian development, featured by granulosa, epithelial, stromal, and immune cells that showed strong temporal heterogeneity spanning lifetime, whilst referred to the key function during the corresponding stages. Based on the correlations of each cell type with age and stage-specific molecular dynamics, we further constructed a transcriptomic ovarian clock which could perceive an effective biological age prediction of the ovary and further applied to humans. The findings reveal granulosa, epithelial, and stromal cells as the highest performance predictors of ovarian biological age, while highlighting the crucial role of AGE-RAGE and Relaxin signaling pathways in regulating ovarian aging. Our work not only provide valuable resource for obtaining insights into the development, aging and dysfunction of key organs, but also establish a transcriptomic clock to predict biological ovarian aging thus to be potential clinical implementation in future.