Time-resolved functional genomics using deep learning reveals global hierarchical control of autophagy

Recycling of cellular components through autophagy maintains homeostasis in changing nutrient environments. Although its core mechanisms are extensively studied, understanding of its systems-wide dynamic regulation remains limited, particularly regarding how autophagy is inactivated once nutrients are restored. Here we mapped the genetic network that controls activation and inactivation of autophagy during nitrogen changes by combining time-resolved high-content imaging, deep learning and latent feature analysis. This dataset, termed AutoDRY, categorizes 5,919 mutants based on nutrient response kinetics and their contributions to autophagosome formation and clearance. Integrating these profiles with functional and genetic network data uncovered hierarchical and multilayered control of autophagy and revealed multiple new regulatory pathways. Notably, we identified the retrograde pathway as a pivotal time-varying modulator that tunes the expression of core autophagy genes and plays a central role in autophagy inactivation. Together, this study establishes a systems-level resource to guide future investigations of autophagy.