Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi‐omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single‐dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes. Synopsis Genetic variant effects can be described according to the spread of affected molecules across the cellular molecular network. Integrative multi‐omics analyses show how variants can shift network states in a global manner while other variant effects remain local or regional. Global changes of the cellular molecular network in response to genetic variation result from the requirement to balance the activity of diverse cellular processes. Quantification of cellular molecular network state differences due to combined PKA and TOR activity in a scalar quantity (“PT score”) captures genetically encoded and environmental variability in transcripts, proteins, and protein phosphorylation in yeast. Genetic alteration of the (PKA/TOR‐dependent) network state affects correlated and anti‐correlated protein pairs across large distances in a physical interaction network. Complex fitness traits such as thermotolerance and longevity are subject to network state alteration. Graphical Abstract Genetic variant effects can be described according to the spread of affected molecules across the cellular molecular network. Integrative multi‐omics analyses show how variants can shift network states in a global manner while other variant effects remain local or regional.