Abstract
Population genetics has been successful in explaining how drift, selection, and mutation shape allele frequencies. However, we still lack an understanding of how biological and evolutionary constraints arising from genotype-phenotype maps shape evolutionary dynamics. To explore this question, we developed a new framework for simulating the evolution of an inherently polygenic and epistatic trait - metabolism - combining population genetics with flux balance analysis. We found that the evolution of metabolic networks exhibits surprisingly simple, reproducible dynamics. We identify evolutionary collective modes (EvCMs) - linear combinations of genes with high, constant selective pressure - as organizers of the long-term dynamics and the origin of this simplicity. EvCMs arise through the interaction of physical constraints, evolvability, and the requirements for growth. We developed a theoretical framework to predict EvCMs from large-scale metabolic models and found quantitative agreement between theory and simulation of E. coli central metabolism. Inspired by these results, we re-analyzed mutational data from Lenski's long-term evolution experiment and found compelling evidence for the existence of EvCMs. This work suggests that biological constraints encoded in genotype-phenotype maps play an important role in shaping evolutionary dynamics, offering a new perspective on complex trait evolution - one that shifts focus from individual genes to collective modes.