Dynamics of genetic code evolution: The emergence of universality

A bstract We study the dynamics of genetic code evolution. The algorithm of Vetsigian et al. [1] provides a solution that is both optimal and universal. We reproduce and analyze the algorithm as a dynamical system. All the parameters used in the model are varied to assess their impact on achieving universality. We show that by allowing specific parameters to vary with time, the algorithm converges much faster to a universal solution. Finally, we study automorphisms of the genetic code arising due to this model. We use this to examine the scaling of the solutions in order to understand the origin of universality and find that there is a direct link to mutation rate.