Genetic Code Population Dynamics in a Simulated System of Protocells

An evolutionary algorithm was developed to investigate how the biological genetic code may have evolved. Graph theoretical "degree sequences " were derived from the simulated genetic codes of "organisms " produced by this algorithm. These graph theory metrics were used as a measure of similarity among evolving genetic codes, in order to classify the set of organisms into equivalence classes without requiring absolute identity. A detailed look at the population dynamics of these sequences revealed patterns in the rise and fall of specific sequences reminiscent of the succession of biological species. A new sequence first appears in small numbers, may become dominant for a time, but then fades away in the process of giving way to another, more "fit" sequence. The “fit ” sequences are the remaining survivors after fidelity, tRNA, and stem loop rate selection. Except for a few scattered sequences that were accidentally reproduced in the first generation of entirely random genetic codes, these matching sequences frequently turned out to belong to offspring of a single "primordial " organism, as replicated during the genetic algorithm simulations