Developmental processes are thought to be highly complex, but there have been few attempts to measure and compare such complexity across different groups of organisms. Here we introduce a measure of biological complexity based on the similarity between developmental and computer programs. We define the algorithmic complexity of a cell lineage as the length of the shortest description of the lineage based on its constituent sublineages. We then use this measure to estimate the complexity of the embryonic lineages of four metazoan species from two different phyla. We find that these cell lineages are significantly simpler than would be expected by chance. Furthermore, evolutionary simulations show that the complexity of the embryonic lineages surveyed is near that of the simplest lineages evolvable, assuming strong developmental constraints on the spatial positions of cells and stabilizing selection on cell number. We propose that selection for decreased complexity has played a major role in moulding metazoan cell lineages.

The program can run on any operating system with a compliant Java 2 environment. Ales is free for academic use and can be downloaded from http://mbi.dkfz-heidelberg.de/mbi/research/cellsim/ales.