Self-organization in the ontogeny of multicellular organisms: A computer simulation

Abstract

Advances in understanding patterns in the evolution of the ontogeny of multicellular organisms are hindered by the fact that many features of ontogeny are counterintuitive (as are the features of other processes associated with self-organization, self-assembly, and spontaneous increase in complexity). The basic principle of ontogeny of multicellular organisms is that it is the process of self-assembly of ordered multicellular structures by means of coordinated behavior of many individual modules (cells), each of which follows the same set of “rules for behavior” encoded in the genome. These rules are based on the gene regulatory networks. We hypothesize that many specific features of ontogeny that seem nontrivial or enigmatic are in fact the inevitable consequences of this basic principle. If so, they do not require any special explanations. To verify this hypothesis, we have developed a computer program named Evo-Devo, which is based on the above principle. The program is designed to model the self-assembly of ordered multicellular structures from a set of dividing cells. Each cell follows a set of rules for behavior (“genotype”) that can be arbitrarily specified by the experimenter but should be the same for all cells in an embryo (each cell is initially programmed in exactly the same way as all the other cells). It is prohibited to specify rules for groups of cells or for the whole embryo: only local rules that are true at the level of a single cell are permitted. Analysis of a phenotypic implementation of different genotypes allowed the detection of several features characteristic of the ontogeny of real organisms which were regularly reproduced in simulation. These features include inherent stochasticity, a default characteristic of the ontogeny; the necessity of stabilizing adaptations involving negative feedbacks and decreasing the stochasticity of ontogeny; equifinality (noise resistance) resulting from these adaptations; the ability of ontogeny to respond to major perturbations by generating new morphological structures that differ from the “normal” ones but have a similar level of complexity; similar phenotypic manifestations of different mutations; canalization of possible evolutionary transformations of ontogeny (existence of creods); high probability of destabilization of ontogeny (in particular, due to mutations); potential emergence of novel morphological characteristics, initially as a rare abnormality (a low penetrance of many mutations); pleiotropy of mutations influencing the ontogeny; spontaneous emergence of morphogenetic correlations; and integrity of the developing organism. The fact that these features are regularly reproduced in the model suggests that they are likely the inevitable consequences of the basic principle of ontogeny of multicellular organisms formulated above.