The evolutionary origins of multicellularity and development in experimental populations of digital organisms

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This project investigates fundamental questions about how evolution produces shifts in what it means to be an individual organism and how those shifts affect subsequent evolution. What is an individual organism varies greatly. With bacteria, an individual consists of a single cell, while in mammals individuals might have trillions of cells, all coordinating different roles (blood, skin, and so forth) Some species, such as the honey bee, form highly coordinated colonies (with queens, foragers, guards, and so forth) that behave like an individual organism. The evolution of previously distinct entities (cells or insects) into new types of unified individuals (bodies or colonies) are challenging to study because evolution occurs over long time scales. Instead, the researchers will use computer simulations in which they will manipulate environmental conditions to see how they promote or constrain the evolution of complex individuals. The researchers will also develop web-based software to let others easily explore these evolutionary transitions, with a goal of simplifying experimentation by fellow researchers, facilitating student learning, and promoting citizen science. This project will be divided into three conceptual stages: (1) Formation: Under what selective conditions do formerly solitary organisms unite to form a higher-level individual unit? (2) Differentiation: Once higher-level units have been formed, how do the preexisting traits of the lower-level individuals (such as phenotypic plasticity or environmental interactions) influence the evolution of division-of-labor strategies? (3) Complexification: How do different types of division-of-labor mechanisms facilitate the evolution of new, more complex features (such as developmental patterns or tightly-coordinated task performance)? The researchers will use an experimental-evolution approach with digital study organisms that operate in a 2D virtual world. Digital evolution systems allow the researchers to observe all genomes in a population, track all interactions, and record perfect phylogenies. Each digital cell has a fully-functional genetic program, theoretically capable of performing any algorithmic processes. Evolution in these systems frequently produce unexpected survival strategies with complex environmental and inter-cellular interactions, far beyond a traditional simulation. Probing the conditions that produce major transitions in an open-ended and transparent system will contribute to a deeper understanding of our natural origins, generate numerous hypotheses that can be tested concisely in laboratory experiments, and promote ideas for how computational algorithms can be produced that coordinate at a scale comparable to biological systems.