The Origins of Division of Labor and Developmental Complexity: Using Digital Organisms to Understand Major Transitions in Evolution

Major transitions in evolution occur when formerly distinct individuals join together in a higher-level unit that functions as a single reproductive entity. Such transitions include single cells evolving into multicellular organisms and insects forming eusocial colonies. Major transitions in evolution are challenging to study because of the slow pace of evolution and imperfect historical data. To address these challenges, I use digital organisms (populations of self-replicating computer programs that undergo open-ended evolution) to investigate questions surrounding the evolution of division of labor, a fundamental aspect of major transitions in evolution. In this talk, I will present how simple evolutionary pressures can give rise to self-organized groups of digital organisms that exhibit task-based and reproductive division of labor. In response to evolutionary pressures, some evolved groups become so dependent upon communication capabilities that they exhibit a marked loss in lower-level individuality: individuals within groups can perform tasks that no individual can perform in isolation. The simultaneous loss of functionality at a lower level and emergence of new functionality at a higher level indicates a shift in autonomy, which is a central component of major transitions in evolution. Additionally, I will present a new hypothesis regarding the evolution of reproductive division of labor, as well as experimental evidence in support of it. The "dirty-work" hypothesis states that germ-soma differentiation can evolve to mitigate a tradeoff between performing mutagenic work and conserving the genetic material that encodes the ability to perform work. Studying evolution using a tractable, computational system provides us with unprecedented access to understanding how evolutionary pressures shape the behavior of individuals, groups, and populations as they undergo major transitions in evolution.
Heather J. Goldsby received the B.S. degree in Computer Science in 2001, the M.S. degree in Computer Science in 2004, and the Ph.D. degree in Computer Science and Ecology, Evolutionary Biology, and Behavior in 2011, all from Michigan State University, East Lansing. She is currently an NSF Post-Doctoral Fellow with the Department of Biology, University of Washington, Seattle. Her current research interests include evolutionary questions surrounding cooperation, division of labor, and major transitions in evolution.