Groups of organisms including animals, plants, and even microbes can often accomplish tasks together that individuals cannot do alone. However, individuals who do not help their neighbors erode the benefits of group living, which can destabilize the group. In the long run, the balance of these forces leads some populations and species to live in complex groups while others live solitary lives. Examples of species living in complex groups include ant and bee colonies, hyena clans, and human societies. Mathematical tools from evolutionary biology and economics have been used to predict when the benefits of group living might outweigh the costs. Although these predictions can explain broad patterns across the tree of life, they have not been updated to incorporate recent advances in DNA technology. These advances have revolutionized how scientists understand the influence of genes on human disease and have also helped biologists link genes to social behavior and the propensity to act cooperatively in groups in many different animals species. This research will develop new mathematical and computational tools for the scientific community that will explicitly incorporate these data so that biologists can better understand the history and function of genes that affect social behavior and group living. This knowledge will not only shed light on the evolutionary origins of cooperation and conflict, it will help biologists dissect the genetic basis of group living, which is important for understanding the mechanisms by which changes in the social environment might negatively impact human health. Students of all ages will be supported by this research and gain important mathematical and computational training.
This research will bridge evolutionary theory for social behavior with population genomics by creating new mathematical and computational tools that specifically address the role of genetic linkage, recombination, and epistasis in the evolution of complex social traits. These tools will include: (i) new population genetic methods and simulation tools for evaluating the role of reduced recombination in enhancing the evolution of cooperation; this could be a precursor to the evolution of "super genes" found in a number of social species; (ii) new methods for studying the coevolution of multiple traits and recombination itself, which will allow the study of the long-term evolution of supergenes; and (iii) new simulation approaches for investigating how gene regulatory interactions evolve when those genes underlie social traits, which will allow a better understanding of how social behavior affects the evolution of gene networks. High school students, undergraduates, graduate students, and a postdoctoral fellow will benefit from this research. This award was co-funded by Evolutionary Processes in the Division of Environmental Biology, Behavioral Systems in the Division of Integrative Organismal Systems, and the Established Program to Stimulate Competitive Research (EPSCoR).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
