Aggression evolving: understanding how social interactions create evolutionary feedbacks at the behavioral and genomic levels

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Predicting evolution over multiple generations is one of the central goals of modern biology, with applications in agriculture, conservation, and human health. Predicting the evolution of behavior presents special challenges, because behavior often depends not only on the individual doing the behavior (and its genes), but also on other interacting individuals (and their genes). Such complex social behaviors may thus evolve in unique ways, termed evolutionary feedbacks. Although evolutionary feedbacks are believed to be widespread, little is still known about how they work to shape evolution over time. In this project, the researcher will take advantage of a powerful model system (fruit flies, Drosophila melanogaster), to directly observe evolutionary feedbacks for aggressive behavior as they are happening over multiple generations in the lab. The research team will evolve highly-aggressive fruit flies under circumstances in which feedbacks are allowed or restricted. This will allow the team to determine how feedbacks influence evolution across generations, for both behavior and its underlying genes. This research will provide scientific opportunities to community college students. NSF support will allow talented community college students to experience research for the first time, and contribute to educating the broader community.Evolutionary feedbacks occur when behavioral evolution in one generation results in altered selection pressures in subsequent generations. Despite longstanding hypotheses that feedbacks should be nearly ubiquitous, little is still known about how feedbacks influence behavioral evolution and its underlying genetic basis. This research will fill this gap in knowledge by manipulating evolutionary feedbacks for aggressive behavior in replicate fruit fly (Drosophila melanogaster) populations evolving under artificial selection for increased aggressiveness. By manipulating the social environment in which artificial selection occurs, replicate populations will be artificially selected under conditions that permit positive, negative, or no feedbacks, alongside unselected controls. Behavioral changes will be tracked across generations, and whole-genome sequences from evolved populations will be compared to identify population-genomic "signatures of feedbacks." Individual genes that are putative targets of selection will be transgenically manipulated to determine their effects on behavior(s), allowing direct measurement of whether different feedbacks target genes with different roles in aggressive interactions. Together, these Aims provide the first direct tests of the hypotheses that evolutionary feedbacks alter the rate, trajectory, and genetic basis of behavioral evolution. The results have the potential to reconcile previously-incongruent studies, and will provide a conceptual and methodological framework for studying the ways that social interactions during individuals' lifetimes scale up to influence evolutionary change across generations. The research will support diverse community college students to experience research in evolutionary genetics during the summer. These scientific enrichment opportunities will provide opportunities for diverse students to enter STEM fields while learning about evolution.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.