DISSERTATION RESEARCH: Using Covariance to Test Hypotheses about the Function and Underlying Genetic Control of Multi-component Signals

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The ability to communicate effectively with other individuals is important for survival and reproduction; however, little is known about the genetics of producing communication signals. The proposed project focuses on sound (auditory) signals used in courtship in a species of fruit fly. The multiple auditory signals produced by this species are complex but their relationships to each other and genetic control of their production have not been determined. The proposed research incorporates methods from animal behavior, evolution, and genetics to better understand how conveying and receiving messages occurs in animals. This can provide insights into what messages are passed from males to females and how these messages are genetically controlled. Given the abundance of genetic knowledge in fruit flies, and how many genes are shared between flies and humans, broader connections can be made from this species to other study systems. In addition, part of the project will extend public understanding of the genetics and information content of signals through mentorship of two undergraduate students, outreach at a local high school, attendance at national scientific conferences, and development of teaching materials for high school classrooms. Signals transmitted between individuals are often complex and contain multiple components. These components may convey the same information, in which case they are expected to evolve in concert, or they may have separate messages, which implies independent evolution. Understanding how signal components co-vary and are genetically controlled may provide insight into the messages conveyed. To address this problem, the acoustic signals of Drosophila sturtevanti will be examined using a novel approach. This species has complex mating signals, generated by male wing vibration, that stimulate females to mate. Two signal components, pulse song and beep song, will be examined for phenotypic covariance. The absence of phenotypic co-variation between the song components will support the hypothesis that the respective components contain multiple messages. In contrast, significant positive co-variation will support the hypothesis that the respective components contain the same message. Alternatively, significant negative co-variation will support the hypothesis that respective components constrain each other. In addition to phenotypic covariance, the genetic architecture of the two signal components will be assessed through quantitative trait loci (QTL) mapping using a next generation sequencing approach. The amount of co-localization of the QTLs for the signal components will determine the commonality of genetic control. Significant co-localization will imply shared genetic control and the direction of association (positive or negative) will indicate how selection pressures act on the genetically linked systems. Understanding the genetic control of associated signals is essential for elucidating mechanisms by which adaptive behavioral traits evolve and for modeling the evolution of multi-component signals.