Assessing the impact of mate choice on genetic architecture and testing the "good genes" model

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In many organisms, humans included, one or both genders are able to exercise choice among potential mates. Mates are typically chosen based upon particular traits and these are often exaggerated in the chosen individuals. Such preferential mating is expected to generate an association between the genes underlying the preference and the genes underlying the preferred trait. Over time, continued selection on the preferred trait is also expected to reduce its genetic variability. PIs Roff and Fairbairn develop theory that predicts the strength of the genetic association between the preference and the preferred trait and explains how genetic variation in the preferred trait may be maintained within such mating systems. To test this theory the PIs will measure the genetic variances of female preferences and male calling song parameters in sand crickets over ten generations of laboratory evolution. Crickets are excellent subjects these studies because females choose males based on song characteristics that can be readily quantified in the laboratory. The key test will be comparisons among populations in which females mate (i) according to their preferences, (ii) with randomly selected males, or (iii) with non-preferred males. These comparisons will also be used to test the hypothesis that male song is a reliable signal of male genetic quality and hence enables females to choose males that have "good" genes. This research tests fundamental theory for the evolution of mate choice and breaks new ground in revealing the genetic underpinnings of exaggerated sexual display traits. In addition, the PIs will use their experimental, mate choice protocol as an instructional tool for illustrating the concepts of sexual selection and adaptive evolution. In collaboration with local high school teachers and using resources and materials provided by this grant, they will develop educational modules and participate in transferring these to local classrooms. DATA MANAGEMENTThis project will generate two types of data, informational data in the form of measurements and object data in the form of preserved specimens. The former types of data will be made available to the general scientific community by submission to the Dryad repository (datadryad.org) as the results of the research become published. The preserved specimens will be retained for future analysis.