Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments

3. Modeling Experimental Evolution Using Individual-Based Variance Components Models

31 3 MODELING EXPERIMENTAL EVOLUTION USING INDIVIDUAL-BASED, VARIANCE-COMPONENTS MODELS Derek A. Roff and Daphne J. Fairbairn MODELING APPROACHES Population-Based Models Mendelian-Based Models Variance-Components Models SINGLE-TRAIT MODELS Artificial Selection in the Single-Trait Model Laboratory Evolution in the Single-Trait Model MULTIPLE-TRAIT MODELS Artificial Selection in the Multiple-Trait Model Laboratory Evolution in the Multiple-Trait Model Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments, edited by Theodore Garland, Jr., and Michael R. Rose. Copyright © by the Regents of the University of California. All rights of reproduction in any form reserved. A CASE STUDY: PREDICTING LABORATORY EVOLUTION IN THE SAND CRICKET, GRYLLUS FIRMUS Problem Description Model Description Background Analyses and Data Running the Model CONCLUSION Experimental evolution as used in this volume encompasses both artificial selection and “laboratory” evolution in which populations are introduced into a novel environment and allowed to breed without any overt selection by the experimenter. Any selection that occurs in laboratory evolution experiments is assumed to be imposed by aspects of the novel environment. The major advantage of this latter approach over artificial selection is that the organisms are allowed to evolve relatively naturally in response to diverse selection acting on the whole phenotype, and hence the observed evolutionary processes may more closely mimic those that occur in nature (see also Futuyma and Bennett this volume; Gibbs and Gefen this volume; Huey and Rosenweig this volume; Rose and Garland this volume). In particular, allowing organisms to evolve naturally in the novel environment enables researchers to explore the coherence and coordination of traits in terms of both the immediate physiological interactions within an organism and their evolutionary potential. Artificial selection has been applied very extensively, although surprisingly almost entirely on single traits (Roff 2007; Bell 2008), whereas laboratory evolution is a relatively recent approach. It has been used to investigate evolution in cultures of unicellular eukaryotes, bacteria, and viruses (e.g., Travisano et al. 1995; Reboud and Bell 1997; Bennett and Lenski 1999; Messenger et al. 1999; Wichman et al. 2000) and in diverse multicellular organisms, such as nematodes, Caenorhabditis elegans (Cutter 2005), and fruit flies, Drosophila melanogaster (e.g., Stearns et al. 2000; Mery and Kawecki 2002; Rose et al. 2005). The simple act of bringing organisms into the laboratory and keeping them in culture is itself a case of experimental evolution because the laboratory environment invariably differs from the native environment. The cultured organisms experience a novel selective regime, and, assuming that the requisite genetic variance is present, they are expected to evolve in response to this. This is a process of passive (i.e., not overtly selected by the experimenter) adaptation to the laboratory environment, or “domestication.” One common example, observed in many insects (Danilevsky 1965), is loss of obligatory dormancy when laboratory environments are continuously favorable for growth and reproduction . Domestication of D. melanogaster leads to changes in both life history and physiology , although the selective factors favoring such changes are not well understood (Chippindale et al. 1997; Bochdanovits and de Jong 2003; Rose et al. 2005; Simões et al. this volume). Indeed, a significant problem in interpreting and predicting the course of experimental evolutionary experiments is the definition of what exactly is being favored in the new environment (Rose et al. 1990). In any experimental evolution program, the researcher is faced with the problem of deciding on the population size per generation and number of generations over which to run the experiment. These issues have received considerable attention for artificial selection on single traits (Roff 1997) but remain relatively unexplored for multiple traits or laboratory evolution. The evolution of multiple traits is a primary focus of laboratory evolution experiments and studies of evolutionary changes in natural populations. Given the labor and costs of undertaking such studies, it behooves the researcher to develop a 32 • I N T R O D U C T I O N T O E X P E R I M E N T A L E V O L U T I O N M O D E L I N G E X P E R I M E N T A L E V O L U T I O N • 33 priori predictions from which to determine the appropriate experimental requirements. Genetic models of evolutionary change allow us to make such predictions. There are three approaches to modeling the evolution of quantitative traits: (1...