Mutation and Levels of Selection in Clonal Organisms

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Clonal reproduction, or the nonsexual production of new individuals, is widespread throughout both plant and animal species. Existing theory fails to adequately address many important details of clonal life histories, including the existence of multiple levels of organization and opportunities for selection. The overall aim is to expand evolutionary genetic models to incorporate these unique life history characteristics. Analytical models developed will combine both a population genetics framework (where, for example, allele frequencies in the entire population are followed) and demographic models (which incorporate details of the organism's particular life history). Empirically derived demographic data will be used for further numerical analyses. In order to consider multiple levels of selection, individual-level fitness will reflect genetic diversity generated by the accumulation of mutations within the individual or clone. Models will also be extended to populations that are structured in other ways (for example, spatial structure imposed by clonal growth). There are three major and unique strengths of the proposed research: (1) integration of classical population genetics theory with demographic models allows consideration of both genetic and ecological factors influencing selection, (2) combining empirical results with theoretical models allows a better and more realistic understanding of these genetic and ecological factors, and (3) the life history characteristics being considered are found in plants, in algae, and across at least two-thirds of metazoan animal phyla, including important marine invertebrates such as corals, making the results of this work widely applicable. By expanding existing population genetics theory to include organisms outside of those previously considered, the proposed research will provide crucial insight into processes such as mutation, selection at different levels of organization, and the origin and maintenance of genetic diversity.