The goal of this project is to develop quantitative understanding of the evolutionary dynamics of large populations with abundant selection and recombination by analyzing a variety of models that build in various of the key features. The interplay between multiple beneficial mutations accumulating in one lineage and recombination that breaks apart and brings together collections of such mutations will be studied in several situations: re-assortment, the exchange of chromosomes between individuals without recombination as occurs for influenza viruses; transfer of small segments of a genome as in lateral gene transfer between bacteria; occasional mating between otherwise asexually evolving populations, as in yeast; and various approximations of the spectrum of degrees of linkage that arise from the linear structure of chromosomes. Epistatic interactions between mutations together with changing linkage leads to a balance between selection on individual genes and selection on genomes: this will be explored for various models of the interactions focusing on the statistical properties of the rare, anomalously good combinations of mutations that dominate the future evolution. The models of epistasis will be informed by, and inform, experiments on laboratory evolution of budding yeast carried out by collaborators. Mating within or between asexually evolved populations that have been "barcoded", should provide crucial information about the fitness of parents and their offspring, and the theory developed will enable predictions about the benefits of sex that can be tested in future experiments. Going beyond well-mixed populations in which all individuals compete directly, other forms of competition that could be realized in the laboratory (such as selection of the best half of a population) will be studied. Spatial structure and the interplay between local competition and mixing on longer time scales will also be investigated, focusing on the effects of recombination on rates of evolution and dynamics of diversity. Collaborations with several groups carrying out laboratory evolution experiments with yeast or bacteria will be further developed to obtain statistical information needed for the modeling, and to propose and plan future experiments. Analysis of deep sequencing data of bacterial populations will be carried out with collaborators to infer aspects of the evolutionary history, including recombination, and to develop plans for the most informative future sampling and sequencing. The students and postdocs involved will greatly benefit from mentoring by several faculty from different fields. Beyond the research, the PI is developing new courses on evolution for quantitative scientists and biologists: lecture notes will be made available on the internet. The PI will also become further involved in educating the general public about evolution, including the future challenges, as well as the successes, of evolutionary theory.
