Experimental evolution of complex traits

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PROJECT SUMMARY Evolution via natural selection results in organisms adapted to their environment, but also involves trade-offs. Many complex diseases affecting humans today are historical artifacts of our past evolution. Thus, a better understanding of the process of adaptation may provide new tools to combat complex disease. And yet there are considerable gaps in our knowledge of the dynamics of adaptation at the level of genotype and phenotype, in large part due to the challenges of inferring the effects of past selection on human populations. The long-term goal of this proposal is to elucidate the molecular basis of adaptation using an innovative, sexually-reproducing laboratory system of outcrossing yeast (Saccharomyces cerevisiae). Experimental evolution offers a powerful method to test hypotheses about adaptation as investigators observe populations evolve in real time under controlled conditions. With genome sequencing, genetic variation can be sampled from populations during the process of adaptation; this technique is called “Evolve-and-Resequence”, or E&R. Recent E&R work with this yeast laboratory system has advanced fundamental evolutionary questions, for example by providing strong evidence that preexisting genetic variation drives adaptation, rather than beneficial new mutations. Also, it finds that the stable long-term maintenance of genetic diversity is common, even when selection is strong. Building upon these initial discoveries, additional questions are being tested, such as what evolutionary outcomes result from complex selection environments involving fluctuating or otherwise dynamic selection pressures, and what influence gene expression has on adaptive change, over a range of time scales. This proposal takes advantage of MIRA’s flexible research goals, as it would support multiple yeast E&R projects. Each will further understanding of general adaptative dynamics, and will also deliver specific insights into particular traits. A trait of special interest to this proposal is late-life fertility. Senescence, or the decline in survival and fertility with advancing age, is a good example of a complex disease facing humans as a result of evolutionary trade-offs. Preliminary data in this application show that through selecting only the oldest cells to reproduce over many generations, yeast populations evolve to live longer and remain fertile at later ages than control populations. This provides an exciting potential to dissect the genetic basis underlying longevity and late-life fertility, and new research horizons are expected to become attainable as a result. The proposed research is significant, because it is expected to vertically advance and expand understanding of the natural genetic variation underlying healthy versus disease-related phenotypes, and specifically for phenotypes related to late-life reproductive success. Ultimately, such knowledge has the potential to inform the development of approaches in personalized medicine, and/or gene therapies, that will lead to a variety of improved health outcomes.