Combining experimental evolution and molecular phenotyping to understand variation in organismal phenotypes

PROJECT SUMMARY Understanding the forces that shape patterns of genetic and phenotypic variation in populations is a central goal of evolutionary biology. Within a biomedical context, this translates to questions like: Why are some individuals more susceptible to disease? Or why do some naturally age “better” and live longer?

Answering these questions is a crucial step toward true personalized medicine, and would pave the way for intervention strategies and treatments that could transform how we approach human health. However, efforts to answer these questions are often hampered by difficulties associated with inferring past and

present selective pressures, and differentiating between the consequences of selection, genetic drift, and demographic shifts. Here experimental evolution offers a path forward. By studying evolution in real-time in controlled environments, we are able to directly test hypotheses about how evolutionary forces shape

trait variation. The adaptive changes we observe also provide key mechanistic insights into the biology underlying observed differences – a fact that is especially valuable in experiments where selection targets health-relevant traits. In sexually reproducing systems that mirror human populations, we find that

adaptation is typically fueled by standing genetic variation and involves hundreds of genes. Taken together, these findings suggest there is abundant functional genetic variation segregating for most complex traits and recent selection significantly impacts patterns of phenotypic variation. However,

moving beyond the findings that “standing genetic variation facilitates rapid adaptation” and “complex traits are highly polygenic” has been difficult. While we routinely use experimental evolution to identify genes associated with specific phenotypes, we lack the ability to validate and explore their functions in

mass. As such, efforts to generate deeper biological insights have seen limited success. The Phillips Lab is seeking to address this by incorporating molecular phenotyping and metabolomics into the experimental evolution framework. Using metabolomic profiling and 3-dimensional electron microscopy, we are working to understand the factors that drive differences in rates of senescence using

experimentally evolved fruit fly populations with radically different aging and life-history patterns. We are also working to establish a new experimental system to study variation in susceptibility to type 2 diabetes. By subjecting fruit fly populations to high-sugar diets for generations, we will effectively create populations

enriched for sugar-tolerant individuals. And by collecting genomic, transcriptomic, and metabolomic data from them as they evolve, we will decipher how the relationships between these levels of biological organization shape this phenotype. As a whole, the proposed projects all aim to improve our understanding of the factors underlying common trait variation in real populations.