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.
