Gene expression, is an intermediate step of the process translating genetic information into
functional proteins, is a complex trait regulated by a multitude of genetic factors. Recent
advances in genomic technologies have allowed us to identify genetic variants (eQTLs)
associated with variation in gene expression. However, the extent to which these variants
contribute to the adaptive evolution of gene expression remains unclear.
We aim to investigate the genetic basis of gene expression evolution by comparing the
genetic architecture revealed by eQTL mapping with the actual evolutionary trajectories of
gene expression. We hypothesize that the adaptive architecture of gene expression is more
complex than the simple additive model implied by eQTL mapping, involving factors such as
epistasis (gene-gene interactions) and pleiotropy (genes affecting multiple traits).
To test this hypothesis, we will employ a combination of eQTL mapping and experimental
evolution. We will use a unique population with low linkage disequilibrium, which will
enable us to accurately estimate the effects of individual genetic variants. By tracking
changes in gene expression and allele frequencies over time in replicate populations
adapting to a novel environment, we will be able to quantify the contribution of different
genetic factors to the adaptive process.
Our research will provide novel insights into the genetic mechanisms underlying gene
expression evolution. By understanding the interplay between genetic variation,
environmental pressures, and evolutionary processes, we can gain a deeper appreciation of
the complexity of adaptation and its implications for various biological phenomena,
including disease susceptibility and drug response.