We study the regulation and evolution of gene expression using a combination of experimental and computational approaches.
Our work brings together quantitative genetics, genomics, epigenetics, and evolutionary biology to achieve a deeper understanding of how genetic variation within and between species affects genome-wide gene expression and ultimately shapes the phenotypic diversity of life.
Some of our long-term goals are to better understand:
Some specific projects in the lab:
Genome-wide scans for adaptive evolution of gene expression
Despite a great deal of work in this area, only a handful of cases of adaptive gene expression evolution have been discovered, each by a painstaking candidate gene approach. We have recently developed the first method that systematically scans genome-wide data to identify genes whose expression levels are under positive selection. We are currently extending this method in a variety of ways, and applying it to a wide range of species, including yeast, insects, plants, mice, and humans.Publications: Fraser et al 2010; Fraser et al 2011; Fraser 2011; Fraser et al 2012; Fraser 2013; Artieri & Fraser 2014.
Pinpointing mutations underlying gene expression adaptations
Even once gene expression adaptations have been identified (above), a major challenge is to identify the precise nucleotide changes that were selected. Knowing these will allow us to study a number of fundamental issues, such as the molecular mechanisms of gene expression adaptation, as well as the roles of epistasis and fitness trade-offs in adaptation. We are using yeast as a model for these studies, since it offers unparalleled advantages for engineering specific genetic alterations and measuring fitness.Publications: Fraser et al 2010; Chang et al 2013.
Uncovering the genetic basis of complex traits
The genetic basis of phenotypes is usually investigated with genetic mapping approaches known as QTL mapping or GWAS. These are effective at finding genomic regions of interest, but they have several drawbacks: they do not implicate specific genes or genetic variants; they do not reveal molecular mechanisms involved; and they require genotyping and phenotyping hundreds or thousands of individuals. We are improving on these methods in two ways. First, we are developing new methods to map genetic variants affecting molecular-level traits (such as DNA methylation and transcription factor binding) throughout the genome, which do not require any individual-level genotyping or phenotyping. In addition, we are using inter-species hybrids to map the landscape of cis-regulatory divergence, which allows us to identify the genes underlying polygenic adaptations far more efficiently than QTL mapping. We are currently applying this approach to study adaptations in yeast, mice, cichlids, zebras, and other species.Publications: Fraser et al 2011; Fraser 2011; Fraser et al 2012; Artieri & Fraser 2014; Kaplow et al 2015.
Epigenetic evolution of gene expression
Gene expression is not only determined by the genome, but also by the epigenome (heritable information not encoded by DNA). However very little is known about how evolutionary changes in the epigenome may affect gene expression. We are focusing on two important epigenetic phenomena: DNA methylation and imprinting. For DNA methylation we are investigating both the causes and the consequences of its variation among humans. We are also exploring the evolutionary dynamics of imprinting, where only one allele of a gene (either the mother's or the father's) is expressed in any individual.Publications: Fraser et al 2012; Lam et al 2012; Babak et al 2015; Kaplow et al 2015.