Personalized medicine offers the hope that we can tailor treatment to a person's unique genetic background. To that end, we can now quickly and cheaply sequence a patient. However, rare variation abounds in humans, posing a formidable challenge: how do we interpret the sequencing data that is returned for a particular patient?
I am using genome engineering techniques and developing new technologies to address this question. In particular, I'm leveraging Cas9-based genome editing for large-scale functional characterization of genetic variants in human cells. Using these methods, my goal is to make comprehensive protein sequence-function maps that could be used to interpret any variant in a protein of interest. Pharmacogenes are an exciting focus of this research, as many patients carry variants in these genes that have unknown effects. Using our approach, we can understand how variants we’ve already seen affect protein function and make predictions about what drugs and doses would be appropriate for each new variant that is identifiede. I'm also interested in methods for investigating non-coding variants and multiplexing variants to better map genotypes to phenotypes.