The end goal of medical genomics research is to predict, prevent, and treat disease and with our research, we are leveraging next-generation sequencing data to address a number of questions that relate to this goal. Our work in this area includes development of analysis pipelines and new computational techniques for addressing issues such as: characterization of gene expression profiles in the lungs of both healthy individuals and those with lung disease, the evolution of ovarian cancer, and population genetic analysis of factors important for the etiology of disease.

Using genome-wide gene expression data collected for cell populations in the small airway of the lung, we used a multivariate technique to quantify the effects of low levels of smoking. We found that even with at levels equivalent to second-hand smoke, there is a considerable effect on the genome-wide gene expression profile of the lung. While it is unclear if these changes have a direct connection to lung disease such as Chronic Obstructive Pulmonary Disease and cancer, these results indicate that it is not possible to smoke without producing a detectable genomic effect in the lung Strulovici-Barel et al. 2010. Using next-generation sequencing, we are studying the variation in exomes of individuals in the country of Qatar, on the Arabian peninsula, to discover alleles that make this population distinct from the rest of the world. The plot shows the genomic position of single nucleotide polymorphisms (SNPs) that are significantly different than the continental allele frequencies in Africa, Europe, and Asia, as estimated from the 1000 Genomes project. Among the risk alleles discovered to be at unusually high frequency in Qatar are those associated with diabetes, consistent with high incidence of this disease in this country. Rodriguez-Flores et al. in prep.
Rodriguez-Flores et al. Web Resource