Houston, TX 77005
9:00 a.m. Monday, Feb. 25, 2013
On Campus | Alumni
A fundamental challenge in evolutionary biology is to understand the genetic basis of adaptation. And enduring effort in medical genetic research is to identify genetic variations responsible for disease and drug interactions. Both seemingly disparate fields have in common that it is a challenge to connect the phenotype (be it a disease in humans or a trait in animals or plants) with the genotype. Using a study system of warfarin resistance in rats, my dissertation utilizes innovative experimental, computational and population genetic tools to detect the genetic architecture of warfarin resistance and the signatures under the strong selection pressure. With network-guided genomic association study and expression analysis, my project identifies candidate genes involved in resistance to warfarin, which is a first-generation anticoagulant rodenticide used since 1950s, and also a widely prescribed blood-thinning drug for preventing thrombosis, embolisms, and heart attacks in human. The drug has a very narrow therapeutic window such that gene-drug interactions need to be identified in order to better predict drug dosages, which vary dramatically within and between individuals owing to genetics, diet and environments. Warfarin was initially a highly effective tool to control rats. However, rats resistant to warfarin have evolved within a mere ~10-15 years. As of now Vkorc1 is the gene known to cause warfarin resistance in rodents. In humans, several mutations in the genes VKORC1, CYP2C9, CYP4F2 affect the physiological response to warfarin drug treatment, thus are used as biomarkers predicting warfarin dosage. We systematically study the genetic bases for warfarin resistance with fundamental questions in mind; the genetics of adaptation, and the search for additional warfarin-interacting genes, which have implications for agriculture and medication. We applied population genomics approaches and network algorithms (including a modified Google’s PageRank algorithm) to search for candidate genes and detect the selection signatures. In our research, we show that warfarin resistance in our German rats has evolved by balancing selection (like the famous example of sickle cell anemia in human) on a novel variant entering the population after the introduction of warfarin as rodenticide. The identified multiple candidate genes are connected with vitamink K pathway. Combining SNP array and microarray data, we detect cis-eQTLs (cis-expression quantitative trait loci), which are enriched in candidate genes. The list of additional candidate genes involved in warfarin resistance will be further evaluated. One candidate gene Calu is found to be associated with warfarin resistance in multiple wild populations. Post genome era tools and approaches enabled us to show that adaptive traits, seemingly simple (single gene) as warfarin resistance, likely are more complex. The additional candidate genes should be of interest to the biomedical field concerned with warfarin therapy. Other genes involved in the fitness cost (such as arterial calcification) of resistance suggest a more comprehensive picture of adaptation. The developed framework and algorithms would be generally applied to other systems of candidate gene identification for cancer or diseases.