eQTL mapping

(this page is in progress)

In this research project we will analyze behavioral trait, genotype, RNAseq, whole genome sequence data in an effort to identify genes that influence a wide variety of drug abuse related behavioral traits. Genotype data from almost 5,000 heterogeneous stock (HS) rats will be provided by the Sequencing Core (Core C); genotypes will be obtained using an innovative genotyping-by-sequencing (GBS) approach. Because the 8 founders of the HS have been fully sequenced, we will be able to impute founder haplotypes and genotypes at 7.2 million SNPs throughout the rat genome. We will use this information to perform a genome-wide association study (GWAS) for each of the behavioral traits measured in Research Projects 1-3. The results of that analysis will identify behavioral quantitative trait loci (QTLs). Because we are also interested in sex differences, we will investigate gene x sex interactions. Furthermore, we will use multitrait mapping methods because many of our behavioral traits are known to be correlated with one another. A key feature of our analysis is that we will account for relatedness among HS individuals. Because they are produced by a large but finite breeding colony, the individuals that we are studying will have varying levels of genetic relationships with one another (e.g. siblings, cousins, etc.). Failure to properly account for such relationships can result in dramatic false positive errors. We have extensive experience using mixed models to deal with similar populations and have developed widely used R packages for this purpose. Another major component of this research project will be the mapping of expression QTL’s (eQTLs). As part of Research Project 2, Dr. Hao Chen will collect specific brain regions. The Sequencing Core (Core C) will perform RNAseq on these brain regions. In this research project we will use RNAseq data to quantify gene expression in each brain region and use these data to map eQTLs. A further goal of this project is to explore genetic correlations between traits, including traits that are not measured in the same rats. Our approach is similar to recent investigations of co-heritability among major psychiatric disorders and depends on the varied levels of relatedness among the HS rats used by Research Projects 1-3. This highly innovative approach will fundamentally enhance our understanding of these drug abuse related behaviors. Finally, we will integrate behavioral QTLs, eQTLs and genome-wide sequence data from the 8 founders of the HS to identify putatively causal genes. Thus, by the end of the proposed five-year project, we expect to identify not only numerous chromosomal regions, but also specific genes within those regions that we believe are causally related to the behavioral QTLs. Subsequent functional studies to replicate and extend these findings using tools such as genetically engineered mutant rats, viral mediated gene transfer and pharmacological manipulations will be funded by the Pilot Project Core (Core D) or by subsequent grants.