eQTL mapping

In this research project we will analyze behavioral trait, genotype, RNA-Seq, and 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. 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 RNA-Seq on these brain regions. In this research project we will use RNA-Seq data to quantify gene expression in each brain region and use these data to map eQTLs. We will also analyze allele-specific expression (ASE) as another indicator of regulatory variation.

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.

Samples collected from HS rats that are available for eQTL mapping

 ProjectInvestigatorTissueNumber of samples
1P50 DA037844 Y5-10, Project 1:
Neurogenetic Substrates of Cocaine Addiction
Paul Meyer,
U at Buffalo
Brain: nucleus accumbens core180
2P50 DA037844 Y5-10, Project 1:
Neurogenetic Substrates of Cocaine Addiction
Paul Meyer,
U at Buffalo
Brain: insular cortex180
3P50 DA037844 Y5-10, Project 1:
Neurogenetic Substrates of Cocaine Addiction
Paul Meyer,
U at Buffalo
Brain: posterior VTA180
4P50 DA037844 Y1-5, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: nucleus accumbens core88
5P50 DA037844 Y1-5, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: lateral habenula88
6P50 DA037844 Y1-5, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: orbitofrontal cortex88
7P50 DA037844 Y1-5, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: infralimbic cortex88
8P50 DA037844 Y1-5, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: prelimbic cortex88
9P50 DA037844 Y5-10, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: posterior ventral tegmental area100
10P50 DA037844 Y5-10, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: medial habenula100
11P50 DA037844 Y5-10, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: ventral hippocampus100
12P50 DA037844 Y5-10, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: insular cortex100
13P50 DA037844 Y5-10, Project 2:
Socially-acquired nicotine self-administration
Hao Chen, UTHSCBrain: lateral hypothalamus100
14U01 DA050239:
Single-cell Resolution analysis of chromatin
accessibility and gene expression changes
in a model of drug addiction
Francesca Telese, UCSDBrain: nucleus accumbens100
15Pilot:
Creating the dataset for TWAS in HS rats
Francesca Telese, UCSDBrain: whole hemisphere375
16U01DA046077:
Identification of Genetic Features of Delay Discounting
Using a Heterogeneous Stock Rat Model
Suzanne Mitchell,
OSHU
Brain: nucleus accumbens core200
17U01DA046077:
Identification of Genetic Features of Delay Discounting
Using a Heterogeneous Stock Rat Model
Suzanne Mitchell,
OSHU
Brain: basolateral amygdala200
18U01DA046077:
Identification of Genetic Features of Delay Discounting
Using a Heterogeneous Stock Rat Model
Suzanne Mitchell,
OSHU
Brain: infralimbic cortex200
19R01 EY021200:
Genetic Modulators of Glaucoma
Monica Jablonsky, UTHSCEye50