The Heritable Transcriptome and Alcoholism

本应用程序的目标是建立一个适合系统的动物模型和相应的数据库

The goal of this application is to establish an animal model and accompanying database suitable for a systems genetic analysis of complex traits, specifically traits that represent genetic predisposing factors for alcohol use disorder (AUD). Systems genetic approaches require a global analysis of factors such as gene expression, protein and metabolite levels in multiple tissues of an organism, as well as an understanding of gene-gene and gene-environment interactions, and the interdependency of these factors in contributing to complex traits/disorders. As a result, a key requirement for an animal model is a genetically stable population that can be studied repeatedly, over many generations, to provide cumulative data that can eventually allow for a complete systems genetic analysis. During the past grant periods, we have progressed well with the development of a Hybrid Rat Diversity Panel (HRDP) that meets these criteria. We have chosen to focus on the rat, rather than the mouse, for studies of complex traits related to AUD, because of the greater size of the rat brain, the ease of training in operant tasks, and the rat’s higher cognitive ability. We have generated DNA sequence data, RNA sequence data and whole genome exon array data on four tissues (brain, liver [whole organ and cell-specific data], heart and brown adipose tissue) from rat strains of the HXB/BXH recombinant inbred (RI) panel and from classic inbred rat strains. We have mapped QTLs for behavioral/physiological traits (alcohol consumption, alcohol deprivation effect, alcohol metabolism including acetate levels after alcohol administration), as well as used transcriptome data to map expression QTLs, to generate transcript coexpression modules and map module eigengene (first principal component) QTLs. These data have been used to identify candidate genes and transcriptional networks that contribute to the measured biochemistry and behaviors. All of our raw, processed and analyzed data have been made available to the research community on our PhenoGen website (http://phenogen.ucdenver.edu). This website, that we developed, also includes several visualization tools to explore these data in a systems genetics framework and allows the user to observe genetic relationships between a complex phenotype of interest and networks of gene products that influence the phenotype. We are now proposing to complete the main core of transcriptional data for the 96- strain HRDP, adding data from another rat RI panel (FXLE/LEXF) and more inbred rat strains. We will obtain full transcriptome information of brain and liver of male and female rats from all strains, quantify the expression of transcript isoforms, including 3’UTR isoforms, and analyze the 3’UTR regions for alternative use of polyadenylation sites and miRNA binding sites. We will use our established and newly developed pipelines to disseminate integrated, systems level data (PhenoGen and Rat Genome Database). We will also expand our demonstration for applying the gathered information to the identification of genetic factors that are linked to the development of AUD by obtaining information on predisposition to “depression” in the HXB/BXH RI panel, and we will continue to integrate the animal data with human GWAS data.