Using genetically engineered animal models in the postgenomic era to understand gene function in alcoholism

Abstract

Over the last 50 years, researchers have made substantial progress in identifying genetic variations that underlie the complex phenotype of alcoholism. Not much is known, however, about how this genetic variation translates into altered biological function. Genetic animal models recapitulating specific characteristics of the human condition have helped elucidate gene function and the genetic basis of disease. In particular, major advances have come from the ability to manipulate genes through a variety of genetic technologies that provide an unprecedented capacity to determine gene function in the living organism and in alcohol-related behaviors. Even newer genetic-engineering technologies have given researchers the ability to control when and where a specific gene or mutation is activated or deleted, allowing investigators to narrow the role of the gene's function to circumscribed neural pathways and across development. These technologies are important for all areas of neuroscience, and several public and private initiatives are making a new generation of genetic-engineering tools available to the scientific community at large. Finally, high-throughput "next-generation sequencing" technologies are set to rapidly increase knowledge of the genome, epigenome, and transcriptome, which, combined with genetically engineered mouse mutants, will enhance insight into biological function. All of these resources will provide deeper insight into the genetic basis of alcoholism.

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Exploring the relationship between genotype and phenotype by using high-throughput sequencing and genetically engineered animal models. Novel high-throughput “next-generation sequencing” technology can be used together with new genetic engineering technology to understand gene function in alcoholism. Compared with traditional sequencing, “next-generation sequencing” allows researchers to efficiently and cost-effectively obtain large amounts of genomic data (e.g., from large cohorts of humans with and without disease) to detect all the genomic, epigenomic, and transcriptomic variation associated with the disease, creating comprehensive “disease maps.” In a next step, functional information can be attached to these disease maps that defines how the various components of the map (i.e., individual genes) act and interact, for example, using genetically engineered animal models. Genomic variations associated with human diseases can be engineered into rodent models (or other experimental organisms) and detailed phenotypic analyses can be performed, further refining disease maps with functional annotation.