Behavioral Genetics and Neuropsychiatric Disorders in a Natural Model System

Univ Of Massachusetts Med Sch Worcester, Worcester MA

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Abstract

The domesticated animal is one of the best natural models for human behavioral and neuropsychiatric disorders, with similar clinical presentation and therapeutic response, and genetic studies implicating almost identical neural pathways. The strong artificial selection on behavioral traits pushed associated variants of large effect up in prevalence, makes them particularly tractable to genomewide association mapping. Identifying and functionally elucidating genetic changes underlying both normal behavioral variation and behavioral disorders is a powerful tool for understanding the pathways disrupted in mental illness. Until now, gene mapping in domesticated populations has focused almost exclusively on strictly genetically isolated and remarkably homogenous populations created within the last few hundred years. Genome-wide association studies (GWAS) done in a single population require only a sparse marker set and relatively few markers, but have notable limitations: regions of association are very large, making it difficult to identify the precise causal variant; disease causing variants can be fixed (100% prevalence) and thus undetectable; assembling large cohorts of single population is difficult, limiting statistical power. While the genes for many single-gene, Mendelian traits have been mapped, complex traits, including behavioral traits, have proven much more difficult, and just a handful of significant associations published. We propose to implement, for the first time, genetic association studies of behavioral traits in genetically diverse domesticated animals. To do this, we will harness two technological revolutions since the advent of genome sequencing. First, rapid and inexpensive next-generation sequencing has led to huge catalogs of genetic variation, facilitating design of the far denser SNP array needed for mapping. Simultaneously, the rapid spread of handheld devices (smart phones and tablets) is an unprecedented opportunity to solicit detailed behavioral phenotype information. We propose to develop a new model for GWAS of behavioral traits and disorders that allows them be done quickly and efficiently and with much larger sample sizes. We aim to: 1) Develop web based surveys to accurately phenotype heritable traits 2) Establish a robust, expandable DNA databank 3) Pilot genomewide association using new Affymetrix SNP array. Ultimately, we seek to shift the paradigm in behavioral genetics away from its focus on purebred populations and embrace the potential offered by diverse populations.