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.

Public Health Relevance

The domesticated animal is remarkable natural model for investigating the genetics underlying behavior, mental illness and neurological disease, but, despite widespread interest, studies focused genetically isolated populations have found only a handful of the underlying genes. We propose to develop, for the first time, genetic mapping in diverse populations. We will expand the scope and power of our genetic studies by linking high-throughput genomics with detailed behavioral data provided through web based surveys.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21MH109938-02
Application #
9267176
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Beckel-Mitchener, Andrea C
Project Start
2016-05-01
Project End
2018-04-30
Budget Start
2017-05-01
Budget End
2018-04-30
Support Year
2
Fiscal Year
2017
Total Cost
$226,125
Indirect Cost
$91,125
Name
University of Massachusetts Medical School Worcester
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
603847393
City
Worcester
State
MA
Country
United States
Zip Code
01655