This application requests continued support for the long-term objectives of AA 011034, namely to develop and implement high throughput strategies for investigating the natural genetic variation in alcohol- related behavioral phenotypes. Historically AA 011034 has focused on the detection and fine mapping of quantitative trait loci (QTL) and on the integration of QTL mapping with gene expression and sequence data. This competing renewal continues this work with a focus on 7 coincident-reciprocal QTLs detected for acute ethanol withdrawal and ethanol consumption/preference. "Coincident-reciprocal" simply refers to QTLs where alleles associated with increased severity of the withdrawal response are also associated with decreased ethanol consumption and vice-versa. However, this renewal application also moves in a new direction. The rationale for this new direction builds from the idea that the natural genetic variation in any complex trait phenotype is a systems biology phenomenon and must be investigated as such."Systems" can be defined in many different ways. Here "systems" are generally defined as gene co-expression networks (Langfelder and Horvath, 2008) strongly associated with the consumption and withdrawal phenotypes. These networks are detected independently of the QTL analysis. Importantly, network structure provides both a new tool for interrogating QTL intervals and the broader context for determining how a single gene can affect the phenotypes of interest. The systems biology approach also emphasizes that it is the system and not any individual gene that has translational value. This competing renewal has 4 specific aims. 1) To fine map in heterogeneous stock (HS4) animals (to a resolution of 1 cM or less) 7 high quality QTLs for consumption and acute withdrawal. Mapping in HS4 will provide QTL resolution of approximately 1-2 cM. 2) To integrate the QTL data with interval relevant gene expression and sequence data. As each interval will be completely sequenced, all causative polymorphisms will be detected. In addition to standard oligonucleotide gene expression analysis, we will test the idea that some QTLs may be generated by alternative exon usage. 3) To determine in the STSB lines the gene networks associated with consumption and acute withdrawal. The clusters (modules) of genes coincidently associated with consumption and withdrawal will be interrogated to determine if there is overlap with the candidate quantitative trait genes generated from aims 1 and 2. 4) To determine if the consumption and withdrawal modules identified in aim 3 are also detected in a more genetically diverse mouse population.
Aim 4 will employ short-term selective breeding from an outbred population of the collaborative cross mouse. To our knowledge, this is the first test for a behavioral trait of the idea that "network" or "module" trumps genetic diversity.

Public Health Relevance

The proposed work attempts to understand the genetics of ethanol response. The eventual goal is to determine which gene or genes make some individuals more prone to develop alcoholism than others. With this information in hand, it should be possible to develop new therapeutic strategies.

Agency
National Institute of Health (NIH)
Institute
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Type
Research Project (R01)
Project #
5R01AA011034-18
Application #
8475405
Study Section
Neurotoxicology and Alcohol Study Section (NAL)
Program Officer
Parsian, Abbas
Project Start
1996-03-01
Project End
2015-05-31
Budget Start
2013-06-01
Budget End
2014-05-31
Support Year
18
Fiscal Year
2013
Total Cost
$326,950
Indirect Cost
$114,645
Name
Oregon Health and Science University
Department
Other Basic Sciences
Type
Schools of Medicine
DUNS #
096997515
City
Portland
State
OR
Country
United States
Zip Code
97239
Chesler, Elissa J; Gatti, Daniel M; Morgan, Andrew P et al. (2016) Diversity Outbred Mice at 21: Maintaining Allelic Variation in the Face of Selection. G3 (Bethesda) 6:3893-3902
Urban, Daniel J; Zhu, Hu; Marcinkiewcz, Catherine A et al. (2016) Elucidation of The Behavioral Program and Neuronal Network Encoded by Dorsal Raphe Serotonergic Neurons. Neuropsychopharmacology 41:1404-15
Thanos, Panayotis K; Michaelides, Mike; Subrize, Mike et al. (2015) Roux-en-Y Gastric Bypass Alters Brain Activity in Regions that Underlie Reward and Taste Perception. PLoS One 10:e0125570
Zheng, Christina L; Wilmot, Beth; Walter, Nicole Ar et al. (2015) Splicing landscape of the eight collaborative cross founder strains. BMC Genomics 16:52
Iancu, Ovidiu D; Colville, Alexandre; Oberbeck, Denesa et al. (2015) Cosplicing network analysis of mammalian brain RNA-Seq data utilizing WGCNA and Mantel correlations. Front Genet 6:174
Metten, Pamela; Iancu, Ovidiu D; Spence, Stephanie E et al. (2014) Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects. Alcohol Clin Exp Res 38:2915-24
Hitzemann, Robert; Bottomly, Daniel; Iancu, Ovidiu et al. (2014) The genetics of gene expression in complex mouse crosses as a tool to study the molecular underpinnings of behavior traits. Mamm Genome 25:12-22
Hitzemann, Robert; Darakjian, Priscila; Walter, Nikki et al. (2014) Introduction to sequencing the brain transcriptome. Int Rev Neurobiol 116:1-19
Iancu, Ovidiu D; Oberbeck, Denesa; Darakjian, Priscila et al. (2013) Differential network analysis reveals genetic effects on catalepsy modules. PLoS One 8:e58951
Michaelides, Michael; Anderson, Sarah Ann R; Ananth, Mala et al. (2013) Whole-brain circuit dissection in free-moving animals reveals cell-specific mesocorticolimbic networks. J Clin Invest 123:5342-50

Showing the most recent 10 out of 57 publications