This is a competing renewal application for a U01 grant entitled """"""""Neurocircuitry Mapping and Genotyping Core"""""""";the application is submitted as a member of the NIAAA sponsored """"""""Integrative Neuroscience Initiative on Alcoholism (INIA)-West (G. Koob, PI). The application continues the focus of the current funding period on both research and core activities. Key core activities of the current funding period were a) the mastery of the use of the Weighted Gene Co-variance Network Analysis (WGCNA) for moderate to large sample sizes (lancu et al. 2010) and b) the development of a strategy for and implementation of quantitative RNAseq (Bottomly et al, 2011;Appendix A). With these tools in hand, we propose 1) to directly sequence the transcriptome ( ~ 25,000,000 75 bp reads/sample) in both replicate High Drinking in the Dark (HDID) mouse lines and in the HS/NPT control animals and 2) to sequence the transcriptome HDID animals that have completed the chronic intermittent ethanol (CIE) procedure with the appropriate control groups. The tissues needed for this analysis will be provided by the Crabbe U01. As the HDID and controls are derived from a 8- way inbred strain cross (Hitzemann et al. 1994), RNAseq is particularity useful, given that masking oligonucleotide array data is never optimal (see Walter et al. 2007,2009). N = 32/group;previous work (lancu et al. 2010) has illustrated that samples of this size are adequate for the proposed analyses. Samples are collected by laser capture micro-dissection (LCM);the regional priority for analysis will be the central nucleus of the amygdala (CeA) >the infralimbic cortex (IL) >the prelimbic cortex (PL). The occipital cortex (OC) will be used as a control region.
Aim 1 focuses on binge drinking whereas aim 2 focuses on how chronic ethanol exposure affects ethanol consumption in limited access 2-bottle choice paradigm. Our working hypothesis is that differences between co-expression networks and not the differential expression of individual genes have the greatest translational value (see e.g. Oti et al. 2008;Zhao et al. 2010).
In Aim 3, samples from ethanol exposed macaques (Grant U01- INlA-Stress) will be sequenced. Data from the CeA and cortical areas 25 and 32 will be compared to the results obtained in specific aims 1 and 2.

Public Health Relevance

The purpose of the proposed research is to understand what genes are associated with animal models of excessive ethanol consumption. Detecting these genes and probably more importantly their associated gene networks may lead to new therapeutic targets for the treatment of alcoholism.

Agency
National Institute of Health (NIH)
Institute
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01AA013484-12
Application #
8328777
Study Section
Special Emphasis Panel (ZAA1-DD (50))
Program Officer
Grandison, Lindsey
Project Start
2001-09-27
Project End
2016-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
12
Fiscal Year
2012
Total Cost
$294,928
Indirect Cost
$103,416
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
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Iancu, Ovidiu D; Colville, Alexander; Walter, Nicole A R et al. (2018) On the relationships in rhesus macaques between chronic ethanol consumption and the brain transcriptome. Addict Biol 23:196-205
Iancu, Ovidiu Dan; Colville, Alex M; Wilmot, Beth et al. (2018) Gender-Specific Effects of Selection for Drinking in the Dark on the Network Roles of Coding and Noncoding RNAs. Alcohol Clin Exp Res :
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Colville, A M; Iancu, O D; Oberbeck, D L et al. (2017) Effects of selection for ethanol preference on gene expression in the nucleus accumbens of HS-CC mice. Genes Brain Behav 16:462-471
Hitzemann, Robert; Oberbeck, Denesa; Iancu, Ovidiu et al. (2017) Alignment of the transcriptome with individual variation in animals selectively bred for High Drinking-In-the-Dark (HDID). Alcohol 60:115-120
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
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

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