Core Component 3:
Molecular and Bioinformatics Support Core
Director: John Belknap
Molecular Genetics Unit (MGU): Lead Co-Director: Kari Buck; Co-Director: Robert Hitzemann
Bioinformatics and Biostatistics Unit (BBU): Lead Co-Director: Shannon McWeeney; Co-Director: Robert Searles
Dr. John Belknap is the Director of this Core, which is comprised of two units. The Molecular Genetics Unit [MGU] is headed by Kari Buck in close concert with Robert Hitzemann, and the Bioinformatics & Biostatistics Unit [BBU] headed by Shannon McWeeney in conjunction with Christina Harrington and Kemal Sonmez. The BBU will focus on statistical, quantitative genetic, computational and bioinformatics support, especially concerning microarray data analysis, QTL analysis, gene network analyses and further central database development. In addition, the BBU will be responsible for providing statistical, computational and bioinformatics support of a more general nature, and take part in training our students and postdocs in these areas.
This Core will facilitate hypothesis-driven (candidate gene) and hypothesis-generating (network) analyses to elucidate the genetic determinants of alcohol preference/consumption, withdrawal and impulsivity. In some cases the underlying gene will be the same in animal models (mice or nonhuman primates) and humans. In other cases animal model research will identify a gene network relevant in humans. Analyses of both candidate genes and networks will be more powerful than either alone to provide the interlocking levels of proof to move from gene/network to mechanism, and better prevent and treat alcohol abuse/dependence.
The MGU will focus on providing molecular genetic support to PARC components. During the past 5 years of support, this Core has moved from identifying chromosomal regions (called quantitative trait loci, QTLs) that contain genes involved in ethanol responses to identifying, in the case of some QTLs, the causative gene or quantitative trait gene (QTG) (e.g., Mpdz for chromosome 4 QTLs). We have made good progress in the same direction for additional QTLs in the identification of high-quality QTG candidates (e.g., Kcnj9 for chromosome 1 QTLs) QTG and at the gene network level. These now require rigorous testing to be accepted as having causal roles in the effects of ethanol, most specifically on preference drinking, withdrawal severity and impulsivity. Providing technical support for this testing is a major goal of this Core.
An important goal of behavioral genomics is to identify individual genes and gene networks underlying phenotypic variation, and to elucidate the mechanism by which the gene and gene network affect behavior. In the next 5 years of support, the role of the Core will continue to provide expertise for both candidate gene hypothesis-driven (e.g., RNA interference [RNAi]) and hypothesis-generating (e.g., weighted gene co-expression networks) analyses in mice and nonhuman primates. Complementary strategies will emphasize identification and definitive proof of genes and gene networks involved in ethanol preference/consumption, withdrawal, and genetically correlated traits (including impulsivity). Genes will be tested for differential expression and/or sequence (coding and regulatory) using appropriate animal models. Priority for expression and sequence comparisons will be determined based on several criteria, including putative biological role and likely relevance to ethanol action. Database sequence information will also be used to design oligonucleotide primers that flank genes of interest for real-time quantitative PCR (QPCR) to test for genotype-differences in expression. In some cases, PCR amplification of the coding and regulatory regions from appropriate strains will be needed for DNA sequencing of PCR products to identify sequence differences.
Both units of Core Component #3 (the Molecular Genetics Unit [MGU] and the Bioinformatics & Biostatistics Unit [BBU]) will be active in all years of requested Center support. Both units will support all five Center research components, as well as pilot projects in Component #10 and several other NIH (R01, R37, U01, K01, F31 and F32) and VA grants focused on alcohol research.
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