A major goal for post-genomic biology will be to understand how the one dimensional (1D) genome gives rise to the staggering 3D complexity of the mammalian brain. To address this problem, it will be necessary to spatially map transcripts, proteins, and the networks they form in the brain at a genome-wide level. In this Bioengineering Research Partnership, 3 groups with complementary expertise and an established history of collaboration will combine forces to achieve this goal. (1) At UCLA, Desmond Smith will map gene expression patterns at a genome-wide scale in the mouse brain at volumetric resolutions of 11 ul and 1 ul. This project will employ microarray technology in combination with voxelation, a method for rapid acquisition of expression patterns in the brain. (2) At PNNL, Dick Smith will use voxelation to map protein expression patterns at high throughput using mass spectrometry (FT-ICR MS), again at resolutions of 11 ul and 1 ul. (3) At USC, Richard Leahy will perform image analysis of the data produced by the first 2 aims to create 3D transcript and protein atlases and to extract meaning from the large multivariate data sets that will result. Thus, the first 2 aims will display the relationship between the transcriptome and the proteome in the 3D space of mammalian brain, while the third aim will display the relationships between the brain transcriptome and proteome in the conceptual ID space of the genome.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS050148-04
Application #
7485169
Study Section
Special Emphasis Panel (ZRG1-MDCN-K (55))
Program Officer
Tagle, Danilo A
Project Start
2005-09-20
Project End
2010-08-31
Budget Start
2008-09-01
Budget End
2009-08-31
Support Year
4
Fiscal Year
2008
Total Cost
$438,768
Indirect Cost
Name
University of California Los Angeles
Department
Pharmacology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
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An, Li; Ling, Haibin; Obradovic, Zoran et al. (2012) Learning pair-wise gene functional similarity by multiplex gene expression maps. BMC Bioinformatics 13 Suppl 3:S1
Ghazalpour, Anatole; Bennett, Brian; Petyuk, Vladislav A et al. (2011) Comparative analysis of proteome and transcriptome variation in mouse. PLoS Genet 7:e1001393
Zhang, Xu; Zhou, Jian-Ying; Chin, Mark H et al. (2010) Region-specific protein abundance changes in the brain of MPTP-induced Parkinson's disease mouse model. J Proteome Res 9:1496-509
Petyuk, Vladislav A; Qian, Wei-Jun; Smith, Richard D et al. (2010) Mapping protein abundance patterns in the brain using voxelation combined with liquid chromatography and mass spectrometry. Methods 50:77-84
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Smith, Desmond J (2009) Mitochondrial dysfunction in mouse models of Parkinson's disease revealed by transcriptomics and proteomics. J Bioenerg Biomembr 41:487-91
Park, Christopher C; Petyuk, Vladislav A; Qian, Wei-Jun et al. (2009) Dual spatial maps of transcript and protein abundance in the mouse brain. Expert Rev Proteomics 6:243-9
An, Li; Obradovic, Zoran; Smith, Desmond et al. (2009) Mining Association Rules among Gene Functions in Clusters of Similar Gene Expression Maps. IEEE Int Conf Bioinform Biomed Workshops 2009:254-259
Chin, Mark H; Qian, Wei-Jun; Wang, Haixing et al. (2008) Mitochondrial dysfunction, oxidative stress, and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson's disease. J Proteome Res 7:666-77

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