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Multiplex three dimensional brain gene expression mapping in a mouse model of Parkinsonís disease

Vanessa M. Brown, Alex Ossadtchi, Arshad H. Khan, Simon Yee, William P. Melega, Simon R. Cherry, Richard M. Leahy, and Desmond Smith



We are pleased to invite you to explore this web supplementary site for Multiplex three dimensional brain gene expression mapping in a mouse model of Parkinsonís disease.Through this web site you may access the microarray raw data acquired while performing this research, as well as the computer algorithms used to analyze the raw data and to create the reconstructed images.If you have any questions regarding the paper or the contents of this supplementary web site, you may contact us at dsmith@mednet.ucla.edu.


Voxelation, a novel technology designed to produce high throughput three-dimensional imaging of gene expression patterns in the brain.In these experiments, mouse brains were dissected into 40 voxels, or cubes, by cutting 10 serial coronal sections and transecting each coronal section into fourths. You may access the voxelation scheme through this web site.


Using microarrays, the gene expression pattern of 9000 genes was acquired for both a normal and a pharmacological model of Parkinsonís disease (PD) mouse brain.We have provided the raw data from each of the microarray hybridizations performed for these experiments.The gene list of the microarray is also provided. Please note that the gene list is a large file and may take some time to download.A subset of genes found to be differentially expressed between normal and Parkinsonís brains by microarray were verified using real-time RT-PCR.The primers and probe sequences used for the QRT-PCR verification can be found at this site

Computer Algorithms

Computer algorithms were used to perform quality control analyses, reveal a network of correlated genes shared between the normal brain and PD brain and reconstruct the SVD based images.Supplementary figures demonstrating correlated gene expression patterns can also be viewed.



Principle Component Reconstruction


Bioinformatic Analysis

From the analyses of the microarray data by computer algorithms, genes that were correlated were identified and a search for putative regulatory regions was performed.This search resulted in the creation of a gene network based on our experimental data.


This work was supported by grants from the Dana Foundation, Merck Genome Research Institute, W.M. Keck Foundation, National Foundation for Functional Brain Imaging, NIH (DAO15802-01), NSF (0079375), Staglin Music Festival, NARSAD Young Investigator Award, and the UCLA School of Medicine.


Interesting Links

Smith Lab

Leahy Lab

Melega Lab

Cherry Lab

UCLA Department of Molecular & Medical Pharmacology

Crump Institute of Biological Imaging

Genome Research