Genomic convergence: identifying candidate genes for Parkinson's disease by combining serial analysis of gene expression and genetic linkage.

We present a multifactorial, multistep approach called genomic convergence that combines gene expression with genomic linkage analysis to identify and prioritize candidate susceptibility genes for Parkinson's disease (PD). To initiate this process, we used serial analysis of gene expression (SAGE) to identify genes expressed in two normal substantia nigras (SN) and adjacent midbrain tissue. This identified over 3700 transcripts, including the three most abundant SAGE tags, which did not correspond to any known genes or ESTs. We developed high-throughput bioinformatics methods to map the genes corresponding to these tags and identified 402 SN genes that lay within five large genomic linkage regions, previously identified in 174 multiplex PD families. These genes represent excellent candidates for PD susceptibility alleles and further genomic convergence and analyses.

Duke Scholars

Author Michael Arthur Hauser Medicine, Medical Genetics

Author Yi-Ju Li Biostatistics & Bioinformatics, Division of Integrative Geno ...

Author Elizabeth Rebecca Hauser Biostatistics & Bioinformatics

Author Fred Samuel Dietrich Molecular Genetics and Microbiology