Detecting genetic variation in microarray expression data.

The use of high-density oligonucleotide arrays to measure the expression levels of thousands of genes in parallel has become commonplace. To take further advantage of the growing body of data, we developed a method, termed "GeSNP," to mine the detailed hybridization patterns in oligonucleotide array expression data for evidence of genetic variation. To demonstrate the performance of the algorithm, the hybridization patterns in data obtained previously from SAMP8/Ta, SAMP10/Ta, and SAMR1/Ta inbred mice and from humans and chimpanzees were analyzed. Genes with consistent strain-specific and species-specific hybridization pattern differences were identified, and approximately 90% of the candidate genes were independently confirmed to harbor sequence differences. Importantly, the quality of gene expression data was also improved by masking the probes of regions with putative sequence differences between species and strains. To illustrate the application to human disease groups, data from an inflammatory bowel disease study were analyzed. GeSNP identified sequence differences in candidate genes previously discovered in independent association and linkage studies and uncovered many promising new candidates. This approach enables the opportunistic extraction of genetic variation information from new or pre-existing gene expression data obtained with high-density oligonucleotide arrays.

Mechanisms of aging in senescence-accelerated mice.

BACKGROUND: Progressive neurological dysfunction is a key aspect of human aging. Because of underlying differences in the aging of mice and humans, useful mouse models have been difficult to obtain and study. We have used gene-expression analysis and polymorphism screening to study molecular senescence of the retina and hippocampus in two rare inbred mouse models of accelerated neurological senescence (SAMP8 and SAMP10) that closely mimic human neurological aging, and in a related normal strain (SAMR1) and an unrelated normal strain (C57BL/6J). RESULTS: The majority of age-related gene expression changes were strain-specific, with only a few common pathways found for normal and accelerated neurological aging. Polymorphism screening led to the identification of mutations that could have a direct impact on important disease processes, including a mutation in a fibroblast growth factor gene, Fgf1, and a mutation in and ectopic expression of the gene for the chemokine CCL19, which is involved in the inflammatory response. CONCLUSION: We show that combining the study of inbred mouse strains with interesting traits and gene-expression profiling can lead to the discovery of genes important for complex phenotypes. Furthermore, full-genome polymorphism detection, sequencing and gene-expression profiling of inbred mouse strains with interesting phenotypic differences may provide unique insights into the molecular genetics of late-manifesting complex diseases.