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1.  Acute physical activity effects on cardiac gene expression 
Experimental physiology  2010;95(11):1071-1080.
Regular bouts of physical activity may cause changes in gene expression that accumulate over time and ultimately affect phenotypes, such as body weight, blood lipid profile, and tumor development. Furthermore, acute activity may affect gene expression and phenotypes differently depending on whether the individual is regularly inactive or active. One-month old male Sprague-Dawley rats (n=72) were equally divided into SED (standard laboratory cage, n=24), PA (large activity box, n=24), and EX (exercise wheel inside standard cage, n=24) groups. At three months of age, half the animals from each group were sacrificed at rest and the other half following 30 minutes of physical activity. RNA was extracted from cardiac tissue, and microarray analysis was performed on 27,000 genes. Select gene results were validated using qPCR. No gene expression differences occurred when comparing all 3-month old groups at rest. A relatively small percentage of genes (1.9%) were differentially expressed (p<0.05) following acute swim activity in all groups but only 37 unique and identifiable genes reached or exceeded two fold differences in expression. The genes Atf3, Fos, Apold1, and Pxdn were expressed differently among SED, PA and EX following acute activity, with a clear separation of the magnitude in gene expression with SED > PA > EX. Differences in gene expression levels in young physically inactive and active animals following acute activity have different regulatory roles in gene networks that affect health-related phenotypes.
doi:10.1113/expphysiol.2010.054858
PMCID: PMC2956844  PMID: 20696783
acute exercise; gene expression; physical activity
2.  Gene-resolution analysis of DNA copy number variation using oligonucleotide expression microarrays 
BMC Genomics  2007;8:111.
Background
Array-based comparative genomic hybridization (aCGH) is a high-throughput method for measuring genome-wide DNA copy number changes. Current aCGH methods have limited resolution, sensitivity and reproducibility. Microarrays for aCGH are available only for a few organisms and combination of aCGH data with expression data is cumbersome.
Results
We present a novel method of using commercial oligonucleotide expression microarrays for aCGH, enabling DNA copy number measurements and expression profiles to be combined using the same platform. This method yields aCGH data from genomic DNA without complexity reduction at a median resolution of approximately 17,500 base pairs. Due to the well-defined nature of oligonucleotide probes, DNA amplification and deletion can be defined at the level of individual genes and can easily be combined with gene expression data.
Conclusion
A novel method of gene resolution analysis of copy number variation (graCNV) yields high-resolution maps of DNA copy number changes and is applicable to a broad range of organisms for which commercial oligonucleotide expression microarrays are available. Due to the standardization of oligonucleotide microarrays, graCNV results can reliably be compared between laboratories and can easily be combined with gene expression data using the same platform.
doi:10.1186/1471-2164-8-111
PMCID: PMC1868757  PMID: 17470268

Results 1-2 (2)