Individual variation of adipose gene expression and identification of covariated genes by cDNA microarrays

Abstract

Gene expression profiling through the application of microarrays provides comprehensive assessment of gene expression levels in a given tissue or cell population, as well as information on changes of gene expression in altered physiological or pathological situations. Microarrays are particularly suited to study interactions in the regulation of large numbers of different genes, since their expression is analyzed simultaneously. For improved understanding of the physiology of adipose tissue, and consequently obesity and diabetes, identification of covariability in gene expression was attempted by analysis of the individual variability of gene expression in subcutaneous white and brown fat of the Siberian dwarf hamster using microarrays containing approximately 300 cDNA fragments of adipose genes. No sex-dependant variability in gene expression could be found, and overall individual variability was rather low, with more than 80% of clones showing a coefficient of variation lower than 30%. Uncoupling protein 1 (UCP1) displayed a high variability of gene expression in brown fat, which was negatively correlated with the gene expression of complement factor B (FactB), implying a possible functional relationship.