Achieving greater understanding of the genomic influence on milk synthesis in dairy cows represents a daunting challenge. Bovine-specific microarrays have allowed for high-throughput gene expression analysis of the mammary transcriptome. However, real-time PCR (qPCR) still represents the method of choice for accurate expression profiling of small numbers of genes and verification of key microarray relationships. This method is extremely sensitive but requires data normalization to account for analytical errors. Ideally, expression of genes used as internal controls should not be affected by specific treatments or physiological state. Mammary biopsies were collected from five cows each at −15, 1, 15, 30, 60, 120, and 240 days relative to parturition for gene expression profiling. We evaluated expression of nine genes ( RPS9, ACTB, GAPD, GTP, ITGB4BP, MRPL39, RPS23, RPS15, and UXT) that could serve as internal controls in mammary tissue using qPCR. Due to gradual increases in mammary RNA concentration (μg/mg tissue) over lactation, all genes investigated experienced a dilution effect. We used pairwise comparison of expression ratios to analyze the reliability of these genes as internal controls. UXT, RPS9, and RPS15 had the most stable expression ratios across cow and time. We also assessed co-regulation among genes through network analysis. Network analysis suggested co-regulation among most of the genes examined, with MYC playing a central role. Pairwise comparison was suitable for finding appropriate internal controls in mammary gland tissue. Results showed that the geometrical average of UXT, RPS9, and RPS15 expression could be used as internal control for longitudinal mammary gene expression profiling.
Selection of optimal internal controls for gene expression profiling of liver disease
