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Reference gene selection for quantitative PCR studies in sheep neutrophils.

William R Vorachek | Hugejiletu | Gerd Bobe | Jean A Hall
International journal of molecular sciences | 2013

Reference genes are essential for studying mRNA expression with quantitative PCR (qPCR). We investigated 11 potential neutrophil reference genes (RPL19, GAPDH, ACTB, B2M, HPRT, G6PD, TFRC, PGK1, YWHAZ, SDHA and GYPC) for sheep under disease conditions of foot rot (FR) and with or without Se supplementation. Initial screening was based on gene expression level (<28 Cq cycles) and variability (SD < 1.5 Cq cycles) and excluded TFRC, GYPC and HPRT from further analysis. Expression stability of the remaining genes was evaluated using four software programs: geNorm, NormFinder, BestKeeper and the comparative delta Cq method. The neutrophil reference genes, G6PD, YWHAZ, GAPDH, RPL19 and SDHA, consistently ranked among the top five most stable genes under these experimental conditions. The SDHA gene expression was not stable in FR-diseased sheep receiving Se treatment and, thus, cannot be recommended as a reference gene. The commonly used genes, PGK1, ACTB and B2M, were not reliable reference genes, underscoring the need to validate neutrophil reference genes under different experimental conditions. Multiple references genes rather than a single gene may provide more robust and reliable results. The best pair of reference genes was SDHA/G6PD in healthy sheep and GADPH/YWHAZ in FR-diseased sheep.

Pubmed ID: 23722658

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RefSeq (tool)

RRID:SCR_003496

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

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geNORM (tool)

RRID:SCR_006763

Software to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.

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