Computational protocol: Selection of Internal Control Genes for Real-Time Quantitative PCR in Ovary and Uterus of Sows across Pregnancy

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Protocol publication

[…] Ten potential reference genes were chosen for being frequently used as endogenous controls in expression studies by different authors , , : beta-actin (ACTB), beta-2 microglobulin (B2M), guanine nucleotide binding protein (G protein), beta polypeptide 2-like 1 (GNB2L1), hydroxymethylbilane synthase (HMBS), hypoxanthine phosphoribosyltransferase 1 (HPRT), ribosomal protein L32 (RPL32), succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA), TATA box binding protein (TBP), ubiquitin C (UBC), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide (YWHAZ). For each gene, a set of primers was designed with Primer Express Software v2.0 (Applied Biosystems, Foster City, USA) to quantitate the level of expression by real-time qPCR (). Primer pairs were designed so as to fall in different exons (as inferred from human or pig gene organization data) and to amplify a fragment of less than 250bp (). Fleige and Pfaffl demonstrated that real-time qPCR based on short amplicons (70–250 bp) was independent of RNA integrity and therefore give more accurate results than long amplicons. Real time PCR reactions were performed in triplicate for each individual sample in a final volume of 5 µl containing 1x SYBRgreen PCR Master Mix (Applied Biosystems), 100 nM each primer and 1 µl of 1∶10 diluted cDNA on an ABI 7500 Real Time PCR System (Applied Biosystems). As a calibrator we used a pool of all RNA samples in the experiment. Data normalization and analysis were performed by the E−ΔCt method using as a calibrator a pool of all RNA samples of both tissues used in this study. PCR efficiency (E) was calculated as follow:where S is the slope from the standard curve . A dissociation curve analysis evidenced a single peak for all reactions indicating the specificity of the amplification and the absence of primer dimer formation. Ten-fold serial dilution of a cDNA template (generated from a mix of all RNA samples involved in this experiment) showed for all candidate reference genes an average amplification efficiency of 93.19% and an average correlation coefficient (R2) of 0.99 (). [...] Gene expression stability was evaluated with three different statistical algorithms: BestKeeper , geNorm and NormFinder . The three different software packages make use of the Ct values to determine the most stably expressed genes. BestKeeper analyzes the inter-gene relationship, calculating the Pearson correlation coefficient (r), the probability and the sample integrity and expression stability within each reference gene with an intrinsic variance of expression . Data from the genes showing higher correlation values is combined to computes the geometric mean of Ct values (BestKeeper Index). Next, the Pearson’s correlation coefficient between each candidate reference gene and the index (rI) is calculated, which gives and estimation of the contribution of the gene to the BestKeeper Index. GeNorm determines the pairwise variation of a particular gene with all other control genes as the standard deviation of the logarithmically transformed expression ratios. A measure of internal control gene-stability (M) is defined by GeNorm as the average of the pairwise variation of one gene with all the other potential reference genes . The lowest the M value, the more stable the expression of that gene is. To select the best-performing reference genes, the program recalculates the M stability measures after removal of the least stable gene and repeats the process until only the two most stable genes remain . To test the minimum number of reference gene needed for adequate data normalization, geNorm calculates a pairwise variation (V) between using n and n+1 reference genes. Large V values indicate a significant effect of the additional gene on data normalization and endorse the need of including this gene among the controls. On the other hand, NormFinder is a model-based approach that enables estimation not only of the overall variation of the candidate normalization genes, but also of the variation between subgroups of the same sample set. NormFinder combines the intra- and intergroup variation to estimate, for each individual gene, a stability value (Sv), which represents a practical measure of the systematic error that will be introduced when using the investigated gene. Candidate reference genes can then be ranked according to the Sv value, where lowest values correspond to the most stable genes. […]

Pipeline specifications

Software tools Primer Express, BestKeeper, NormFinder
Application qPCR
Organisms Sus scrofa