Internal Controls for Quantitative Polymerase Chain Reaction of Swine Mammary Glands During Pregnancy and Lactation

Abstract

High-throughput microarray analysis is an efficient means of obtaining a genome-wide view of transcript profiles across physiological states. However, quantitative PCR (qPCR) remains the chosen method for high-precision mRNA abundance analysis. Essential for reliability of qPCR data is normalization using appropriate internal control genes (ICG), which is now, more than ever before, a fundamental step for accurate gene expression profiling. We mined mammary tissue microarray data on >13,000 genes at -34, -14, 0, 7, 14, 21, and 28 d relative to parturition in 27 crossbred primiparous gilts to identify suitable ICG. Initial analysis revealed TBK1, PCSK2, PTBP1, API5, VAPB, QTRT1, TRIM41, TMEM24, PPP2R5B, and AP1S1 as the most stable genes (sample/reference = 1 +/- 0.2). We also included 9 genes previously identified as ICG in bovine mammary tissue. Gene network analysis of the 19 genes identified AP1S1, API5, MTG1, VAPB, TRIM41, MRPL39, and RPS15A as having no known co-regulation. In addition, UXT and ACTB were added to this list, and mRNA abundance of these 9 genes was measured by qPCR. Expression of all 9 of these genes was decreased markedly during lactation. In a previous study with bovine mammary tissue, mRNA of stably expressed genes decreased during lactation due to a dilution effect brought about by large increases in expression of highly abundant genes. To verify this effect, highly abundant mammary genes such as CSN1S2, SCD, FABP3, and LTF were evaluated by qPCR. The tested ICG had a negative correlation with these genes, demonstrating a dilution effect in the porcine mammary tissue. Gene stability analysis identified API5, VABP, and MRPL39 as the most stable ICG in porcine mammary tissue and indicated that the use of those 3 genes was most appropriate for calculating a normalization factor. Overall, results underscore the importance of proper validation of internal controls for qPCR and highlight the limitations of using absence of time effects as the criteria for selection of appropriate ICG. Further, we showed that use of the same ICG from one organism might not be suitable for qPCR normalization in other species.

Identification of reference genes for RT-qPCR in ovine mammary tissue during late pregnancy and lactation and in response to maternal nutritional programming

“…The ability of RT-qPCR to accurately detect changes in gene expression relies upon the selection of stably expressed reference genes. Studies in other species have shown that the expression of commonly used reference genes may vary between physiological and nutritional states and experimental treatments (2,4,19,37). Variation in expression of reference genes may limit the ability to detect and verify changes in expression of target genes, thus reducing the percentage of genes that validate.…”

“…Therefore, in the present study, candidate reference genes were selected from RNA-seq expression data (PRP3, CUL1, SF1, SENP2, and IPO9) and from studies conducted in other species [MRPL39 (4,19,37), EIF6 (4), and ATP1A1 (9,24)]. These genes were evaluated across pooled and individual RNA samples.…”

“…Potential modulation of gene expression through maternal nutritional programming may also contribute to variation in expression of reference genes. While studies in other species have identified reference genes for bovine and porcine mammary tissue during pregnancy and lactation (4,37), there are no studies, to date, for the ovine mammary gland and no studies investigating stability of reference genes in offspring of maternal nutritional programming studies.…”

Selection of reference genes for gene expression studies in porcine skeletal muscle using SYBR green qPCR

“…A few studies have examined reference genes in porcine cells, tissues and organs (Erkens et al, 2006;Foss et al, 1998;Kuijk et al, 2007;Nygard et al, 2007;Tramontana et al, 2008), and reveal that GAPDH and ACTB, two commonly used reference genes, are not necessarily constitutively expressed. Reference genes for skeletal muscle at different developmental stages in pigs have not yet been studied, however.…”

Selection and use of reference genes in mouse mammary glands

“…Vandesompele et al (2002) described the geNorm software to identify the most stable reference genes in a given set of tissue samples, and to determine the optimal number of genes required for reliable normalization of qRT-PCR data. geNorm has been applied to the identification of reference genes in bovine and swine mammary gland (Bionaz and Loor, 2007;Tramontana et al, 2008), but not in mouse mammary gland.…”