Validation of Reference Housekeeping Genes for Gene Expression Studies in Western Corn Rootworm (Diabrotica virgifera virgifera)

Quantitative Real-time PCR (qRT-PCR) is a powerful technique to investigate comparative gene expression. In general, normalization of results using a highly stable housekeeping gene (HKG) as an internal control is recommended and necessary. However, there are several reports suggesting that regulation of some HKGs is affected by different conditions. The western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), is a serious pest of corn in the United States and Europe. The expression profile of target genes related to insecticide exposure, resistance, and RNA interference has become an important experimental technique for study of western corn rootworms; however, lack of information on reliable HKGs under different conditions makes the interpretation of qRT-PCR results difficult. In this study, four distinct algorithms (Genorm, NormFinder, BestKeeper and delta-CT) and five candidate HKGs to genes of reference (β-actin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; β-tubulin; RPS9, ribosomal protein S9; EF1a, elongation factor-1α) were evaluated to determine the most reliable HKG under different experimental conditions including exposure to dsRNA and Bt toxins and among different tissues and developmental stages. Although all the HKGs tested exhibited relatively stable expression among the different treatments, some differences were noted. Among the five candidate reference genes evaluated, β-actin exhibited highly stable expression among different life stages. RPS9 exhibited the most similar pattern of expression among dsRNA treatments, and both experiments indicated that EF1a was the second most stable gene. EF1a was also the most stable for Bt exposure and among different tissues. These results will enable researchers to use more accurate and reliable normalization of qRT-PCR data in WCR experiments.     

The Use of Laser Microdissection in the Identification of Suitable Reference Genes for Normalization of Quantitative Real-Time PCR in Human FFPE Epithelial Ovarian Tissue Samples

Quantitative real-time PCR (qPCR) is a powerful and reproducible method of gene expression analysis in which expression levels are quantified by normalization against reference genes. Therefore, to investigate the potential biomarkers and therapeutic targets for epithelial ovarian cancer by qPCR, it is critical to identify stable reference genes. In this study, twelve housekeeping genes (ACTB, GAPDH, 18S rRNA, GUSB, PPIA, PBGD, PUM1, TBP, HRPT1, RPLP0, RPL13A, and B2M) were analyzed in 50 ovarian samples from normal, benign, borderline, and malignant tissues. For reliable results, laser microdissection (LMD), an effective technique used to prepare homogeneous starting material, was utilized to precisely excise target tissues or cells. One-way analysis of variance (ANOVA) and nonparametric (Kruskal-Wallis) tests were used to compare the expression differences. NormFinder and geNorm software were employed to further validate the suitability and stability of the candidate genes. Results showed that epithelial cells occupied a small percentage of the normal ovary indeed. The expression of ACTB, PPIA, RPL13A, RPLP0, and TBP were stable independent of the disease progression. In addition, NormFinder and geNorm identified the most stable combination (ACTB, PPIA, RPLP0, and TBP) and the relatively unstable reference gene GAPDH from the twelve commonly used housekeeping genes. Our results highlight the use of homogeneous ovarian tissues and multiple-reference normalization strategy, e.g. the combination of ACTB, PPIA, RPLP0, and TBP, for qPCR in epithelial ovarian tissues, whereas GAPDH, the most commonly used reference gene, is not recommended, especially as a single reference gene.     

Evaluating a set of reference genes for expression normalization in multiple tissues and skeletal muscle at different development stages in pigs using quantitative real-time polymerase chain reaction

Gene expression analysis requires the use of reference genes consistently expressed under various conditions. In many cases, however, the commonly used reference genes are not uniformly expressed independently of tissues or environmental conditions. To provide a set of reliable reference genes in pigs, we used quantitative polymerase chain reaction to examine expression of six common reference genes (GAPDH, ACTB, H3F3A, HPRT1, RPL32, and RPS18) in adult tissues and prenatal skeletal muscles at 33, 65, and 90 days postcopulation from Tongcheng (obese-type) and Landrace (lean-type) pigs. The expression stability of these reference genes was evaluated by NormFinder, BestKeeper, and geNorm methods. Our data suggest that the reference genes were expressed variably in different tissues, developmental stages and breeds. RPS18, PRL32, and H3F3A could be used as internal controls to normalize gene expression in pig tissues and developmental skeletal muscle. The combination of internal control genes was necessary for accurate expression normalization. During skeletal muscle development, H3F3A and RPS18 would be the most appropriate combination to normalize gene expression in Tongcheng pigs, whereas the combination of PRL32 and RPS18 would be more suitable in Landrace pigs. In different tissues, the expression of PRL32 and RPS18 was the most consistent, and the combination of three genes (RPL32, RPS18, and H3F3A) is the most suitable for accurate normalization.     

Microarray-driven validation of reference genes for quantitative real-time polymerase chain reaction in a rat vocal fold model of mucosal injury

Relative quantification by normalization against a stably expressed reference gene is a widely used data analysis method in microarray and quantitative real-time polymerase chain reaction (qRT-PCR) platforms; however, recent evidence suggests that many commonly utilized reference genes are unstable in certain experimental systems and situations. The primary aim of this study, therefore, was to screen and identify stably expressed reference genes in a well-established rat model of vocal fold mucosal injury. We selected and evaluated the expression stability of nine candidate reference genes. Ablim1, Sptbn1, and Wrnip1 were identified as stably expressed in a model-specific microarray dataset and were further validated as suitable reference genes in an independent qRT-PCR experiment using 2^−ΔCT and pairwise comparison-based (geNorm) analyses. Parallel analysis of six commonly used reference genes identified Sdha as the only stably expressed candidate in this group. Sdha, Sptbn1, and the geometric mean of Sdha and Sptbn1 each provided accurate normalization of target gene Tgfb1; Gapdh, the least stable candidate gene in our dataset, provided inaccurate normalization and an invalid experimental result. The stable reference genes identified here are suitable for accurate normalization of target gene expression in vocal fold mucosal injury experiments.     

Validation of reference genes for RT-qPCR analysis of CYP4T expression in crucian carp

Reference genes are commonly used for normalization of target gene expression during RT-qPCR analysis. However, no housekeeping genes or reference genes have been identified to be stable across different tissue types or under different experimental conditions. To identify the most suitable reference genes for RT-qPCR analysis of target gene expression in the hepatopancreas of crucian carp (Carassius auratus) under various conditions (sex, age, water temperature, and drug treatments), seven reference genes, including beta actin (ACTB), beta-2 microglobulin (B2M), embryonic elongation factor-1 alpha (EEF1A), glyceraldehyde phosphate dehydrogenase (GAPDH), alpha tubulin (TUBA), ribosomal protein l8 (RPL8) and glucose-6-phosphate dehydrogenase (G6PDH), were evaluated in this study. The stability and ranking of gene expression were analyzed using three different statistical programs: GeNorm, Normfinder and Bestkeeper. The expression errors associated with selection of the genes were assessed by the relative quantity of CYP4T. The results indicated that all the seven genes exhibited variability under the experimental conditions of this research, and the combination of ACTB/TUBA/EEF1A or of ACTB/EEF1A was the best candidate that raised the accuracy of quantitative analysis of gene expression. The findings highlighted the importance of validation of housekeeping genes for research on gene expression under different conditions of experiment and species.     

Selection of suitable reference genes from bone cells in large gradient high magnetic field based on GeNorm algorithm

Studies of animals and humans subjected to spaceflight demonstrate that weightlessness negatively affects the mass and mechanical properties of bone tissue. Bone cells could sense and respond to the gravity unloading, and genes sensitive to gravity change were considered to play a critical role in the mechanotransduction of bone cells. To evaluate the fold-change of gene expression, appropriate reference genes should be identified because there is no housekeeping gene having stable expression in all experimental conditions. Consequently, expression stability of ten candidate housekeeping genes were examined in osteoblast-like MC3T3-E1, osteocyte-like MLO-Y4, and preosteoclast-like FLG29.1 cells under different apparent gravities (μg, 1 g, and 2 g) in the high-intensity gradient magnetic field produced by a superconducting magnet. The results showed that the relative expression of these ten candidate housekeeping genes was different in different bone cells; Moreover, the most suitable reference genes of the same cells in altered gravity conditions were also different from that in strong magnetic field. It demonstrated the importance of selecting suitable reference genes in experimental set-ups. Furthermore, it provides an alternative choice to the traditionally accepted housekeeping genes used so far about studies of gravitational biology and magneto biology.     

Identification of novel universal housekeeping genes by statistical analysis of microarray data

Housekeeping genes are widely used as internal controls in a variety of study types, including real time RT-PCR, microarrays, Northern analysis and RNase protection assays. However, even commonly used housekeeping genes may vary in stability depending on the cell type or disease being studied. Thus, it is necessary to identify additional housekeeping-type genes that show sample-independent stability. Here, we used statistical analysis to examine a large human microarray database, seeking genes that were stably expressed in various tissues, disease states and cell lines. We further selected genes that were expressed at different levels, because reference and target genes should be present in similar copy numbers to achieve reliable quantitative results. Real time RT-PCR amplification of three newly identified reference genes, CGI-119, CTBP1 and GOLGAl, alongside three well-known housekeeping genes, B2M, GAPD, and TUBB, confirmed that the newly identified genes were more stably expressed in individual samples with similar ranges. These results collectively suggest that statistical analysis of microarray data can be used to identify new candidate housekeeping genes showing consistent expression across tissues and diseases. Our analysis identified three novel candidate housekeeping genes (CGI-119, GOLGA1, and CTBP1) that could prove useful for normalization across a variety of RNA-based techniques.     

Selection of suitable reference genes from bone cells in large gradient high magnetic field based on GeNorm algorithm

Studies of animals and humans subjected to spaceflight demonstrate that weightlessness negatively affects the mass and mechanical properties of bone tissue. Bone cells could sense and respond to the gravity unloading, and genes sensitive to gravity change were considered to play a critical role in the mechanotransduction of bone cells. To evaluate the fold-change of gene expression, appropriate reference genes should be identified because there is no housekeeping gene having stable expression in all experimental conditions. Consequently, expression stability of ten candidate housekeeping genes were examined in osteoblast-like MC3T3-E1, osteocyte-like MLO-Y4, and preosteoclast-like FLG29.1 cells under different apparent gravities (μg, 1?g, and 2?g) in the high-intensity gradient magnetic field produced by a superconducting magnet. The results showed that the relative expression of these ten candidate housekeeping genes was different in different bone cells; Moreover, the most suitable reference genes of the same cells in altered gravity conditions were also different from that in strong magnetic field. It demonstrated the importance of selecting suitable reference genes in experimental set-ups. Furthermore, it provides an alternative choice to the traditionally accepted housekeeping genes used so far about studies of gravitational biology and magneto biology.     

Bone to pick: the importance of evaluating reference genes for RT-qPCR quantification of gene expression in craniosynostosis and bone-related tissues and cells

ABSTRACT: BACKGROUND: RT-qPCR is a common tool for quantification of gene expression, but its accuracy is dependent on the choice and stability (steady state expression levels) of the reference gene/s used for normalization. To date, in the bone field, there have been few studies to determine the most stable reference genes and, usually, RT-qPCR data is normalised to non-validated reference genes, most commonly GAPDH, ACTB and 18 S rRNA. Here we draw attention to the potential deleterious impact of using classical reference genes to normalise expression data for bone studies without prior validation of their stability. RESULTS: Using the geNorm and Normfinder programs, panels of mouse and human genes were assessed for their stability under three different experimental conditions: 1) disease progression of Crouzon syndrome (craniosynostosis) in a mouse model, 2) proliferative culture of cranial suture cells isolated from craniosynostosis patients and 3) osteogenesis of a mouse bone marrow stromal cell line. We demonstrate that classical reference genes are not always the most 'stable' genes and that gene 'stability' is highly dependent on experimental conditions. Selected stable genes, individually or in combination, were then used to normalise osteocalcin and alkaline phosphatase gene expression data during cranial suture fusion in the craniosynostosis mouse model and strategies compared. Strikingly, the expression trends of alkaline phosphatase and osteocalcin varied significantly when normalised to the least stable, the most stable or the three most stable genes. CONCLUSION: To minimise errors in evaluating gene expression levels, analysis of a reference panel and subsequent normalization to several stable genes is strongly recommended over normalization to a single gene. In particular, we conclude that use of single, non-validated "housekeeping" genes such as GAPDH, ACTB and 18 S rRNA, currently a widespread practice by researchers in the bone field, is likely to produce data of questionable reliability when changes are 2 fold or less, and such data should be interpreted with due caution.