Identification of Optimal Reference Genes for Gene Expression Normalization in a Wide Cohort of Endometrioid Endometrial Carcinoma Tissues

Accurate normalization is a primary component of a reliable gene expression analysis based on qRT-PCR technique. While the use of one or more reference genes as internal controls is commonly accepted as the most appropriate normalization strategy, many qPCR-based published studies still contain data poorly normalized and reference genes arbitrarily chosen irrespective of the particular tissue and the specific experimental design. To date, no validated reference genes have been identified for endometrial cancer tissues. In this study, 10 normalization genes (GAPDH, B2M, ACTB, POLR2A, UBC, PPIA, HPRT1, GUSB, TBP, H3F3A) belonging to different functional and abundance classes in various tissues and used in different studies, were analyzed to determine their applicability. In total, 100 endometrioid endometrial cancer samples, which were carefully balanced according to their tumor grade, and 29 normal endometrial tissues were examined using SYBR Green Real-Time RT-PCR. The expression stability of candidate reference genes was determined and compared by means of geNorm and NormFinder softwares. Both algorithms were in agreement in identifying GAPDH, H3F3A, PPIA, and HPRT1 as the most stably expressed genes, only differing in their ranking order. Analysis performed on the expression levels of all candidate genes confirm HPRT1 and PPIA as the most stably expressed in the study groups regardless of sample type, to be used alone or better in combination. As the stable expression of HPRT1 and PPIA between normal and tumor endometrial samples fulfill the basic requirement of a reference gene to be used for normalization purposes, HPRT1 expression showed significant differences between samples from low-grade and high-grade tumors. In conclusion, our results recommend the use of PPIA as a single reference gene to be considered for improved reliability of normalization in gene expression studies involving endometrial tumor samples at different tumor degrees.     

A critique of widely used normalization software tools and an alternative method to identify reliable reference genes in red clover (Trifolium pratense L.)

Determination of appropriate reference genes is crucial to normalization of gene expression data and prevention of biased results in qRT-PCR studies. This study is the first attempt to systematically compare potential reference genes to detect the most constitutively expressed reference genes for accurate normalization in red clover tissues including leaves, stems and roots. To identify the best-suited reference gene(s) for normalization, several statistical algorithms such as geNorm, BestKeeper and NormFinder have been developed. All these algorithms are based on the key assumption that none of the investigated candidate reference genes show systematic variation in their expression profile across the samples being considered. However, this assumption is likely to be violated in practice. The authors therefore suggest a simple and novel stability index based on the analysis of variance model which is free from the assumption made by the algorithms. We assessed the expression stability of eight candidate reference genes including actin (ACT), glyceraldehyde-3-phosphate-dehydrogenase (GADPH), elongation factor-1alpha (EF-1α), translation initiation factor (EIF-4a), ubiquitin-conjugating enzyme E2 (UBC2), polyubiquitin (UBQ10), sand family protein (SAND) and yellow-leaf-specific protein 8 (YLS8). Our results indicated that UBC2 and UBQ10 ranked as the two most stably expressed genes in leaf tissue. UBC2 and YLS8 were defined as optimal control genes for stem tissue. EIF-4a and UBC2 were found to be the most stable reference gene for root tissue. GAPDH and SAND showed relatively low stability in expression study of red clover. When all tested tissues were considered, we observed that YLS8 and UBC2 showed remarkable stability in their expression level across tissues.     

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.     

Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species

Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses.     

Selection of housekeeping genes for qRT-PCR analysis in potato tubers under cold stress

Quantitative real-time polymerase chain reaction (qRT-PCR) is currently the most sensitive method used for quantitative gene expression studies. However, minimal variation in the amount of material and presence of inhibitors affecting enzyme efficiency can lead to significant quantification errors. Accurate data normalization is vital using reference genes as internal controls. Many so-called housekeeping genes or reference genes with assumed stable expression can exhibit either up- or downregulation depending on the developmental stage or other environmental conditions. We have evaluated six reference genes (actin, APRT, 18S rRNA, ef1α, β-tubulin and ribosomal protein L2) for qRT-PCR profiling experiments in potato tuber tissues of five varieties during cold storage at different temperatures and treatment periods. Genes were ranked according to their expression stability by BestKeeper, geNorm and NormFinder software tools in the same order. This means that any of them can be used for this purpose. The results indicated that ef1α and APRT were the most stably expressed genes in the potato tuber tissues under different cold storage regimes. We therefore recommend use of this pair of genes as internal controls for gene expression studies under the described conditions.     

Identification of suitable reference genes for gene expression studies of human serous ovarian cancer by real-time polymerase chain reaction

Quantitative real-time RT-PCR (RT-qPCR) has proven to be a valuable molecular technique in gene expression quantification. Target gene expression levels are usually normalized to a stably expressed reference gene simultaneously determined in the same sample. It is critical to select optimal reference genes to interpret data generated by RT-qPCR. However, no suitable reference genes have been identified in human ovarian cancer to date. In this study, 10 housekeeping genes, ACTB, ALAS1, GAPDH, GUSB, HPRT1, PBGD, PPIA, PUM1, RPL29, and TBP as well as 18S rRNA that were already used in various studies were analyzed to determine their applicability. Totally 20 serous ovarian cancer specimens and 20 normal ovarian epithelial tissue specimens were examined. All candidate reference genes showed significant differences in expression between malignant and nonmalignant groups except GUSB, PPIA, and TBP. The expression stability and suitability of the 11 genes were validated employing geNorm and NormFinder. GUSB, PPIA, and TBP were demonstrated as the most stable reference genes and thus could be used as reference genes for normalization in gene profiling studies of serous ovarian cancer, while the combination of two genes (GUSB and PPIA) or the all three genes should be recommended as a much more reliable normalization strategy.     

Stability of Expression of Reference Genes Among Different Lentil (Lens culinaris) Genotypes Subjected to Cold Stress, White Mold Disease, and Aphanomyces Root Rot

Precise quantification of differences in gene expression between plants requires the use of “reference” genes, which are stably expressed across different lines and treatments and serve as endogenous controls for normalizing gene expression data. The objectives of this study were to determine the expression stability of several reference genes across five different lentil varieties subjected to either cold stress, inoculation with Sclerotinia sclerotiorum, the causal agent of white mold disease, or inoculation with Aphanomyces euteiches, the causal agent of Aphanomyces root rot. Expression stability was examined in the stems and leaves of plants subjected to cold stress or inoculation with S. sclerotiorum and in the roots of plants inoculated with A. euteiches. Real-time PCR assays (SYBR Green) were designed for six different genes: translation initiation factor (TIF), 18S rRNA, actin, β-tubulin-2, β-tubulin-3, and glyceraldehyde 3-phosphate dehydrogenase. TIF, actin, and 18S rRNA tended to be the most stably expressed genes, with expression stability (M) values less than 0.5 during cold stress and inoculation with A. euteiches. Two reference genes were required to normalize data from plants exposed to cold stress or inoculated with A. euteiches. The reference genes exhibited the lowest expression stability in plants inoculated with S. sclerotiorum, for which five reference genes were required to normalize data. The reference genes reported in this study appear to have a promise for examining gene expression in lentil foliar and root tissues in response to diverse abiotic and biotic factors.     

Validation of Reliable Reference Genes for Real-Time PCR in Human Umbilical Vein Endothelial Cells on Substrates with Different Stiffness

Background

The mechanical properties of cellular microenvironments play important roles in regulating cellular functions. Studies of the molecular response of endothelial cells to alterations in substrate stiffness could shed new light on the development of cardiovascular disease. Quantitative real-time PCR is a current technique that is widely used in gene expression assessment, and its accuracy is highly dependent upon the selection of appropriate reference genes for gene expression normalization. This study aimed to evaluate and identify optimal reference genes for use in studies of the response of endothelial cells to alterations in substrate stiffness.

Methodology/Principal Findings

Four algorithms, GeNorm^PLUS, NormFinder, BestKeeper, and the Comparative ΔCt method, were employed to evaluate the expression of nine candidate genes. We observed that the stability of potential reference genes varied significantly in human umbilical vein endothelial cells on substrates with different stiffness. B2M, HPRT-1, and YWHAZ are suitable for normalization in this experimental setting. Meanwhile, we normalized the expression of YAP and CTGF using various reference genes and demonstrated that the relative quantification varied according to the reference genes.

Conclusion/Significance:

Consequently, our data show for the first time that B2M, HPRT-1, and YWHAZ are a set of stably expressed reference genes for accurate gene expression normalization in studies exploring the effect of subendothelial matrix stiffening on endothelial cell function. We furthermore caution against the use of GAPDH and ACTB for gene expression normalization in this experimental setting because of the low expression stability in this study.