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.     

Normalizing genes for real-time polymerase chain reaction in epithelial and nonepithelial cells of mouse small intestine

Gene expression studies in intestinal epithelial and stromal cells are a common tool for investigating the mechanisms by which the homeostasis of the small intestine is regulated under normal and pathological conditions. Quantitative real-time PCR (qPCR) is a sensitive and highly reproducible method of gene expression analysis, with expression levels quantified by normalization against reference genes in most cases. However, the lack of suitable reference genes for epithelial cells with different differentiation states and nonepithelial tissue cells has limited the application of qPCR in gene expression studies of small intestinal samples. In this study, 13 housekeeping genes, ACTB, B2M, GAPDH, GUSB, HPRT1, HMBS, HSP90AB1, RPL13A, RPS29, RPLP0,PPIA, TBP, and TUBA1, were analyzed to determine their applicability for isolated crypt cells, villus cells, deepithelialized mucosa, and whole mucosa of the mouse small intestine. Using geNorm and NormFinder software, GUSB and TBP were identified as the most stably expressed genes, whereas the expressions of the commonly used reference genes GAPDH, B2M, and ACTB, and ribosomal protein genes RPL13A, RPS29, and RPLP0 were relatively unstable. Thus, this study demonstrates that GUSB and TBP are the optimal reference genes for the normalization of gene expression in the mouse small intestine.     

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.     

Reference gene selection for real-time RT-PCR in regenerating mouse livers

The liver has an intrinsic ability to undergo active proliferation and recover functional liver mass in response to an injury response. This regenerative process involves a complex yet well orchestrated change in the gene expression profile. To produce accurate and reliable gene expression of target genes during various stages of liver regeneration, the determination of internal control housekeeping genes (HKGs) those are uniformly expressed is required. In the present study, the gene expression of 8 commonly used HKGs, including GAPDH, ACTB, HPRT1, GUSB, PPIA, TBP, TFRC, and RPL4, were studied using mouse livers that were quiescent and actively regenerating induced by partial hepatectomy. The amplification of the HKGs was statistically analyzed by two different mathematical algorithms, geNorm and NormFinder. Using this method, PPIA and TBP gene expression found to be relatively stable regardless of the stages of liver regeneration and would be ideal for normalization to target gene expression.     

Evaluation of reference genes for quantitative real-time PCR in the brain,pituitary, and gonads of songbirds

Quantitative real-time PCR (qPCR) is becoming a popular tool for the quantification of gene expression in the brain and endocrine tissues of songbirds. Accurate analysis of qPCR data relies on the selection of appropriate reference genes for normalization, yet few papers on songbirds contain evidence of reference gene validation. Here, we evaluated the expression of ten potential reference genes (18S, ACTB, GAPDH, HMBS, HPRT, PPIA, RPL4, RPL32, TFRC, and UBC) in brain, pituitary, ovary, and testis in two species of songbirds: zebra finch and white-throated sparrow. We used two algorithms, geNorm and NormFinder, to assess the stability of these reference genes in our samples. We found that the suitability of some of the most popular reference genes for target gene normalization in mammals, such as 18S, depended highly on tissue type. Thus, they are not the best choices for brain and gonad in these songbirds. In contrast, we identified alternative genes, such as HPRT, RPL4 and PPIA, that were highly stable in brain, pituitary, and gonad in these species. Our results suggest that the validation of reference genes in mammals does not necessarily extrapolate to other taxonomic groups. For researchers wishing to identify and evaluate suitable reference genes for qPCR in songbirds, our results should serve as a starting point and should help increase the power and utility of songbird models in behavioral neuroendocrinology.     

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.     

Selection of optimal reference genes for quantitative RT-PCR studies of boar spermatozoa cryopreservation

Reference genes can be used to normalize mRNA levels across different samples for the exact comparison of the mRNA expression level. It is important to select reference genes with high quality for the accurate interpretation of qRT-PCR data. Although several studies have attempted to validate reference genes in pigs, no validation studies have been performed on spermatozoa samples frozen with different cryoprotectants. In this study, 11 commonly used reference genes (ACTB, B2M, GAPDH, HPRT1, RPL4, SDHA, YWHAZ, PPIA, PGK1, S18, and BLM) were investigated in boar spermatozoa frozen with six different cryoprotectants using qRT-PCR. The expression stability of these reference genes in different samples was evaluated using geNorm (qbase^plus software), NormFinder, and BestKeeper. The geNorm results revealed that PGK1, ACTB, and RPL4 exhibit high expression stability in all of the samples, and the NormFinder results indicated that GAPDH is the most stable gene. Furthermore, the BestKeeper results indicated that the three most stable genes are PPIA, GAPDH, and RPL4 and that S18, B2M and BLM are the three least stable genes. There are a number of differences in the ranking order of the reference genes obtained using the different algorithms. In conclusion, GAPDH, RPL4, and PPIA were the three most stable genes in frozen boar spermatozoa, as determined based on the cycle threshold coefficient of variation (Ct CV%) and the comprehensive ranking order, and this finding is consistent with the BestKeeper results     

Evaluation of reference genes for real-time quantitative PCR studies in

ABSTRACT: BACKGROUND: The selection of stable and suitable reference genes for real-time quantitative PCR (RT-qPCR) is a crucial prerequisite for reliable gene expression analysis under different experimental conditions. The present study aimed to identify reference genes as internal controls for gene expression studies by RT-qPCR in azole-stimulated Candida glabrata. RESULTS: The expression stability of 16 reference genes under fluconazole stress was evaluated using fold change and standard deviation computations with the hkgFinder tool. Our data revealed that the mRNA expression levels of three ribosomal RNAs (RDN5.8, RDN18, and RDN25) remained stable in response to fluconazole, while PGK1, UBC7, and UBC13 mRNAs showed only approximately 2.9-, 3.0-, and 2.5-fold induction by azole, respectively. By contrast, mRNA levels of the other 10 reference genes (ACT1, EF1a, GAPDH, PPIA, RPL2A, RPL10, RPL13A, SDHA, TUB1, and UBC4) were dramatically increased in C. glabrata following antifungal treatment, exhibiting changes ranging from 4.5- to 32.7-fold. We also assessed the expression stability of these reference genes using the 2-[increment][increment]CT method and three other software packages. The stability rankings of the reference genes by geNorm and the 2-[increment][increment]CT method were identical to those by hkgFinder, whereas the stability rankings by BestKeeper and NormFinder were notably different. We then validated the suitability of six candidate reference genes (ACT1, PGK1, RDN5.8, RDN18, UBC7, and UBC13) as internal controls for ten target genes in this system using the comparative CT method. Our validation experiments passed for all six reference genes analyzed except RDN18, where the amplification efficiency of RDN18 was different from that of the ten target genes. Finally, we demonstrated that the relative quantification of target gene expression varied according to the endogenous control used, highlighting the importance of the choice of internal controls in such experiments. CONCLUSIONS: We recommend the use of RDN5.8, UBC13, and PGK1 alone or the combination of RDN5.8 plus UBC13 or PGK1 as reference genes for RT-qPCR analysis of gene expression in C. glabrata following azole treatment. In contrast, we show that ACT1 and other commonly used reference genes (GAPDH, PPIA, RPL13A, TUB1, etc.) were not validated as good internal controls in the current model.     

Identifying suitable reference genes for developing and injured mouse CNS tissues

Accurate quantification of gene expression is fundamental for understanding the molecular, genetic and functional bases of tissue development and diseases. Quantitative real‐time PCR (qPCR) is now the most widely used method of quantifying gene expression due to its simplicity, specificity, sensitivity, and wide quantification range. The use of appropriate reference genes to ensure accurate normalization is crucial for the correct quantification of gene expression from the early development, maturation, aging to injury processes in the central nervous system (CNS). In this study, we have determined the expression profiles of 12 candidate housekeeping genes (ACTB, CYC1, HMBS, GAPDH, HPRT1, RPL13A, YWHAZ, PPIA, RPLP0, TFRC, GUS, and 18S rRNA) in developing mouse brain and spinal cord. Throughout development, there was a significant degree of fluctuations in their expression levels, indicating the importance and complexity of finding appropriate reference genes. Three software including BestKeeper, geNorm and NormFinder were used to evaluate the stability of potential reference genes. GUS was the most stable gene and GUS/YWHAZ were the most stable reference gene pair across different developmental stages in different CNS regions, whereas HPRT1 and GAPDH were the most variable genes and thus inappropriate to use as reference genes. Therefore, our results identified GUS and YWHAZ as the best combination of two reference genes for expression data normalization in CNS developmental studies. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 39–50, 2018     

Selection of reference genes for normalization of real-time PCR data in minipig heart failure model and evaluation of TNF-α mRNA expression

Real-time PCR is the benchmark method for measuring mRNA expression levels, but the accuracy and reproducibility of its data greatly depend on appropriate normalization strategies. Though the minipig model is largely used to study cardiovascular disease, no specific reference genes have been identified in porcine myocardium. The aim of the study was to identify and validate reference gene to be used in RT-PCR studies of failing (HF) and non-failing pig hearts. Eight candidate reference genes (GAPDH, ACTB, B2M, TBP, HPRT-1, PPIA, TOP2B, YWHAZ) were selected to compare cardiac tissue of normal (n=4) and HF (n=5) minipigs. The most stable genes resulted: HPRT-1, TBP, PPIA (right and left atrium); PPIA, GAPDH, ACTB (right ventricle); HPRT-1, TBP, GAPDH (left ventricle). The normalization strategy was tested analyzing mRNA expression of TNF-α, which is known to be up-regulated in HF and whose variations resulted more significant when normalized with the appropriately selected reference genes. The findings obtained in this study underline the importance to provide a set of reference genes to normalize mRNA expression in HF and control minipigs. The use of unvalidated reference genes can generate biased results because also their expression could be altered by the experimental conditions.     

Effects of prototypical drug-metabolizing enzyme inducers on mRNA expression of housekeeping genes in primary cultures of human and rat hepatocytes

Quantitative real-time RT-PCR was used to investigate the effects of prototypical drug-metabolizing enzyme inducers rifampicin (Rif), dexamethasone (Dex), and omeprazole (Ome) on mRNA expression levels of the housekeeping genes beta-actin (ACTB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta-glucuronidase (GUSB), hypoxanthine phosphoribosyltransferase 1 (HPRT1), peptidylprolylisomerase A (PPIA), TATA box binding protein (TBP), and transferrin receptor (TFRC) in primary cultures of cryopreserved human and rat hepatocytes. The mRNA levels of ACTB, GAPDH, GUSB, PPIA, TBP, and TFRC relative to HPRT1 in human hepatocytes were constant at all concentrations of inducers. However, the mRNA level of GAPDH relative to HPRT1 in rat hepatocytes was markedly increased by Rif. The mRNA levels of GAPDH, GUSB, PPIA, TBP, and TFRC relative to HPRT1 in rat hepatocytes were significantly increased by Dex. ACTB and HPRT1 are suitable internal controls for evaluating mRNA expression levels in primary cultures of human and rat hepatocytes after Rif, Dex, or Ome exposure.     

山羊不同组织器官的内参基因筛选

本研究通过比较9个内参基因在山羊不同组织中的表达水平进而确定最适合研究山羊组织表达的内参基因。本试验以简州大耳羊为试验材料,利用实时荧光定量PCR技术分析9个内参基因(GAPDH,PPIA,18S rRNA,PPIB,UXT,RPLP0,ACTB,EIF3K和TBP)在心脏、肝脏、脾脏、肺脏、肾脏、大肠、瘤胃、背最长肌和皮下脂肪等组织中的表达差异情况,并利用geNorm、NormFinder和BestKeeper等程序分析了它们的表达稳定性。geNorm和NormFinder程序一致显示TBP表达最稳定,其次是UXT和RPLP0;BestKeeper分析显示18S rRNA表达最为稳定,其次为TBP和ACTB;3个程序一致认为GAPDH表达稳定性最差。综合3个程序分析得出TBP最适合作为山羊组织中的内参基因,其次为UXT和RPLP0,GAPDH表达稳定性最差,不适合作为山羊组织内参,这为后续研究其他目的基因在山羊组织器官中的表达模式提供数据保障。     

Novel reference gene RPN1 for normalization of quantitative data in lung and kidney cancer

Quantitative methods of gene expression analysis in tumors require accurate data normalization, which allows comparison of different mRNA/cDNA samples with unknown concentration. For this purpose reference genes with stable expression level (such as GAPDH, ACTB, HPRT1, TBP) are used. The choice of appropriate reference genes is still actual because well-known reference genes are not suitable for certain cancer types frequently and their unreasonable use without additional tests lead to wrong conclusions. We have developed the bioinformatic approach and selected a new potential reference gene RPN1 for lung and kidney tumors. This gene is located at the long arm of chromosome 3. Our method includes mining of the dbEST and Oncomine databases and functional analysis of genes. The RPN1 was selected from 1500 candidate housekeeping genes. Using comparative genomic hybridization with NotI-microarrays we found no methylation, deletions and/or amplifications at the RPN1-containing locus in 56 non-small cell lung and 42 clear cell renal cancer samples. Using RT-qPCR we showed low variability of RPN1 mRNA level comparable to those of reference genes GAPDH and GUSB in lung and kidney cancer. The mRNA levels of two target genes coding hyalouronidases--HYAL1 and HYAL2--were estimated and normalized relative to pair RPN1--GAPDH genes for lung cancer and RPN1--GUSB for kidney cancer. These combinations were shown to be optimal for obtaining accurate and reproducible data. All obtained results allow us to suggest RPN1 as novel reference gene for quantitative data normalization in gene expression studies for lung and kidney cancers.     

Reference gene selection for transcriptional profiling by RT-qPCR in the 28-spotted larger potato ladybird

Henosepilachna vigintioctomaculata is one of the most serious defoliates attacking potatoes. However, studies on functional genes have greatly been limited due to the insufficiency of effective and stable endogenous references to normalize RT-qPCR data. In this report, nine housekeeping genes (RPL4, RPL6, RPL13, RPL32, RPS18, ACT, EF1α, GAPDH and α-TUB) involved in different biological processes were selected. Their expression levels under diverse experimental conditions including developmental stages, tissues, temperatures and host plants were determined using RT-qPCR technology. The tested candidate genes were comprehensively ranked based on five alternative stability analysis methods (Ct value, geNorm, NormFinder, BestKeeper and ReFinder). The results revealed that the optimal internal reference genes varied under different experimental conditions. Any gene pair among the five candidates (RPL4, RPL13, RPL32, RPS18 and EF1α) was a suitable reference gene set under different temperatures and on different host plants. A combination of RPL6 and RPL13 was recommended as the best reference gene set across different developmental stages. A pair of RPS18 and EF1α was ranked as the optimal reference gene combination within different tissues. The most suitable reference genes were RPS18 and RPL13 under four different experimental conditions. Our findings not only establish an accurate and reliable normalization of RT-qPCR data, but also lay a solid foundation for further functional gene researches in H. vigintioctomaculata.