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 housekeeping genes as references for quantitative real-time PCR analysis of European eel,Anguilla anguilla

Eels are important aquaculture species for which an increasing number of reference genes are being identified and applied. In this study, five housekeeping genes [RPL7 (ribosomal protein L7), 18 S (18 S ribosomal RNA), EF1A (elongation factor 1α), ACTB (β-actin) and GAPDH (glyceraldehyde-3-phosphate dehydrogenase)] were chosen to evaluate their reliability as reference genes for quantitative real-time PCR (qPCR) for the study of Anguilla anguilla. The expression of the selected genes in different eel tissues was determined using qPCR at different growth stages or upon challenge by Anguillid herpesvirus (AngHV), and the expression levels of these genes were then compared and evaluated using the geNorm and NormFinder algorithms. Then, RefFinder was used to comprehensively rank the examined housekeeping genes. Interestingly, the expression of the evaluated housekeeping genes exhibited tissue-dependent and treatment-dependent variations. In different growth periods A. anguilla tissues, the most stable genes were the following: ACTB in mucus; 18 S in skin and kidney; RPL7 in muscle, gill, intestine and brain; EF1A in heart and liver; and GAPDH in spleen. In contrast, in AngHV-challenged A. anguilla tissues, the most stable genes were the following: 18 S in mucus; RPL7 in skin, gill, heart, spleen, kidney and intestine; EF1A in muscle and liver; and ACTB in brain. Further comparison analysis indicated that the expression of RPL7 and EF1A was stable in multiple A. anguilla tissues in different growth periods and in eels challenged by AngHV. Nonetheless, the expression level of GAPDH in eel tissues was lower, and it was unstable in several tissues. These results indicated that the selection of reference genes for qPCR analysis in A. anguilla should be made in accordance with experimental parameters, and both RPL7 and EF1A could be used as reference genes for qPCR study of A. anguilla at different growth stages or upon challenge by AngHV. The reference genes identified in this study could improve the accuracy of qPCR data and facilitate further studies aimed at understanding the biology of eels.     

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.     

Verification of suitable and reliable reference genes for quantitative real-time PCR during adipogenic differentiation in porcine intramuscular stromal-vascular cells

Intramuscular fat (IMF) is an important trait influencing meat quality, and intramuscular stromal-vascular cell (MSVC) differentiation is a key factor affecting IMF deposition. Quantitative real-time PCR (qPCR) is often used to screen the differentially expressed genes during differentiation of MSVCs, where proper reference genes are essential. In this study, we assessed 31 of previously reported reference genes for their expression suitability in porcine MSVCs derived form longissimus dorsi with qPCR. The expression stability of these genes was evaluated using NormFinder, geNorm and BestKeeper algorithms. NormFinder and geNorm uncovered ACTB, ALDOA and RPS18 as the most three stable genes. BestKeeper identified RPL13A, SSU72 and DAK as the most three stable genes. GAPDH was found to be the least stable gene by all of the three software packages, indicating it is not an appropriate reference gene in qPCR assay. These results might be helpful for further studies in pigs that explore the molecular mechanism underlying IMF deposition.     

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.     

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.     

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.     

基因表达转录分析中内参基因的选择

目前基因表达的转录分析多采用单一看家基因作为内参来校正目标基因的表达量.实验中以人肝癌BEL-7402细胞为研究对象,应用实时荧光定量PCR技术,观察了新型三肽化合物酪丝缬肽作用后RPL13A、UBC、EIF4A、B2M、GAPDH和ACTB共6个看家基因mRNA水平的表达情况.经过geNorm程序统计学分析处理,结果表明,这6个看家基因的表达存在差异,确定了RPL13A、UBC2个看家基因用于校正目标基因的表达量.基因表达转录分析中内参基因选择的必要性在实验中得以证明,更重要的是为各种实验因素影响下(尤其是新物质作用下)内参基因的选择介绍和提供了一种行之有效的方法.     

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.     

Bt毒素诱导下小菜蛾实时定量PCR 内参基因的筛选

【目的】筛选出Bt毒素诱导后的小菜蛾Plutella xylostella (L.)的实时定量PCR最适内参基因。【方法】选取核糖体18S rRNA (18S rRNA)、 肌动蛋白（ACTB）、 延伸因子（EF1）、3-磷酸甘油醛脱氢酶（GAPDH）、 核糖体蛋白L32 (RPL32)、 核糖体蛋白S13 （RPS13）、 核糖体蛋白S20 （RPS20）和β-微管蛋白(TUB)基因作为候选内参基因, 以geNorm、 Normfinder和BestKeeper软件分析这8个基因在Bt毒素诱导后的小菜蛾不同品系中肠组织中的表达稳定性。并应用筛选出来的内参基因分析小菜蛾氨肽酶2（aminopeptidase N2, APN2）基因的表达水平。【结果】geNorm软件以RPS13和EF1为最稳定内参基因, NormFinder和BestKeeper软件均以RPS13和RPL32为最稳定基因。使用3种不同内参基因分析Bt毒素诱导后的小菜蛾Bt抗性和敏感品系中ANP2表达水平时, 新的内参基因EF1和传统内参基因RPL32表现了良好的稳定性, 二者作为标准化因子, ANP2表达量结果基本一致, 而使用18S rRNA作为内参基因, 却导致部分表达量分析结果有所误差。【结论】筛选出PRS13,RPL32和EF1可以作为小菜蛾某些试验条件下的内参基因, 对小菜蛾基因表达研究奠定了一定基础, 也对其他昆虫内参基因的筛选具有参考价值。     

翘嘴鳜per1 mRNA表达量分析中采用的内参基因稳定性比较

为筛选生物钟核心基因per1表达定量中的相对稳定性最好的内参基因,本研究取翘嘴鳜成鱼心脏、肝脏、肾脏、脑、红肌、白肌、肠、眼和脾等九个组织为研究对象,选取GAPDH、18S rRNA、β-actin、rps29、RPL13a、B2M和EF1a为内参基因,采用实时荧光定量PCR(qRT-PCR)对per1基因mRNA表达水平进行检测分析。研究结果表明18S rRNA和GAPDH的平均稳定值M最低,相对表达量最稳定。以18S rRNA和GAPDH为内参基因时分析发现per1基因表达量在肝脏中最高。本研究为在鱼类per1 mRNA表达检测过程中选用稳定的内参基因提供了实验和理论参考。     

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