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     

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.     

Determination and Validation of Reference Gene Stability for qPCR Analysis in Polysaccharide Hydrogel-Based 3D Chondrocytes and Mesenchymal Stem Cell Cultural Models

Gene expression study is widely used to obtain information of the cell activities and phenotypes. To quantify gene expression, measurement of the mRNA copy number is commonly done by quantitative RT-PCR (RT-qPCR). However, proper reference gene is needed for different tissues to normalize the expression level of different genes accurately. In this study, reference gene determination was done for three-dimensional (3D) artificial tissue constructs in hydrogel. Porcine synovium-derived mesenchymal stem cells (SMSCs) and rabbit chondrocytes were cultured in both alginate and agarose hydrogels to set up four different 3D culture systems to form the artificial tissue constructs. The gene expression levels of candidate genes were determined by RT-qPCR and then analyzed by geNorm, Bestkeeper, and Normfinder. For porcine SMSCs, PPIA, and TBP were selected for tissue in alginate scaffold whereas HPRT and TBP were selected for the agarose scaffold system. On the other hand, HPRT, PPIA, and RPL18 were the stable reference genes for rabbit chondrocytes in alginate scaffold while TBP, RPL5, and RPL18 were selected for rabbit chondrocytes in agarose scaffold. This study has further indicated that suitable reference genes are different for each tissue and study purpose. The reference genes are expressed in different stability when a scaffold of different material is used.     

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.     

Reference gene selection for quantitative real-time PCR normalization in tomato subjected to nitrogen, cold, and light stress

We examined eight putative consistently expressed genes—actin (ACT), β-tubulin, elongation factor 1α (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), ribosomal protein L2 (RPL2), ubiquitin (UBI), and a catalytic subunit of protein phosphatase 2A (PP2Acs)—for their potential as references for the normalization of gene expression in tomato leaves. Expression stability of candidate reference genes was tested during growth conditions of nitrogen (N) starvation, low temperature, and suboptimal light. The geNorm algorithm, using reciprocal cross-validation among a larger group of candidate references, was applied for this purpose. The widely used reference genes GAPDH and PGK were top ranked during light stress but poorly ranked during N and cold stress. In contrast, EF1 was top ranked during N and cold stress but poorly ranked during light stress. The novel references RPL2 and PP2Acs, as well as the traditional references ACT and UBI, appeared to be stably expressed when looking at the data set as a whole. No gene was identified that exhibited such a constant level of expression as to outperform the other candidates under all experimental conditions. Thus, the results highlight the need for normalizing gene expression in tomato using the geometric average of multiple carefully selected reference genes.     

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.     

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.     

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.     

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。     

Selection of reference genes for normalization of qRT-PCR analysis of differentially expressed genes in soybean exposed to cadmium

Accurate normalization of gene expression with qRT-PCR depends on the use of appropriate reference genes (RGs) for the species under a given set of experimental conditions. Multiple RGs for gene expression analysis of soybean exposed to heavy metal stress treatment have not been reported in the literature. In this study, we evaluated the expression stability of ten candidate RGs in leaves, roots and stems of two soybean cultivars exposed to cadmium (Cd). Based on the geNorm and NormFinder analysis, ACT3, PP2A, ELF1B and F-box were the most stable RGs in these gene expression studies. In contrast, G6PD, UBC2, TUB, and ELF1A were the most variable ones and should not be used as RGs in these experimental conditions.     

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.     

冬虫夏草菌实时荧光定量PCR内参基因的筛选

以冬虫夏草单子囊孢子分离得到的菌株TZ8-1的3种菌丝形态为实验材料,提取RNA,经反转录获取cDNA,选择了11个持家基因为候选内参基因（18S rRNA、APRTase、β-TUB、RPL2、EF1-α、PGI、PGM、H⁺-ATPase、ACT1、UBQ和GAPDH）,根据该菌基因组注释结果来设计引物,采用实时荧光定量PCR（qRT-PCR）技术进行定量扩增,利用geNorm、NormFinder和BestKeeper算法程序进行表达稳定性评估,并用RefFinder对评估结果进行综合排比,最终筛选得到了最适内参基因。结果表明,所选取的11个候选内参基因均可作为冬虫夏草菌菌丝体时期的内参基因,稳定性最好的3个内参基因分别是UBQ、PGE和ACT1,稳定性较差的3个内参基因分别是GAPDH、RPL2和β-TUB。     

光裸星虫(Sipunculus nudus)不同发育时期卵细胞内参基因的筛选

内参基因的选择对功能基因表达量的归一化处理尤为重要。为了筛选出光裸星虫不同发育时期卵子的最适内参基因,利用qRT-PCR测定了甘油醛-3-磷酸脱氢酶(GAPDH)、肽基脯氨酰顺反异构酶A(PPIA)、60S核糖体蛋白L10(60S-L10)、铁蛋白(Ferritin)、β-肌动蛋白(β-actin)、泛素C(UBC)、真核生物翻译起始因子(eIF)、NADH脱氢酶(NDH)、28S核糖体RNA(28S)、TATA盒结合蛋白(TBP)、18S核糖体RNA(18S)和琥珀酸脱氢酶A亚基(SDHA)共12个候选内参基因的表达水平,并通过4个程序(geNorm,NormFinder,BestKeeper以及RefFinder)综合分析了各基因的表达稳定性。结果显示:(1)12个候选内参基因均能获得特异性扩增产物,但表达情况各异;(2)对候选内参基因进行综合打分,得到候选内参基因稳定性排名为18S>GAPDH>28S>β-actin>UBC>e IF>NDH|TBP>PPIA|Ferritin>60S-L10>SDHA。18S和GAPDH稳定性较好,可作为不同发育时期卵细胞基因表达研究的单内参基因,或最优组合内参基因。