Top PDF Screening suitable reference genes for normalization in reverse transcription quantitative real-time PCR analysis in melon.

Melon (Cucumis melo. L) is not only an economically important cucurbitaceous crop but also an attractive model for studying many biological characteristics. Screening appropriate reference genes is essential to reverse transcription quantitative real-time PCR (RT-qPCR), which is key to many studies involving gene expression analysis. In this study, 14 candidate reference genes were selected, and the variations in their expression in roots and leaves of plants subjected to biotic stress, abiotic stress, and plant growth regulator treatment were assessed by RT-qPCR. The stability of the expression of the selected genes was determined and ranked using geNorm and NormFinder. geNorm identified the two most stable genes for each set of conditions: CmADP and CmUBIep across all samples, CmUBIep and CmRPL in roots, CmRAN and CmACT in leaves, CmADP and CmRPL under abiotic stress conditions, CmTUA and CmACT under biotic stress conditions, and CmRAN and CmACT under plant growth regulator treatments. NormFinder determined CmRPL to be the best reference gene in roots and under biotic stress conditions and CmADP under the other experimental conditions. CmUBC2 and CmPP2A were not found to be suitable under many experimental conditions. The catalase family genes CmCAT1, CmCAT2, and CmCAT3 were identified in melon genome and used as target genes to validate the reliability of identified reference genes. The catalase family genes showed the most upregulation 3 days after inoculation with Fusarium wilt in roots, after which they were downregulated. Their levels of expression were significantly overestimated when the unsuitable reference gene was used for normalization. These results not only provide guidelines for the selection of reference genes for gene expression analyses in melons but may also provide valuable information for studying the functions of catalase family genes in stress responses.

The anterior cruciate ligament (ACL) is one of the most frequently injured structures during high-impact sporting activities. Gene expression analysis may be a useful tool for under- standing ACL tears and healing failure. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) has emerged as an effective method for such studies. However, this technique requires the use of suitable reference genes for data normalization. Here, we evaluated the suitability of six reference genes (18S, ACTB, B2M, GAPDH, HPRT1, and TBP) by using ACL samples of 39 individuals with ACL tears (20 with isolated ACL tears and 19 with ACL tear and combined meniscal injury) and of 13 controls. The stability of the candidate reference genes was determined by using the NormFinder, geNorm, BestKeeper DataAssist, and RefFinder software packages and the comparative ΔCt method. ACTB was the best single reference gene and ACTB+TBP was the best gene pair. The GenEx soft- ware showed that the accumulated standard deviation is reduced when a larger number of reference genes is used for gene expression normalization. However, the use of a single reference gene may not be suitable. To identify the optimal combination of reference genes, we evaluated the expression of FN1 and PLOD1. We observed that at least 3 reference genes should be used. ACTB+HPRT1+18S is the best trio for the analyses involving iso- lated ACL tears and controls. Conversely, ACTB+TBP+18S is the best trio for the analyses involving (1) injured ACL tears and controls, and (2) ACL tears of patients with meniscal tears and controls. Therefore, if the gene expression study aims to compare non-injured ACL, isolated ACL tears and ACL tears from patients with meniscal tear as three indepen- dent groups ACTB+TBP+18S+HPRT1 should be used. In conclusion, 3 or more genes should be used as reference genes for analysis of ACL samples of individuals with and without ACL tears.

Quantitative real-time reverse transcription polymerase chain reaction (qPCR) is an efficient, specific, and reproducible method for quantifying transcript expression levels, and is widely used to analyze mRNA in different organisms [1], developmental stages [2,3] and responses to abiotic and biotic stress [4–7]. However, the accuracy of qPCR is influenced by a number of variables, such as RNA stability, quantity, purity, enzymatic efficiency in cDNA synthesis and PCR amplification [8]. Thus, to avoid bias, a normalization step is an essential pre-requisite. The most accepted approach for normalization is to include one or a small number of reference genes (internal control genes), whose expression is presumed stable in control and experimental conditions [9,10].

Methods for the quantification of accurate gene expres- sion have an increasingly important role in studies aiming for the reliable examination of expression profiles gener- ated by high-throughput approaches. Real-time reverse transcription quantitative PCR (qRT-PCR) has emerged as one of the most powerful tools for this purpose. Given the extreme sensitivity of qRT-PCR, a careful and stringent selection of a proper constitutively expressed control gene is required to account for differences in the amount and quality of starting RNA and in cDNA synthesis efficiency. Adequate normalizations presume the use of an internal control, often referred to as a housekeeping or reference gene, whose expression levels should not significantly vary among tissues and experimental situations analyzed [1,2]. Genes most commonly applied as references in qRT-PCR studies include: beta actin (ACTB), glyceral- deyde-3-phosphate dehydrogenase (GAPDH), beta glu- curonidase (GUSB), hypoxanthine guanine phosphoribosyl transferase (HPRT1) and ribosome small subunit (18S) ribosomal RNA [1-3]. However, several reports have mentioned these classical housekeeping genes as showing variable expression levels in different experimental conditions [3-9]. Furthermore, the same gene revealed as almost invariant for certain tissues or cell types or could present highly variable expression levels in other tissues or experimental conditions [2,9,10]. Thus, it is clear that suitable control genes are extremely specific for particular sample sets and experimental models, being a crucial component in assessing confident gene expres- sion patterns. It has been strongly suggested that more than one stable expressed reference gene should be used to avoid misinterpretation of gene expression data [6,7,11-13].

ABSTRACT - Real time reverse transcription polymerase chain reaction (RT-qPCR) is an important technique to analyze differences in gene expression due to its sensitivity, accuracy, and specificity. However, before analyzing the expression of the target gene, it is necessary to identify and evaluate the stability of candidate reference genes for the proper normalization. This study aimed at evaluating the stability of candidate reference genes in order to identify the most appropriate genes for the normalization of the transcription in rice and red rice in competition under different nitrogen levels, as well as to demonstrate the effectiveness of the reference gene selected for the expression of the cytosolic ascorbate peroxidase (OsAPX2). Eleven candidate reference genes were assessed using the RefFinder which integrates the four leading software: geNorm, NormFinder, Bestkeeper, and the comparative delta-Ct method in addition to the analysis of variance to identify genes with lower standard deviation and coefficient of variation values. Eight out of the eleven genes have shown the desired effectiveness and, among them, the gene UBC-E2 has the highest stability according to RefFinder and the analysis of variance. The expression of the gene OsAPX2 has proven to be effective in validating the candidate reference gene. This study is the first survey on the stability of candidate reference genes in rice and red rice in competition, providing information to obtain more accurate results in RT-qPCR.

Tubulin is one of several members of a small family of globular proteins, and is the major building block of microtubules in almost all eukaryotic cells, exhibited the most stable expression in the different conditions. Moreover, Tubulin had also been proved to be the normalized reference protein for Western blotting in Drosophila [25–27]. In this study, it was found to be the most stably expressed gene in the different treatment. TBP composed of transcription factor IID with TBP-associated factors, and is frequently used as a reference gene. Bansal et al recommend the TBP as a suitable HKG for efficient normalization among treatments, tissues, and developmental stages of A. glycines [28]. AK is the major phosphagen kinase in invertebrate groups, which has rarely been used as a reference gene in previous studies. In Bombus terrestris, AK was identified the most stable gene in the labial gland and fat body [8], and we found which the most stable gene was in different tissue (Figure S2). RPL18 is located in the cytoplasm, which belongs to the L18E family of ribosomal proteins. Mamidala et al found that it is the most stable gene

One of the methodologies used to determine expression levels by RT-qPCR compares the gene of interest with reference genes, whose expression does not change under different experimental conditions. Statistical analysis methods have been developed to identify the best reference genes for a certain organism or experimental condition (Vandesompele et al., 2002; Pfaffl et al., 2004). The use of reference genes without prior verification of their expression stability can lead to an inaccurate interpretation of the data and generate incorrect results. A reference gene should have stable expression in different organs, developmental stages, and environments. According to previous works on the best reference genes for transcription normalization in plants, the most reliable are those constitutively expressed and involved in basic cellular processes, such as protein and sugar metabolism and maintenance of cell structure (Cruz et al., 2009).

Gene expression analysis plays a major role in understanding of the complex regulatory net- works and identification of genes relevant to new biological processes [3]. Among several tech- niques available for transcript level measurement, real time quantitative reverse transcription PCR (qRT-PCR) is widely used due to its specificity, sensitivity and dynamic range [4]. Valida- tion of high-throughput technologies such as RNA-sequencing (RNA-seq) through qRT-PCR further implies the robustness of this technique [5]. However, several factors including the quantity and integrity of the extracted RNA, the efficiencies of cDNA synthesis and the prod- ucts of polymerase chain reaction (PCR) can significantly generate non-specific variations, which should be corrected by using proper controls [6]. Applying the internal control gene known as reference gene or housekeeping gene is the most common way to normalize the tran- script level and reduce the inherent experimental errors [6–8]. Therefore, the normalization is a crucial step before performing any qRT-PCR analysis. Ideally, an appropriate reference gene is expected to be stable in terms of expression level across various conditions such as develop- mental stages, organ types, and experimental conditions [9]. The most frequently used refer- ence genes are the 18S ribosomal RNA (18SrRNA), glyceraldehyde-3-phosphate

Quantitative real-time PCR (qRT-PCR) is now globally used for accurate analysis of tran- scripts levels in plants. For reliable quantification of transcripts, identification of the best reference genes is a prerequisite in qRT-PCR analysis. Recently, Withania somnifera has at- tracted lot of attention due to its immense therapeutic potential. At present, biotechnological intervention for the improvement of this plant is being seriously pursued. In this background, it is important to have comprehensive studies on finding suitable reference genes for this high valued medicinal plant. In the present study, 11 candidate genes were evaluated for their ex- pression stability under biotic (fungal disease), abiotic (wounding, salt, drought, heat and cold) stresses, in different plant tissues and in response to various plant growth regulators (methyl jasmonate, salicylic acid, abscisic acid). The data as analyzed by various software packages (geNorm, NormFinder, Bestkeeper and ΔCt method) suggested that cyclophilin (CYP) is a most stable gene under wounding, heat, methyl jasmonate, different tissues and all stress conditions. T-SAND was found to be a best reference gene for salt and salicylic acid (SA) treated samples, while 26S ribosomal RNA (26S), ubiquitin (UBQ) and beta-tubulin (TUB) were the most stably expressed genes under drought, biotic and cold treatment respectively. For abscisic acid (ABA) treated samples 18S-rRNA was found to stably expressed gene. Fi- nally, the relative expression level of the three genes involved in the withanolide biosynthetic pathway was detected to validate the selection of reliable reference genes. The present work will significantly contribute to gene analysis studies in W. somnifera and facilitate in improving the quality of gene expression data in this plant as well as and other related plant species.

The increasingly used real time quantitative reverse transcription-PCR (qRT-PCR) method for gene expression analysis requires one or several reference gene(s) acting as normalization factor(s). In order to facilitate gene expression studies in sugarcane (Saccharum officinarum), a non-model plant with limited genome information, the stability of 13 candidate reference genes was evaluated. The geNorm, NormFinder and deltaCt methods were used for selecting stably expressed internal controls across different tissues and under various experimental treatments. These results revealed that, among these 13 candidate reference genes, GAPDH, eEF-1a and eIF-4a were the most stable and suitable for use as normalization factors across all various experimental samples. In addition, APRT could be a candidate for examining the relationship between gene copy number and transcript levels in sugarcane tissue samples. According to the results evaluated by geNorm, combining CUL and eEF-1a in hormone treatment experiments; CAC and CUL in abiotic stress tests; GAPDH, eEF-1a and CUL in all treatment samples plus CAC, CUL, APRT and TIPS-41 in cultivar tissues as groups for normalization would lead to more accurate and reliable expression quantification in sugarcane. This is the first systematic validation of reference genes for quantification of transcript expression profiles in sugarcane. This study should provide useful information for selecting reference genes for more accurate quantification of gene expression in sugarcane and other plant species.

Probably inherited from northern blot analysis, ACTB, HPRT1 and GAPDH have been widely used as reference genes for qPCR analysis, despite the enormous body of evidence indicating that their transcription levels are not constant across many develop- mental stages and experimental conditions [9,10]. To overcome this limitation, several tools have been made available to assess the stability of expression of candidate reference genes for qPCR gene expression analysis [5,6,11]. Most of these studies have focused on a specific tissue type [9,12–14]. The disparity of valid reference genes obtained in each study stresses the importance of selecting suitable controls for each experiment. In pigs, there has been a valuable contribution from a number of authors describing suitable reference gene in time-course study of early embryonic development [12], with-in tissue in seven tissue types [13], and across-tissues [9] from a panel of 17 different tissues. A recent study has focused on sow endometrium at 12 days of pregnancy [14] and reference sequences for small-non coding RNA studies (such as miRNA) have also recently been evaluated in the uterus of 20 days-pregnant sows [15]. In contrast, there are no published reports describing qPCR reference genes for pig ovary studies. Moreover, the stability of reference genes across different reproductive stages has not been evaluated in pig in uterus nor in ovary.

internal control for qPCR analysis, it seems to be a good internal control only for lowly expressed genes [31]. Some studies showed GAPDH was unsuitable as an internal control due to its significant variation of expression levels between different individuals during pregnancy [32], with developmental stages [33,34] and during the cell cycle of human cells [35], which agrees with our result when mRNA from different individuals and developmental stages were examined. For the case of 18S rRNA, this ribosomal subunit gene was previously used as internal control in the gene expression studies of rice with environmental stresses [36] and the fathead minnow fish with environmental estrogens exposure [37]. How- ever, there are two main drawbacks that 18S rRNA cannot be used for normalization: (1) rRNA can be lost during mRNA purification, and (2) it is expressed at much greater levels than target mRNAs [38]. Perhaps, the biological functions of proteins encoded by GAPDH and 18S rRNA suggest that their transcript levels are significantly regulated by various experimental settings and variable in different tissues and thus unstable [39,40].

standard curves for target and reference exons were prepared over serially diluted genomic DNA sam- ples. he mean Ct values corresponding to each concentration were plotted against the log input of DNA. Trend line slopes were within an accept- able range (-0.1< slope< 0.1), the PCR eiciencies of the target and the reference exons were approxi- mately equal, which was a prerequisite for the ac- curate copy number assessment (Fig. 1). To observe the presence of any possible primer dimer or non- speciically ampliied product formation, which

ing the PrimeScript RT-PCR kit (TaKaRa Bio Inc., Japan) according to manufacturer recommendations. The primers for the human PTPN12 gene were designed with Primer Premier 5.0 (Premier Biosoft, USA) and the sequences were sense: 5’-AAATACTGCAGCCACCGGAAC-3’, antisense: 5’-GCAACACTGGCTTTGGATGG-3’; the amplicon size was 126 bp. GAPDH was used as the internal control with the spe- cific primers - sense: 5’-TCATGGGTGTGAACCATGAGAA-3’, antisense: 5’-GGCATGGACTGTGGTCATGAG-3’; the amplicon size was 150 bp. The primers cited above were synthesized by Shanghai Sangon Biological Engineering Technology & Services Co. Ltd. (China). The PCR products were analyzed by 1% agarose gel electrophoresis.

including dehydration, salt and cold stresses, which are often encountered by soybean plants [1,3]. Gene expression in response to abiotic stress has been known to be regulated in ABA- dependent and/or ABA-independent manner [39,51–53]; thus, we also included ABA treatment into our study. A qRT-PCR assay was designed to measure the expression stability between control and stress- or ABA-treated samples of thirteen candidate reference genes obtained from published literature related to qRT-PCR expression profiling in soybean (Table 1, Dataset S1, Figure S1). These candidate genes were chosen based on their functional homology to genes that appear to demonstrate high expression stability in other plant systems [44,45,54]. Additionally, candidate genes were chosen which have been previously shown to demonstrate high stability in soybean under biotic stress conditions [46]. The 18S ribosomal RNA gene was initially included among candidate reference genes for testing but was later excluded due to its extremely high abundance. Template cDNA for the samples analyzed with 18S primers had to be diluted at least 1000-fold relative to all other candidate genes to avoid the signal saturation obtained at low CT values. This dilution introduces a random element of variability which can potentially alter the apparent expression levels of target genes normalized with 18S.

The basic model used for residual data was simple linear mul- tivariate regression. However, for the 10 cases with largest pre- diction errors, also a regression tree model, based on the C&RT algorithm [8], was utilized. The regression trees are non- parametric, non-linear models which are particularly suitable for small data sets with unknown characteristics. Because of the small number of records for the daily based data, the regression tree algorithm was set to keep only 2 records in a leave. The prediction results were compared with those obtained from the linear model.

Gene expression data provides insight into the ongoing molecular activities inside the cells especially in short term acute toxicity studies where the full phenotypic signs and symptoms may have not been fully developed [18]. In the present study, 48 differentially regulated genes were identified that are involved in important biological functions. Most of them (Bnip3l, Neo1, Clca1, Idh3a, Pank2, Prpsap1, Eif5B, Polr2h, Zfp110) are engaged in regulation of apoptosis, stress and cell growth. Isocitrate dehydrogenase (Idh3a) protects cell against oxidative damage [33] has been shown to be more active in producing Nicotinamide Adenine Dinucleotide Phosphate Reduced (NADPH) than other enzymes in the previous studies [34]. Down regulation of this gene clearly indicated that cell might have undergone oxidative stress following Apigenin treatment. Interest- ingly, the simultaneous upregulation of BCL2/adenovirus E1B interacting protein 3-like (Bnip3l) [35], and Neogenin (Neo1) [36] genes that are reported to regulate apoptosis, might be involved in the induction of apoptosis in degenerated hepatocytes of Apigenin treated mice in higher dose groups. Apigenin is reported to induce apoptosis by activating different genes like PKC-d and caspases [2]. Apigenin upregulates the expression of genes involved in transcrip- tion and translation machinery; Phosphoribosyl pyrophosphate synthetase associated protein 1 (Prpsap1), Eukaryotic translation initiation factor 5B (Eif5B), DNA directed polymerase (Polr2h), Zinc finger protein 110 (Zfp110). Pantothenate kinase 2 (Pank2), a mitochondrial enzyme catalyses the first regulatory step of Coenzyme A synthesis, is found to be down regulated in present study. This gene is responsible for a genetic movement disorder named Pank-associated neurodegeneration. Recent evidences sug- gest the silencing of Pank2 gene is directly associated with cell growth reduction and iron deregulation in hepatic cell lines [37]. Another downregulated gene was calcium-activated chloride channel (Clca1) which is integrated to plasma membrane. Another downregulated gene was calcium-activated chloride channel (Clca1) which is integrated to plasma membrane. Differential regulation of Clca1 in

other STSs, including liposarcomas and osteosarcomas [15,17,28,29,30,31,32,33]; however, no specific candidate genes from this region had been studied in the context of UPS. Aryl hydrocarbon receptor nuclear translocator (ARNT), which is also known as hypoxia-induced factor-1 beta (HIF-1beta), is constitu- tively expressed in all normal human tissues with increased expression in the ovary, lung, spleen, testis, and pancreas [34]. ARNT overexpression has been reported in breast cancer, hepatocellular carcinoma, and colon carcinoma cell lines [35,36]. PBXIP1 and SLC27A3 copy number gains were also observed in UPS samples (38% of the cases for each). The SLC27A3 gene encodes Acetyl-CoA synthetase, which is important for fatty-acid metabolism, particularly in neoplastic cells [37]. Although the contribution of lipid-metabolic pathways to tumor development is poorly understood, it is known that a high rate of lipid synthesis is necessary for the biogenesis of plasma membranes, which is required for tumor growth [38]. Lipids also play important roles as second messengers, which can be misregulated in tumor cells. Indeed, increases in the levels of specific messenger lipids are often associated with malignant phenotypes [39]. Functional studies have shown SLC27A3 to be an effective therapeutic target in gliomas because it maintains the oncogenic properties of glioma cell lines through the regulation of the AKT protein [37].

β-actin showed maximum variations in its expression in the blood cells, being inappropriate for standardization. For the samples of human skeletal muscles exposed to creatine supplementation on short-term and high intensity exercise, the β-actin gene was considered a valid option for real-time PCR analysis (Murphy et al. 2003). In the studies with lymphoid cells in cattle (BL-3), β-actin was stable when analyzed by the program NormFinder (Anstaett et al. 2010). In the patients undergoing renal transplantation, acute rejection and antirejection therapy, the gene β-actin is influenced in its expression, which makes it unsuitable for standardization (Gibbs et al. 2003). During the analysis of the expression of interstitial cells in the heart valves in sheep, the gene β-actin was considered invalid (Yperman et al. 2004). According to Fu et al. (2010) in normal ovarian tissue, or in ovaries with endometriomas or various types of tumors, β-actin showed low stability among the groups. Several data have shown that the genes of references, such as β- actin, depending of the tissue, may be inappropriate as internal standard because of its variability (Bustin 2002). Several authors confirmed that the β-actin used as housekeeping presented differential expression in various tissues (Selvey et al. 2001; Barber et al. 2005).

Screening for antibody producing hybridomas: The principle for creating an antibody secreting hybridoma is based on the cellular fusion between antibodies producing spleen cells, with limited life spam, with cells derived from an immortal tumor of lymphocytes that do not synthesize immunoglobulin, myeloma cells. The resulting hybridoma not only is capable of producing and secreting antibodies but also of unlimited growth. As the myeloma cell line is defective in the enzyme hypoxanthine guanidine phosphoribosyltransferase (HGPRT), they die when cultured in DMEM supplemented with HAT (aminopterin blocks the main DNA synthesis pathway and the alternative pathway that requires the use of exogenous hypoxanthine depends on the enzyme HGPRT). Only hybrids between myeloma and spleen cells are capable of surviving in HAT supplemented medium. At day 10, supernatants of the wells containing hybridomas (previously screened under the microscope) were tested by ELISA. Assay plate was prepared as described previously, including a well with no antigen (PBS only) to account for non-specific reaction of the primary antibody (antiserum). Four different controls were performed against the recombinant protein: a positive control using the antiserum diluted 1:1000; and three negative controls (primary antibody (antiserum) with no secondary antibody; no primary antibody with secondary antibody; no primary or secondary antibodies). Hybridoma supernatant was used as primary antibody. The hybridomas selected by ELISA were then expanded to 24-well plates and subsequently to 25 cm 3 tissue culture flasks and supernatants tested again by ELISA and also by WB as described above but using supernatants as primary antibody. For storage supernatants were filtered using a 0.22 μm syringe filter (Carl Roth GmbH) and kept at 4ºC or -20ºC.