Identification of valid reference genes during the differentiation of human myoblasts

Background  

Analysis of RNA expression using real-time PCR (qRT-PCR) traditionally includes reference genes (RG) as an internal control. This practice is being questioned as it becomes increasingly clear that RG may vary considerably under certain experimental conditions. Thus, the validity of a particular RG must be determined for each experimental setting. We used qRT-PCR to measure the levels of six RG, which have been reported in the literature to be invariant. The RG were analyzed in human myoblast cultures under differentiation conditions. We examined the expression by qRT-PCR of mRNA encoding Beta-actin (ACTB), Beta-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), peptidylprolyl isomerase A (PPIA), TATA box binding protein (TBP) and ribosomal protein, large, P0 (RPLPO). The mRNA expression of the following genes of interest (GOI) were analyzed: skeletal muscle alpha 1 actin (ACTA1), myogenin/myogenic factor 4 (MYOG), embryonic skeletal muscle myosin heavy chain 3 (MYH3) and the activity of creatine phosphokinase (CK). The geNorm, NormFinder and BestKeeper software programs were used to ascertain the most suitable RG to normalize the RNA input.     

RNA-Seq is not required to determine stable reference genes for qPCR normalization

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, however, we demonstrate that the statistical approach to determine the best reference genes from commonly used conventional candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using conventional reference genes render the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.     

Evaluation of candidate reference genes in Clostridium difficile for gene expression normalization

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive, efficient and reproducible technique for studying gene expression. Identification of stably expressed reference genes is required to avoid bias in these studies yet mostly unvalidated reference genes are used in studying gene expression in Clostridium difficile. Here, we sought to identify a set of stable reference genes used to normalize C. difficile expression data comparing exponential versus stationary phases of growth. Eight candidate reference genes (rpoA, rrs, gyrA, gluD, adk, rpsJ, tpi, and rho) were assessed in 3 C. difficile genotypes (ribotypes 027, 078, and 001). The primers were analyzed for efficiency and the 8 genes were ranked according to their stability. Overall, the genes rrs, adk, and rpsJ ranked among the most stable. Identification of the most stable genes was, however, strain dependent and suggests that selection of reference genes in a heterogeneous species, such as C. difficile, requires multiple genes to be assessed to confirm their stability within the strains being studied.     

Identification of valid reference genes for circadian gene-expression studies in human mammary epithelial cells

ABSTRACT

The circadian clock controls most of the physiological processes in the body throughout days and nights’ alternation. Its dysregulation has a negative impact on many aspects of human health, such as obesity, lipid disorders, diabetes, skin regeneration, hematopoiesis and cancer. To date, poor is known on the molecular mechanisms that links mammary gland homeostasis to the circadian clock but recent reports highlight the importance of loss of circadian genes for mammary gland development and during tumour progression in breast cancer. Gene expression studies are then required to clarify how the circadian clock can modulates the human mammary gland development during ontology and its behaviour in physiological and oncogenic context. For this, in addition to genome-wide studies, real-time quantitative RT-PCR (qPCR) is a powerful and pertinent technique to quantify the expression of a reduced set of genes of interest in many different samples. Relative quantification of qPCR data requires the use of reference genes for normalisation. For circadian studies, reference genes expression must not oscillate in mirror of the circadian clock and must not be affected by the synchronisation protocols required in vitro to reset the circadian clock. Inappropriate selection of reference genes can consequently affect the amplitude of gene expression oscillation and bias data interpretation. Currently, no standard reference genes have been validated regarding these criteria for human mammary epithelial cells and the purpose of this study was to fill this gap. For this, we used the RefFinder tool, which combines four different algorithms, on 9 candidate reference genes. We compared reference genes stability using three different synchronisation protocols applied on four different mammary epithelial cell lines. This allowed us to define a set of reference genes in human mammary epithelial cells whose expression remains stable despite synchronisation protocols. We observed that the synchronisation of cells by serum shock was the most suitable procedure for maintaining the amplitude of oscillation of clock genes over time and we identified RPL4, RPLP0, HSPCB and TBP as an optimal combination of reference genes for the normalisation of the oscillatory expression of clock genes in human mammary epithelial cells.     

Screening of valid reference genes for real-time RT-PCR data normalization in Hevea brasiliensis and expression validation of a sucrose transporter gene HbSUT3

Real-time RT-PCR (RT-qPCR) is a sensitive and precise method of quantifying gene expression, however, suitable reference genes are required. Here, a systematic reference gene screening was performed by RT-qPCR on 22 candidate genes in Hevea brasiliensis. Two ubiquitin-protein ligases (UBC2a and UBC4) were the most stable when all samples were analyzed together. A mitosis protein (YLS8) and a eukaryotic translation initiation factor (eIF1Aa) were the most stable in response to tapping. UBC2b and UBC1 were the most stable among different genotypes. UBC2b and a DEAD box RNA helicase (RH2b) were the most stable across individual trees. YLS8 and RH8 were most stably expressed in hormone-treated samples. Expression of the candidate reference genes varied significantly across different tissues, and at least four genes (RH2b, RH8, UBC2a and eIF2) were needed for expression normalization. In addition, examination of relative expression of a sucrose transporter HbSUT3 in different RNA samples demonstrated the importance of additional reference genes to ensure accurate quantitative expression analysis. Overall, our work serves as a guide for selection of reference genes in RT-qPCR gene expression studies in H. brasiliensis.     

Evaluating reference genes to normalize gene expression in human epileptogenic brain tissues

Several reference genes have been used to quantify gene expression in human epilepsy surgery tissue. However, their reliability has not been validated in detail, although this is crucial in interpreting epilepsy-related changes of gene expression. We evaluated 12 potential reference genes in neocortical tissues resected from patients with temporal lobe epilepsy (TLE) with either few or many seizures (n=6 each) and post mortem controls (n=6) using geNorm and NormFinder algorithms. For all candidate reference genes threshold cycle (C(T)) values were measured. geNorm analysis revealed that the expression of e.g. glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) and hypoxanthine phosphoribosyl-transferase (HPRT) is unstable, whereas synaptophysin (SYP) and neuron-specific enolase (NSE)/mitochondrial 39S ribosomal protein L28 (MRPL) are most stably expressed. The geometric mean of SYP, NSE and MRPL levels is recommended as normalization factor (NF). NormFinder analysis, in contrast, indicated HPRT as the most stable single gene and recommended the geometric mean of TATA-box binding protein (TBP) and NSE levels as NF. Different values of upregulation of glial fibrillary protein (GFAP) expression were found in TLE tissue compared to control tissue depending on the NF used: 4.5-fold (geNorm-NF), 4.7-fold (NormFinder-NF), 4.2-fold (vs. GAPDH) and 7.8-fold (vs. HPRT). The expression of GABA(A) receptor subunit α5 (GARα5) was unaltered in the TLE groups compared to controls (geNorm-NF, NormFinder-NF, vs. GAPDH). However, normalization to HPRT suggests an apparent increase of GARα5 expression. In conclusion, the geNorm-NF (SYP/NSE/MRPL) and the NormFinder-NF (TBP/NSE) are equally suitable for normalization of gene expression in the human epileptogenic neocortex. In contrast, normalization to single and probably less stably expressed genes may not deliver accurate results.     

Validation of reference genes for the relative quantification of gene expression in human epicardial adipose tissue

Background

Relative quantification is a commonly used method for assessing gene expression, however its accuracy and reliability is dependent upon the choice of an optimal endogenous control gene, and such choice cannot be made a priori. There is limited information available on suitable reference genes to be used for studies involving human epicardial adipose tissue. The objective of the current study was to evaluate and identify optimal reference genes for use in the relative quantification of gene expression in human epicardial fat depots of lean, overweight and obese subjects.

Methodology/Principal Findings

Some of the commonly used reference genes including 18S, ACTB, RPL27, HPRT, CYCA, GAPDH, RPLPO, POLR2A and B2M were quantified using real-time PCR analysis. The expression stability of these genes was evaluated using Genorm, Normfinder and Bestkeeper algorithms. In addition, the effect of sample size on the validation process was studied by randomly categorizing subjects in two cohorts of n = 2 and n = 33.

Conclusions/Significance

CYCA, GAPDH and RPL27 were identified as the most stable genes common to all three algorithms and both sample sizes. Their use as reference gene pairs might contribute to the enhanced robustness of relative quantification in the studies involving the human epicardial adipose tissue.     

Identification of reference genes for normalization of gene expression in thoroughbred and Jeju native horse(Jeju pony) tissues

Quantitative analysis of horse gene expression profiles under diverse experimental conditions is limited by the lack of reliable reference genes for normalization of mRNA levels. Therefore, in this study, the expression of potential reference genes was compared between thoroughbred and Jeju native horse (Jeju pony). We compared the expression of nine genes by quantitative real-time RT-PCR in fourteen tissues between the two horse breeds and analyzed their stability using the geNorm and NormFinder programs. The data obtained in this study suggest that the UBB gene could serve as a reference gene in gene expression analysis of thoroughbred and Jeju native horses.     

Reference genes for normalization of gene expression studies in human osteoarthritic articular cartilage

Background  

Assessment of gene expression is an important component of osteoarthritis (OA) research, greatly improved by the development of quantitative real-time PCR (qPCR). This technique requires normalization for precise results, yet no suitable reference genes have been identified in human articular cartilage. We have examined ten well-known reference genes to determine the most adequate for this application.     

Identification and validation of reference genes for quantitative RT-PCR normalization in wheat

Background  

Usually the reference genes used in gene expression analysis have been chosen for their known or suspected housekeeping roles, however the variation observed in most of them hinders their effective use. The assessed lack of validated reference genes emphasizes the importance of a systematic study for their identification. For selecting candidate reference genes we have developed a simple in silico method based on the data publicly available in the wheat databases Unigene and TIGR.     

Evaluation of potential reference genes for qRT-PCR data normalization in HeLa cells

Reference genes selection is one of the most important stages in qPCR data normalization when a problem of quantitative determination of gene expression is addressed. Stability of gene expression level in all experimental conditions is a basic criterion for the reference gene selection. Over the past decade a lot of publications concerning validation methods of suitable reference genes appeared. In this paper, the main approaches (ΔCt, geNorm, qBase and Haller’s equivalence test) were applied for the reference genes identification in HeLa cell line which is one of the most popular cellular models. Expression stability of seven candidate genes (HPRT1, ACTB, GAPDH, RPS18, HSPC3, UBC and SDHA) was determined at standard conditions, under heat shock and during relaxation. The genes RPS18 and HSPC3 were chosen as reference after the combination of all the validation methods.