Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies

Tricarico, Carmela; Pinzani, Pamela; Bianchi, Simonetta; Paglierani, Milena; Distante, V.; Pazzagli, Mario; Bustin, Stephen A.; Orlando, Claudio

doi:10.1016/s0003-2697(02)00311-1

Cited by 503 publications

(405 citation statements)

References 24 publications

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“…These findings are in agreement with our [19] as well as other [20,21] earlier reports of significant sex, hormonal and non-hormonal effects on the expression levels of such housekeeping genes as cyclophilin, tyrosine aminotransferase, β-actin, tubulin, glyceraldehyde-3-phosphate dehydrogenase and 18S in rat liver [19]. Accordingly, we normalized real-time PCR determined CYP2C11 mRNA concentrations to total RNA (Table 1) as we [22] and others [23] have reported.…”

Section: Sexually Dimorphic Expression Of Tubulinsupporting

confidence: 93%

Sex-dependent expression of CYP2C11 in spleen, thymus and bone marrow regulated by growth hormone

Thangavel

Dhir

Volgin

et al. 2007

Biochemical Pharmacology

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CYP2C11, the most commonly expressed isoform of cytochrome P450 in male rat liver, was measured in spleen, thymus and bone marrow by quantitative real-time PCR and enhanced Western blotting. CYP2C11 concentrations in the lymphoid tissues were a fraction of that observed in liver, but like the liver, were sexually dimorphic (M>F) with mRNA and protein levels in agreement. Although the response to hypophysectomy varied according to tissue and sex, expression levels of CYP2C11 in all measured tissues remained greater in males. Further differences in CYP2C11 expression between liver and lymphoid tissue were observed following restoration of the circulating masculine growth hormone profile in hypophysectomized rats. In contrast to the liver where the renaturalized growth hormone profile elevated CYP2C11 expression in both sexes, the response was opposite in spleen and thymus with isoform concentrations declining in both sexes. Lastly, the divergent response of CYP2C11 between the liver and immune system was examined in cultured splenocytes exposed to different mitogens. In contrast to the dramatic depletion of CYP2C11 reported in proliferating hepatocytes, mitogen-stimulation resulted in a significant elevation in splenocyte CYP2C11 expression. In summary, we report for the first time that thymus, spleen and bone marrow express, albeit nominal, sex-dependent levels of CYP2C11 (M>F) whose regulation appears to be under some hormonal control, but very different from that of the hepatic isoform.

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Section: Sexually Dimorphic Expression Of Tubulinsupporting

confidence: 93%

Sex-dependent expression of CYP2C11 in spleen, thymus and bone marrow regulated by growth hormone

Thangavel

Dhir

Volgin

et al. 2007

Biochemical Pharmacology

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“…5,[17][18][19][20][21][22][23] Some have argued that the above-mentioned factors are academic as the overall study findings will not be affected because this variability is likely to be similar in the study and Real-time RT-PCR normalisation J Huggett et al control groups. 24 However, unless the variability is defined this argument simply does not hold.…”

Section: Normalisation; Reference Genesmentioning

confidence: 99%

“…24 However, unless the variability is defined this argument simply does not hold. While genes like GAPDH have been found to be appropriate for certain experimental situations 25 21 who demonstrated that if the wrong reference gene is chosen it can result in altered findings. This occurs when the reference gene is regulated by the experimental conditions.…”

Section: Normalisation; Reference Genesmentioning

confidence: 99%

Real-time RT-PCR normalisation; strategies and considerations

et al. 2005

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Real-time RT-PCR has become a common technique, no longer limited to specialist core facilities. It is in many cases the only method for measuring mRNA levels of vivo low copy number targets of interest for which alternative assays either do not exist or lack the required sensitivity. Benefits of this procedure over conventional methods for measuring RNA include its sensitivity, large dynamic range, the potential for high throughout as well as accurate quantification. To achieve this, however, appropriate normalisation strategies are required to control for experimental error introduced during the multistage process required to extract and process the RNA. There are many strategies that can be chosen; these include normalisation to sample size, total RNA and the popular practice of measuring an internal reference or housekeeping gene. However, these methods are frequently applied without appropriate validation. In this review we discuss the relative merits of different normalisation strategies and suggest a method of validation that will enable the measurement of biologically meaningful results.

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“…Variability may also occur when cellular signalling pathways and basic cell metabolism are disturbed (Singh and Green 1993). In addition, the expression of these reference genes may be influenced by experimental conditions (Thellin et al 1999;Selvey et al 2001;Tricarico et al 2002;Arukwe 2006;Valenti et al 2006;Tanic et al 2007), drug and hormone treatments (Bustin 2000;Gorzelniak et al 2001;Huggett et al 2005). Therefore, appropriate reference genes need to be identified and validated for every experimental design.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, appropriate reference genes need to be identified and validated for every experimental design. Indeed, several studies have provided evidence that the common practice of using single reference gene for normalisation has led to inaccurate or biased target gene expression profiling (Tricarico et al 2002;Vandesompele et al 2002). Therefore, the geometric mean of multiple reference genes should be carefully selected as the internal controls for accurate and reliable normalisation in gene expression study using real-time PCR (Vandesompele et al 2002).…”

Section: Introductionmentioning

confidence: 99%

UBC and YWHAZ as suitable reference genes for accurate normalisation of gene expression using MCF7, HCT116 and HepG2 cell lines

et al. 2011

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Relative quantification of in vitro gene expression using real-time PCR requires stably expressed reference gene for normalisation. In this study, total RNA from MCF7, HCT116 and HepG2 cells were extracted and converted to cDNA using commercially available kit, and real-time PCR was then performed to analyse the expression levels of twelve reference genes to select the most ideal reference gene for accurate normalisation in gene expression study. geNorm and NormFinder software were used to analyse the stabilities of the reference genes, which showed a wide range of C t values. The geNorm analysis showed the following ranking for stability of genes:A similar ranking of reference genes was obtained by NormFinder, and the four most stable reference genes were identical using both approaches. UBC and YWHAZ were proposed to be the two most suitable reference genes based on the above analyses. To further assess the stabilities of the UBC and YWHAZ in a formal experiment, MCF7, HCT116 and HepG2 cell lines were subjected to treatments with 5-aza-dC and TSA. Both UBC and YWHAZ exhibited stable expression levels across control and treatment groups. Therefore, we propose that UBC and YWHAZ are the two most suitable reference genes for our gene expression studies using MCF7, HCT116 and HepG2 cell lines.

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Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies

Cited by 503 publications

References 24 publications

Sex-dependent expression of CYP2C11 in spleen, thymus and bone marrow regulated by growth hormone

Sex-dependent expression of CYP2C11 in spleen, thymus and bone marrow regulated by growth hormone

Real-time RT-PCR normalisation; strategies and considerations

UBC and YWHAZ as suitable reference genes for accurate normalisation of gene expression using MCF7, HCT116 and HepG2 cell lines

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