Reference Gene Validation for RT-qPCR, a Note on Different Available Software Packages

Spiegelaere, Ward De; Dern-Wieloch, Jutta; Weigel, Roswitha; Schumacher, Valérie; Schorle, Hubert; Nettersheim, Daniel; Bergmann, Martin; Brehm, Ralph; Kliesch, Sabine; Vandekerckhove, Linos; Fink, Cornelia

doi:10.1371/journal.pone.0122515

Cited by 219 publications

(201 citation statements)

References 29 publications

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“…In order to correct for this, we manually adjusted the raw Ct-values for efficiencies before analysis. This has previously proved to make results obtained with the RefFinder software comparable to those obtained with the stand-alone applications22. Similar and comparable evaluations are obtained from the Genorm, NormFinder, and the ΔCt-methods, with deviations for some genes obtained from BestKeeper.…”

Section: Discussionsupporting

confidence: 60%

“…RefFinder, a free online software platform for identification of stable RGs, derives a comprehensive ranking based on the geometric mean of the scores from Genorm, BestKeeper, NormFinder, and the ΔCt-method in order to extract the best RGs based on the different mathematical approaches20. Although these methods differ in their mathematical design, studies have shown only small variations in the outcomes for Genorm, NormFinder, and BestKeeper, and also between the stand-alone applications for Genorm, NormFinder, and BestKeeper, and RefFinder, making these methods comparable2122.…”

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confidence: 99%

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Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases

Rydbirk

Folke

Winge

et al. 2016

Sci Rep

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Evaluation of gene expression levels by reverse transcription quantitative real-time PCR (RT-qPCR) has for many years been the favourite approach for discovering disease-associated alterations. Normalization of results to stably expressed reference genes (RGs) is pivotal to obtain reliable results. This is especially important in relation to neurodegenerative diseases where disease-related structural changes may affect the most commonly used RGs. We analysed 15 candidate RGs in 98 brain samples from two brain regions from Alzheimer’s disease (AD), Parkinson’s disease (PD), Multiple System Atrophy, and Progressive Supranuclear Palsy patients. Using RefFinder, a web-based tool for evaluating RG stability, we identified the most stable RGs to be UBE2D2, CYC1, and RPL13 which we recommend for future RT-qPCR studies on human brain tissue from these patients. None of the investigated genes were affected by experimental variables such as RIN, PMI, or age. Findings were further validated by expression analyses of a target gene GSK3B, known to be affected by AD and PD. We obtained high variations in GSK3B levels when contrasting the results using different sets of common RG underlining the importance of a priori validation of RGs for RT-qPCR studies.

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Section: Discussionsupporting

confidence: 60%

mentioning

confidence: 99%

Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases

Rydbirk

Folke

Winge

et al. 2016

Sci Rep

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“…Moreover, geNorm and NormFinder were also in agreement on the least stable gene for each treatment. The accordance in the results provided by these algorithms was also mentioned in some previous study on other plants (De Spiegelaere et al, 2015; Mafra et al, 2012). However, obvious divergence in these results still exists in some situations, mainly caused by the varying priorities in different algorithms.…”

Section: Discussionsupporting

confidence: 87%

Evaluation of putative reference genes for quantitative real-time PCR normalization inLilium regaleduring development and under stress

Liu

Chi

Zhang

et al. 2016

PeerJ

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Normalization to reference genes is the most common method to avoid bias in real-time quantitative PCR (qPCR), which has been widely used for quantification of gene expression. Despite several studies on gene expression, Lilium, and particularly L. regale, has not been fully investigated regarding the evaluation of reference genes suitable for normalization. In this study, nine putative reference genes, namely 18S rRNA, ACT, BHLH, CLA, CYP, EF1, GAPDH, SAND and TIP41, were analyzed for accurate quantitative PCR normalization at different developmental stages and under different stress conditions, including biotic (Botrytis elliptica), drought, salinity, cold and heat stress. All these genes showed a wide variation in their Cq (quantification Cycle) values, and their stabilities were calculated by geNorm, NormFinder and BestKeeper. In a combination of the results from the three algorithms, BHLH was superior to the other candidates when all the experimental treatments were analyzed together; CLA and EF1 were also recommended by two of the three algorithms. As for specific conditions, EF1 under various developmental stages, SAND under biotic stress, CYP/GAPDH under drought stress, and TIP41 under salinity stress were generally considered suitable. All the algorithms agreed on the stability of SAND and GAPDH under cold stress, while only CYP was selected under heat stress by all of them. Additionally, the selection of optimal reference genes under biotic stress was further verified by analyzing the expression level of LrLOX in leaves inoculated with B. elliptica. Our study would be beneficial for future studies on gene expression and molecular breeding of Lilium.

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“…Herein, we have employed geNorm, first developed by Vandesompele, et al [34], and NormFinder statistical programs to access the stability of candidate reference genes. Both retrieved highly comparable results, especially in terms of gene stability ranking [51]. Accordingly, we have identified B2M and HPRT as the most stable reference genes to address the impact of oxygen shortage in hypoxic bladder cancer cells, irrespectively of their molecular nature.…”

Section: Discussionmentioning

confidence: 93%

Reference Genes for Addressing Gene Expression of Bladder Cancer Cell Models under Hypoxia: A Step Towards Transcriptomic Studies

et al. 2016

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Highly aggressive, rapidly growing tumors contain significant areas of hypoxia or anoxia as a consequence of inadequate and/or irregular blood supply. During oxygen deprivation, tumor cells withstand a panoply of adaptive responses, including a shift towards anaerobic metabolism and the reprogramming of the transcriptome. One of the major mediators of the transcriptional hypoxic response is the hypoxia-inducible factor 1 (HIF-1), whose stabilization under hypoxia acts as an oncogenic stimulus contributing to chemotherapy resistance, invasion and metastasis. Gene expression analysis by qRT-PCR is a powerful tool for cancer cells phenotypic characterization. Nevertheless, as cells undergo a severe transcriptome remodeling.in response to oxygen deficit, the precise identification of reference genes poses a significant challenge for hypoxic studies. Herein, we aim to establish the best reference genes for studying the effects of hypoxia on bladder cancer cells. Accordingly, three bladder cancer cell lines (T24, 5637, and HT1376) representative of two distinct carcinogenesis pathways to invasive cancer (FGFR3/CCND1 and E2F3/RB1) were used. Additionally, we have explored the most suitable control gene when addressing the influence of Deferoxamine Mesilate salt (DFX), an iron chelator often used to avoid the proteasomal degradation of HIF-1α, acting as an hypoxia-mimetic agent. Using bioinformatics tools (GeNorm and NormFinder), we have elected B2M and HPRT as the most stable genes for all cell lines and experimental conditions out of a panel of seven putative candidates (HPRT, ACTB, 18S, GAPDH, TBP, B2M, and SDHA). These observations set the molecular basis for future studies addressing the effect of hypoxia and particularly HIF-1α in bladder cancer cells.

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Reference Gene Validation for RT-qPCR, a Note on Different Available Software Packages

Cited by 219 publications

References 29 publications

Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases

Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases

Evaluation of putative reference genes for quantitative real-time PCR normalization inLilium regaleduring development and under stress

Reference Genes for Addressing Gene Expression of Bladder Cancer Cell Models under Hypoxia: A Step Towards Transcriptomic Studies

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