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Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

ABSTRACT: BACKGROUND:Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. RESULTS:We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. CONCLUSIONS:The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.

SUBMITTER: Vandesompele J

PROVIDER: S-EPMC126239 | biostudies-literature | 2002 Jun

REPOSITORIES: biostudies-literature

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Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

Vandesompele Jo J De Preter Katleen K Pattyn Filip F Poppe Bruce B Van Roy Nadine N De Paepe Anne A Speleman Frank F

Genome biology 20020618 7

<h4>Background</h4>Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been report ...[more]

PMID: 12184808

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Project description:BackgroundNormalizing through reference genes, or housekeeping genes, can make more accurate and reliable results from reverse transcription real-time quantitative polymerase chain reaction (qPCR). Recent studies have shown that no single housekeeping gene is universal for all experiments. Thus, suitable reference genes should be the first step of any qPCR analysis. Only a few studies on the identification of housekeeping gene have been carried on plants. Therefore qPCR studies on important crops such as cotton has been hampered by the lack of suitable reference genes.ResultsBy the use of two distinct algorithms, implemented by geNorm and NormFinder, we have assessed the gene expression of nine candidate reference genes in cotton: GhACT4, GhEF1alpha5, GhFBX6, GhPP2A1, GhMZA, GhPTB, GhGAPC2, GhbetaTUB3 and GhUBQ14. The candidate reference genes were evaluated in 23 experimental samples consisting of six distinct plant organs, eight stages of flower development, four stages of fruit development and in flower verticils. The expression of GhPP2A1 and GhUBQ14 genes were the most stable across all samples and also when distinct plants organs are examined. GhACT4 and GhUBQ14 present more stable expression during flower development, GhACT4 and GhFBX6 in the floral verticils and GhMZA and GhPTB during fruit development. Our analysis provided the most suitable combination of reference genes for each experimental set tested as internal control for reliable qPCR data normalization. In addition, to illustrate the use of cotton reference genes we checked the expression of two cotton MADS-box genes in distinct plant and floral organs and also during flower development.ConclusionWe have tested the expression stabilities of nine candidate genes in a set of 23 tissue samples from cotton plants divided into five different experimental sets. As a result of this evaluation, we recommend the use of GhUBQ14 and GhPP2A1 housekeeping genes as superior references for normalization of gene expression measures in different cotton plant organs; GhACT4 and GhUBQ14 for flower development, GhACT4 and GhFBX6 for the floral organs and GhMZA and GhPTB for fruit development. We also provide the primer sequences whose performance in qPCR experiments is demonstrated. These genes will enable more accurate and reliable normalization of qPCR results for gene expression studies in this important crop, the major source of natural fiber and also an important source of edible oil. The use of bona fide reference genes allowed a detailed and accurate characterization of the temporal and spatial expression pattern of two MADS-box genes in cotton.

Project description:BackgroundReal-time quantitative reverse transcription PCR (RT-qPCR) data needs to be normalized for its proper interpretation. Housekeeping genes are routinely employed for this purpose, but their expression level cannot be assumed to remain constant under all possible experimental conditions. Thus, a systematic validation of reference genes is required to ensure proper normalization. For soybean, only a small number of validated reference genes are available to date.ResultsA systematic comparison of 14 potential reference genes for soybean is presented. These included seven commonly used (ACT2, ACT11, TUB4, TUA5, CYP, UBQ10, EF1b) and seven new candidates (SKIP16, MTP, PEPKR1, HDC, TIP41, UKN1, UKN2). Expression stability was examined by RT-qPCR across 116 biological samples, representing tissues at various developmental stages, varied photoperiodic treatments, and a range of soybean cultivars. Expression of all 14 genes was variable to some extent, but that of SKIP16, UKN1 and UKN2 was overall the most stable. A combination of ACT11, UKN1 and UKN2 would be appropriate as a reference panel for normalizing gene expression data among different tissues, whereas the combination SKIP16, UKN1 and MTP was most suitable for developmental stages. ACT11, TUA5 and TIP41 were the most stably expressed when the photoperiod was altered, and TIP41, UKN1 and UKN2 when the light quality was changed. For six different cultivars in long day (LD) and short day (SD), their expression stability did not vary significantly with ACT11, UKN2 and TUB4 being the most stable genes. The relative gene expression level of GmFTL3, an ortholog of Arabidopsis FT (FLOWERING LOCUS T) was detected to validate the reference genes selected in this study.ConclusionNone of the candidate reference genes was uniformly expressed across all experimental conditions, and the most suitable reference genes are conditional-, tissue-specific-, developmental-, and cultivar-dependent. Most of the new reference genes performed better than the conventional housekeeping genes. These results should guide the selection of reference genes for gene expression studies in soybean.

Project description:BackgroundThe elucidation of gene expression patterns leads to a better understanding of biological processes. Real-time quantitative RT-PCR has become the standard method for in-depth studies of gene expression. A biologically meaningful reporting of target mRNA quantities requires accurate and reliable normalization in order to identify real gene-specific variation. The purpose of normalization is to control several variables such as different amounts and quality of starting material, variable enzymatic efficiencies of retrotranscription from RNA to cDNA, or differences between tissues or cells in overall transcriptional activity. The validity of a housekeeping gene as endogenous control relies on the stability of its expression level across the sample panel being analysed. In the present report we describe the first systematic evaluation of potential internal controls during tomato development process to identify which are the most reliable for transcript quantification by real-time RT-PCR.ResultsIn this study, we assess the expression stability of 7 traditional and 4 novel housekeeping genes in a set of 27 samples representing different tissues and organs of tomato plants at different developmental stages. First, we designed, tested and optimized amplification primers for real-time RT-PCR. Then, expression data from each candidate gene were evaluated with three complementary approaches based on different statistical procedures. Our analysis suggests that SGN-U314153 (CAC), SGN-U321250 (TIP41), SGN-U346908 ("Expressed") and SGN-U316474 (SAND) genes provide superior transcript normalization in tomato development studies. We recommend different combinations of these exceptionally stable housekeeping genes for suited normalization of different developmental series, including the complete tomato development process.ConclusionThis work constitutes the first effort for the selection of optimal endogenous controls for quantitative real-time RT-PCR studies of gene expression during tomato development process. From our study a tool-kit of control genes emerges that outperform the traditional genes in terms of expression stability.

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Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

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Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

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