Reference Genes for Expression Analyses by qRT-PCR in Phthorimaea operculella (Lepidoptera: Gelechiidae)

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Abstract

Due to a lack of effective internal references, studies on functional genes in Phthorimaea operculella, a serious Lepidopteran pest attacking potatoes worldwide, have been greatly limited. To select suitable endogenous controls, ten housekeeping genes of actin (ACT), α-tubulin (α-TUB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1α (EF1α), 18S and 28S ribosomal RNA (18S, 28S), ribosomal protein genes RPL4, RPL13 and RPL27 and superoxide dismutase (SOD) were tested. Their expression levels were determined under three different experimental conditions (developmental stages, tissues/organs and temperatures) using qRT-PCR technology. The stability was evaluated with five methods (Ct value, geNorm, NormFinder, BestKeeper and RefFinder). The results clarified that RPL13, EF1α and RPL27 are ranked as the best reference gene combination for measuring gene expression levels among different developing stages and under various temperatures; EF1α and RPL13 are recommended to normalize the gene expression levels among diverse tissues. EF1α and RPL13 are the best reference genes in all the experimental conditions. To validate the utility of the selected reference pair, EF1α and RPL13, we estimated the tissue-biased expression level of chitin synthase A gene (PoChSA). As expected, PoChSA was abundantly expressed in ectodermally derived epidermal cells, and lowly transcribed in the midgut. These findings will lay the foundation for future research on the molecular physiology and biochemistry of P. operculella.

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The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments.

Stephen A Bustin, Vladimir Benes, Jeremy A Garson … (2009)

Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader's ability to evaluate critically the quality of the results presented or to repeat the experiments. The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement. Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.

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Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.

Claus Lindbjerg Andersen, Jens Ledet Jensen, Torben Falck Ørntoft (2004)

Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.

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Reference genes in real-time PCR

Bartłomiej Kozera, Marcin Rapacz (2013)

This paper aims to discuss various aspects of the use of reference genes in qPCR technique used in the thousands of present studies. Most frequently, these are housekeeping genes and they must meet several criteria so that they can lay claim to the name. Lots of papers report that in different conditions, for different organisms and even tissues the basic assumption—the constant level of the expression is not maintained for many genes that seem to be perfect candidates. Moreover, their transcription can not be affected by experimental factors. Sounds simple and clear but a great number of designed protocols and lack of consistency among them brings confusion on how to perform experiment properly. Since during selection of the most stable normalizing gene we can not use any reference gene, different ways and algorithms for their selection were developed. Such methods, including examples of best normalizing genes in some specific cases and possible mistakes are presented based on available sources. Numerous examples of reference genes applications, which are usually in too few numbers in relevant articles not allowing to make a solid fundament for a reader, will be shown along with instructive compilations to make an evidence for presented statements and an arrangement of future qPCR experiments. To include all the pitfalls and problems associated with the normalization methods there is no way not to begin from sample preparation and its storage going through candidate gene selection, primer design and statistical analysis. This is important because numerous short reviews available cover the topic only in lesser extent at the same time giving the reader false conviction of complete topic recognition.