Validation of Reference Housekeeping Genes for Gene Expression Studies in Western Corn Rootworm (Diabrotica virgifera virgifera)

Quantitative Real-time PCR (qRT-PCR) is a powerful technique to investigate comparative gene expression. In general, normalization of results using a highly stable housekeeping gene (HKG) as an internal control is recommended and necessary. However, there are several reports suggesting that regulation of some HKGs is affected by different conditions. The western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), is a serious pest of corn in the United States and Europe. The expression profile of target genes related to insecticide exposure, resistance, and RNA interference has become an important experimental technique for study of western corn rootworms; however, lack of information on reliable HKGs under different conditions makes the interpretation of qRT-PCR results difficult. In this study, four distinct algorithms (Genorm, NormFinder, BestKeeper and delta-CT) and five candidate HKGs to genes of reference (β-actin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; β-tubulin; RPS9, ribosomal protein S9; EF1a, elongation factor-1α) were evaluated to determine the most reliable HKG under different experimental conditions including exposure to dsRNA and Bt toxins and among different tissues and developmental stages. Although all the HKGs tested exhibited relatively stable expression among the different treatments, some differences were noted. Among the five candidate reference genes evaluated, β-actin exhibited highly stable expression among different life stages. RPS9 exhibited the most similar pattern of expression among dsRNA treatments, and both experiments indicated that EF1a was the second most stable gene. EF1a was also the most stable for Bt exposure and among different tissues. These results will enable researchers to use more accurate and reliable normalization of qRT-PCR data in WCR experiments.     

Validation of internal control for gene expression study in soybean by quantitative real-time PCR

Background  

Normalizing to housekeeping gene (HKG) can make results from quantitative real-time PCR (qRT-PCR) more reliable. Recent studies have shown that no single HKG is universal for all experiments. Thus, a suitable HKG should be selected before its use. Only a few studies on HKGs have been done in plants, and none in soybean, an economically important crop. Therefore, the present study was conducted to identify suitable HKG(s) for normalization of gene expression in soybean.     

Temperature and Development Impacts on Housekeeping Gene Expression in Cowpea Aphid,Aphis craccivora (Hemiptera: Aphidiae)

Quantitative real-time PCR (qRT-PCR) is a powerful technique to quantify gene expression. To standardize gene expression studies and obtain more accurate qRT-PCR analysis, normalization relative to consistently expressed housekeeping genes (HKGs) is required. In this study, ten candidate HKGs including elongation factor 1 α (EF1A), ribosomal protein L11 (RPL11), ribosomal protein L14 (RPL14), ribosomal protein S8 (RPS8), ribosomal protein S23 (RPS23), NADH-ubiquinone oxidoreductase (NADH), vacuolar-type H+-ATPase (ATPase), heat shock protein 70 (HSP70), 18S ribosomal RNA (18S), and 12S ribosomal RNA (12S) from the cowpea aphid, Aphis craccivora Koch were selected. Four algorithms, geNorm, Normfinder, BestKeeper, and the ΔC_t method were employed to evaluate the expression profiles of these HKGs as endogenous controls across different developmental stages and temperature regimes. Based on RefFinder, which integrates all four analytical algorithms to compare and rank the candidate HKGs, RPS8, RPL14, and RPL11 were the three most stable HKGs across different developmental stages and temperature conditions. This study is the first step to establish a standardized qRT-PCR analysis in A. craccivora following the MIQE guideline. Results from this study lay a foundation for the genomics and functional genomics research in this sap-sucking insect pest with substantial economic impact.     

Evaluation and validation of internal control genes for studying gene expression in the dinoflagellate Prorocentrum minimum using real-time PCR

Housekeeping genes (HKGs) are required for the normalization of expression levels in real-time PCR, and their selection is critical for gene expression studies. However, stable expressions of candidate HKGs vary among organisms and tissues and even according to environmental conditions. Here, we evaluated the gene expressions of 10 frequently used HKGs, including 18S rRNA, P2, ACT, TUA, TUB, CYC, eIF4E, MDH, UBQ, and GAPDH, with a total of 17 RNA samples extracted from the dinoflagellate Prorocentrum minimum. All the RNAs were prepared from various cells cultured under different conditions, including thermal shocks, toxic chemical exposures, and different life stages. Via C(T) analyses of the 10 HKGs using the geNorm software, TUA was selected as the most stable HKG for gene expression studies of the dinoflagellate, followed by MDH. Pair-wise variation (V) analysis showed that at least 2 genes were required for accurate normalization of gene expression studies depending on the experimental conditions. These HKGs are useful internal controls for the normalization of gene expression in P. minimum.     

Reference gene selection for real-time RT-PCR in regenerating mouse livers

The liver has an intrinsic ability to undergo active proliferation and recover functional liver mass in response to an injury response. This regenerative process involves a complex yet well orchestrated change in the gene expression profile. To produce accurate and reliable gene expression of target genes during various stages of liver regeneration, the determination of internal control housekeeping genes (HKGs) those are uniformly expressed is required. In the present study, the gene expression of 8 commonly used HKGs, including GAPDH, ACTB, HPRT1, GUSB, PPIA, TBP, TFRC, and RPL4, were studied using mouse livers that were quiescent and actively regenerating induced by partial hepatectomy. The amplification of the HKGs was statistically analyzed by two different mathematical algorithms, geNorm and NormFinder. Using this method, PPIA and TBP gene expression found to be relatively stable regardless of the stages of liver regeneration and would be ideal for normalization to target gene expression.     

Predicting housekeeping genes based on Fourier analysis

Housekeeping genes (HKGs) generally have fundamental functions in basic biochemical processes in organisms, and usually have relatively steady expression levels across various tissues. They play an important role in the normalization of microarray technology. Using Fourier analysis we transformed gene expression time-series from a Hela cell cycle gene expression dataset into Fourier spectra, and designed an effective computational method for discriminating between HKGs and non-HKGs using the support vector machine (SVM) supervised learning algorithm which can extract significant features of the spectra, providing a basis for identifying specific gene expression patterns. Using our method we identified 510 human HKGs, and then validated them by comparison with two independent sets of tissue expression profiles. Results showed that our predicted HKG set is more reliable than three previously identified sets of HKGs.     

Reference gene selection for transcriptional profiling by RT-qPCR in the 28-spotted larger potato ladybird

Henosepilachna vigintioctomaculata is one of the most serious defoliates attacking potatoes. However, studies on functional genes have greatly been limited due to the insufficiency of effective and stable endogenous references to normalize RT-qPCR data. In this report, nine housekeeping genes (RPL4, RPL6, RPL13, RPL32, RPS18, ACT, EF1α, GAPDH and α-TUB) involved in different biological processes were selected. Their expression levels under diverse experimental conditions including developmental stages, tissues, temperatures and host plants were determined using RT-qPCR technology. The tested candidate genes were comprehensively ranked based on five alternative stability analysis methods (Ct value, geNorm, NormFinder, BestKeeper and ReFinder). The results revealed that the optimal internal reference genes varied under different experimental conditions. Any gene pair among the five candidates (RPL4, RPL13, RPL32, RPS18 and EF1α) was a suitable reference gene set under different temperatures and on different host plants. A combination of RPL6 and RPL13 was recommended as the best reference gene set across different developmental stages. A pair of RPS18 and EF1α was ranked as the optimal reference gene combination within different tissues. The most suitable reference genes were RPS18 and RPL13 under four different experimental conditions. Our findings not only establish an accurate and reliable normalization of RT-qPCR data, but also lay a solid foundation for further functional gene researches in H. vigintioctomaculata.     

Selection and Evaluation of Reference Genes for Expression Analysis Using qRT-PCR in the Beet Armyworm Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae)

Quantitative real-time PCR (qRT-PCR) is a reliable and reproducible technique for measuring and evaluating changes in gene expression. The most common method for analyzing qRT-PCR data is to normalize mRNA levels of target genes to internal reference genes. Evaluating and selecting stable reference genes on a case-by-case basis is critical. The present study aimed to facilitate gene expression studies by identifying the most suitable reference genes for normalization of mRNA expression in qRT-PCR analysis of the beet armyworm Spodoptera exigua (Lepidoptera: Noctuidae). For this purpose, three software tools (geNorm, NormFinder and BestKeeper) were used to investigate 10 candidate reference genes in nine developmental stages and five different tissues (epidermis, head, midgut, fat body and hemolymph) in three larval physiological stages (molting, feeding and wandering stages) of, S. exigua. With the exception of 18S ribosomal RNA (18S), all other candidate genes evaluated, β-actin1(ACT1), β-actin2 (ACT2), elongation factor1(EF1), elongation factor 2 (EF2), Glyceralde hyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein L10 (L10), ribosomal protein L17A (L17A), superoxide dismutase (SOD), α-tubulin (TUB),proved to be acceptable reference genes. However, their suitability partly differed between physiological stages and different tissues. L10, EF2 and L17A ranked highest in all tissue sample sets. SOD, ACT2, GAPDH, EF1 and ACT1 were stably expressed in all developmental stage sample sets; ACT2, ACT1 and L10 for larvae sample sets; GAPDH, ACT1 and ACT2 for pupae and adults; SOD and L17A for males; and EF2 and SOD for females. The expression stability of genes varied in different conditions. The findings provided here demonstrated, with a few exceptions, the suitability of most of the 10 reference genes tested in tissues and life developmental stages. Overall, this study emphasizes the importance of validating reference genes for qRT-PCR analysis in S. exigua.     

Reference Gene Selection for qRT-PCR Normalization in <i>Iris germanica</i> L.

Quantitative real-time PCR (qPCR) is an effective and widely used method to analyze expression patterns of target genes. Selection of stable reference genes is a prerequisite for accurate normalization of target gene expression by qRT-PCR. In Iris germanica L., no studies have yet been published regarding the evaluation of potential reference genes. In this study, nine candidate reference genes were assessed at different flower developmental stages and in different tissues by four different algorithms (GeNorm, NormFinder, BestKeeper, and RefFinder). The results revealed that ACT11 (Actin 11) and EF1α (Elongation factor 1 alpha) were the most stable reference genes in different tissues, whereas TUA (Tubulin alpha) and UBC9 (Ubiquitin-protein ligase 9) were the most stable ones in different flower developmental stages. UBC9 and ACT11 were the most stable reference genes in all of the tested samples, while the SAMDC (S-Adenosylmethionine decarboxylase) showed the least stability. Finally, to validate the suitability of the selected reference genes, the relative expression level of IgTPS (beta-caryophyllene synthase) was assessed and highlighted the importance of suitable reference gene selection. This work constitutes the first systematic evaluation of potential reference genes in I. germanica and provides guidelines for future research on gene function and molecular mechanisms on I. germanica and related species.     

Exploring Valid Reference Genes for Quantitative Real-Time PCR Analysis in Sesamia inferens (Lepidoptera: Noctuidae)

The pink stem borer, Sesamia inferens, which is endemic in China and other parts of Asia, is a major pest of rice and causes significant yield loss in this host plant. Very few studies have addressed gene expression in S. inferens. Quantitative real-time PCR (qRT-PCR) is currently the most accurate and sensitive method for gene expression analysis. In qRT-PCR, data are normalized using reference genes, which help control for internal differences and reduce error between samples. In this study, seven candidate reference genes, 18S ribosomal RNA (18S rRNA), elongation factor 1 (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal protein S13 (RPS13), ribosomal protein S20 (RPS20), tubulin (TUB), and β-actin (ACTB) were evaluated for their suitability in normalizing gene expression under different experimental conditions. The results indicated that three genes (RPS13, RPS20, and EF1) were optimal for normalizing gene expression in different insect tissues (head, epidermis, fat body, foregut, midgut, hindgut, Malpighian tubules, haemocytes, and salivary glands). 18S rRNA, EF1, and GAPDH were best for normalizing expression with respect to developmental stages and sex (egg masses; first, second, third, fourth, fifth, and sixth instar larvae; male and female pupae; and one-day-old male and female adults). 18S rRNA, RPS20, and TUB were optimal for fifth instars exposed to different temperatures (−8, −6, −4, −2, 0, and 27°C). To validate this recommendation, the expression profile of a target gene heat shock protein 83 gene (hsp83) was investigated, and results showed the selection was necessary and effective. In conclusion, this study describes reference gene sets that can be used to accurately measure gene expression in S. inferens.     

Evaluating a set of reference genes for expression normalization in multiple tissues and skeletal muscle at different development stages in pigs using quantitative real-time polymerase chain reaction

Gene expression analysis requires the use of reference genes consistently expressed under various conditions. In many cases, however, the commonly used reference genes are not uniformly expressed independently of tissues or environmental conditions. To provide a set of reliable reference genes in pigs, we used quantitative polymerase chain reaction to examine expression of six common reference genes (GAPDH, ACTB, H3F3A, HPRT1, RPL32, and RPS18) in adult tissues and prenatal skeletal muscles at 33, 65, and 90 days postcopulation from Tongcheng (obese-type) and Landrace (lean-type) pigs. The expression stability of these reference genes was evaluated by NormFinder, BestKeeper, and geNorm methods. Our data suggest that the reference genes were expressed variably in different tissues, developmental stages and breeds. RPS18, PRL32, and H3F3A could be used as internal controls to normalize gene expression in pig tissues and developmental skeletal muscle. The combination of internal control genes was necessary for accurate expression normalization. During skeletal muscle development, H3F3A and RPS18 would be the most appropriate combination to normalize gene expression in Tongcheng pigs, whereas the combination of PRL32 and RPS18 would be more suitable in Landrace pigs. In different tissues, the expression of PRL32 and RPS18 was the most consistent, and the combination of three genes (RPL32, RPS18, and H3F3A) is the most suitable for accurate normalization.