Age-related changes in relative expression stability of commonly used housekeeping genes in selected porcine tissues

<p>Abstract</p> <p>Background</p> <p>Gene expression analysis using real-time RT-PCR (qRT-PCR) is increasingly important in biological research due to the high-throughput and accuracy of qRT-PCR. For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes or internal control genes is required. The stability of reference genes has a tremendous effect on the results of relative quantification of gene expression by qRT-PCR. The expression stability of reference genes could vary according to tissues, age of individuals and experimental conditions. In the pig however, very little information is available on the expression stability of reference genes. The aim of this research was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in varieties of porcine tissues at different ages.</p> <p>Results</p> <p>The mRNA expression stability of nine commonly used reference genes (<it>B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP </it>and <it>YWHAZ</it>) was determined in varieties of tissues collected from newborn, young and adult pigs. geNorm, NormFinder and BestKeeper software were used to rank the genes according to their stability. geNorm software revealed that <it>RPL4, PPIA </it>and <it>YWHAZ </it>showed high stability in newborn and adult pigs, while <it>B2M, YWHAZ </it>and <it>SDHA </it>showed high stability in young pigs. In all cases, <it>GAPDH </it>showed the least stability in geNorm. NormFinder revealed that <it>TBP </it>was the most stable gene in newborn and young pigs, while <it>PPIA </it>was most stable in adult pigs. Moreover, geNorm software suggested that the geometric mean of three most stable gene would be the suitable combination for accurate normalization of gene expression study.</p> <p>Conclusions</p> <p>Although, there was discrepancy in the ranking order of reference genes obtained by different analysing software methods, the geometric mean of the <it>RPL4, PPIA </it>and <it>YWHAZ </it>seems to be the most appropriate combination of housekeeping genes for accurate normalization of gene expression data in different porcine tissues at different ages.</p

Development and evaluation of different normalization strategies for gene expression studies in Candida albicans biofilms by real-time PCR

BACKGROUND: Candida albicans biofilms are commonly found on indwelling medical devices. However, the molecular basis of biofilm formation and development is not completely understood. Expression analysis of genes potentially involved in these processes, such as the ALS (Agglutinine Like Sequence) gene family can be performed using quantitative PCR (qPCR). In the present study, we investigated the expression stability of eight housekeeping genes potentially useful as reference genes to study gene expression in Candida albicans (C. albicans) biofilms, using the geNorm Visual Basic Application (VBA) for Microsoft Excel. To validate our normalization strategies we determined differences in ALS1 and ALS3 expression levels between C. albicans biofilm cells and their planktonic counterparts. RESULTS: The eight genes tested in this study are ranked according to their expression stability (from most stable to least stable) as follows: ACT1 (β-actin)/PMA1 (adenosine triphosphatase), RIP (ubiquinol cytochrome-c reductase complex component), RPP2B (cytosolic ribosomal acidic protein P2B), LSC2 (succinyl-CoA synthetase β-subunit fragment), IMH3 (inosine-5'-monophosphate dehydrogenase fragment), CPA1 (carbamoyl-phosphate synthethase small subunit) and GAPDH (glyceraldehyde-3-phosphate dehydrogenase). Our data indicate that five genes are necessary for accurate and reliable normalization of gene expression data in C. albicans biofilms. Using different normalization strategies, we found a significant upregulation of the ALS1 gene and downregulation of the ALS3 gene in C. albicans biofilms grown on silicone disks in a continous flow system, the CDC reactor (Centre for Disease Control), for 24 hours. CONCLUSION: In conclusion, we recommend the use of the geometric mean of the relative expression values from the five housekeeping genes (ACT1, PMA1, RIP, RPP2B and LSC2) for normalization, when analysing differences in gene expression levels between C. albicans biofilm cells and planktonic cells. Validation of the normalization strategies described above showed that the ALS1 gene is overexpressed and the ALS3 gene is underexpressed in C. albicans biofilms grown on silicone in the CDC reactor for 24 hours

Tracking the best reference genes for RT-qPCR data normalization in filamentous fungi

Background: A critical step in the RT-qPCR workflow for studying gene expression is data normalization, one of the strategies being the use of reference genes. This study aimed to identify and validate a selection of reference genes for relative quantification in Talaromyces versatilis, a relevant industrial filamentous fungus. Beyond T. versatilis, this study also aimed to propose reference genes that are applicable more widely for RT-qPCR data normalization in filamentous fungi. [br/]Results: A selection of stable, potential reference genes was carried out in silico from RNA-seq based transcriptomic data obtained from T. versatilis. A dozen functionally unrelated candidate genes were analysed by RT-qPCR assays over more than 30 relevant culture conditions. By using geNorm, we showed that most of these candidate genes had stable transcript levels in most of the conditions, from growth environments to conidial germination. The overall robustness of these genes was explored further by showing that any combination of 3 of them led to minimal normalization bias. To extend the relevance of the study beyond T. versatilis, we challenged their stability together with sixteen other classically used genes such as beta-tubulin or actin, in a representative sample of about 100 RNA-seq datasets. These datasets were obtained from 18 phylogenetically distant filamentous fungi exposed to prevalent experimental conditions. Although this wide analysis demonstrated that each of the chosen genes exhibited sporadic up-or down-regulation, their hierarchical clustering allowed the identification of a promising group of 6 genes, which presented weak expression changes and no tendency to up-or down-regulation over the whole set of conditions. This group included ubcB, sac7, fis1 and sarA genes, as well as TFC1 and UBC6 that were previously validated for their use in S. cerevisiae. [br/]Conclusions: We propose a set of 6 genes that can be used as reference genes in RT-qPCR data normalization in any field of fungal biology. However, we recommend that the uniform transcription of these genes is tested by systematic experimental validation and to use the geometric averaging of at least 3 of the best ones. This will minimize the bias in normalization and will support trustworthy biological conclusions

Identification of stable endogenous reference genes for real-time PCR in the human fetal gonad using an external standard technique

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Identification of stably expressed reference small non-coding RNAs for microRNA quantification in high-grade serous ovarian carcinoma tissues

MicroRNAs (miRNAs) belong to a family of small non‐coding RNAs (sncRNAs) playing important roles in human carcinogenesis. Multiple investigations reported miRNAs aberrantly expressed in several cancers, including high‐grade serous ovarian carcinoma (HGS‐OvCa). Quantitative PCR is widely used in studies investigating miRNA expression and the identification of reliable endogenous controls is crucial for proper data normalization. In this study, we aimed to experimentally identify the most stable reference sncRNAs for normalization of miRNA qPCR expression data in HGS‐OvCa. Eleven putative reference sncRNAs for normalization (U6, SNORD48, miR‐92a‐3p, let‐7a‐5p, SNORD61, SNORD72, SNORD68, miR‐103a‐3p, miR‐423‐3p, miR‐191‐5p, miR‐16‐5p) were analysed on a total of 75 HGS‐OvCa and 30 normal tissues, using a highly specific qPCR. Both the normal tissues considered to initiate HGS‐OvCa malignant transformation, namely ovary and fallopian tube epithelia, were included in our study. Stability of candidate endogenous controls was evaluated using an equivalence test and validated by geNorm and NormFinder algorithms. Combining results from the three different statistical approaches, SNORD48 emerged as stably and equivalently expressed between malignant and normal tissues. Among malignant samples, considering groups based on residual tumour, miR‐191‐5p was identified as the most equivalent sncRNA. On the basis of our results, we support the use of SNORD48 as best reference sncRNA for relative quantification in miRNA expression studies between HGS‐OvCa and normal controls, including the first time both the normal tissues supposed to be HGS‐OvCa progenitors. In addition, we recommend miR‐191‐5p as best reference sncRNA in miRNA expression studies with prognostic intent on HGS‐OvCa tissues

Temperature dependence of the LabPET small-animal PET scanner

INTRODUCTION In quantitative PET imaging it is important to correct for all image-degrading effects, for example detector efficiency variation. Detector efficiency variation depends on the stability of detector efficiency when operating conditions vary within normal limits. As the efficiency of APD-based light detection strongly depends on ambient temperature, temperature-dependent detector efficiency normalization may be needed in APD-based PET scanners. We have investigated the temperature dependence of the LabPET APD-based small-animal PET scanner. MATERIALS AND METHODS First a simulation study was performed to evaluate the effect of different APD temperature coefficients on the temperature dependence of scanner sensitivity. Five experiments were also performed. First the immediate effect of temperature changes on scanner sensitivity was evaluated. Second, the effect of temperature changes that have stabilized for a few hours was investigated. In a third experiment the axial sensitivity profile was acquired at 21 degrees C and 24 degrees C. Next, two acquisitions of the NEMA image quality phantom (at 21 degrees C and 23 degrees C) were performed and absolute quantification was done based on normalization scans acquired at the correct and incorrect temperature. Finally, the feasibility of maintaining a constant room temperature and the stability of the scanner sensitivity under constant room temperature was evaluated. RESULTS Simulations showed that the relation between temperature-dependent APD gain changes and scanner sensitivity is quite complex. A temperature deviation leading to a 1 % change in APD gain corresponds to a much larger change in scanner sensitivity due to the shape of the energy histogram. In the first and second experiment a strong correlation between temperature and scanner sensitivity was observed. Changes of 2.24 kcps/MBq and 1.64 kcps/MBq per degrees C were seen for immediate and stabilized temperature changes respectively. The NEMA axial sensitivity profile also showed a decrease in sensitivity at higher temperature. The quantification experiment showed that a larger quantification error (up to 13%) results when a normalization scan acquired at the incorrect temperature is used. In the last experiment, temperature variability was 0.19 degrees C and counts varied by 10.2 Mcts (1.33%). CONCLUSION The sensitivity of the LabPET small-animal PET scanner strongly depends on room temperature. Therefore, room temperature should be kept as stable as possible and temperature-dependent detector efficiency normalization should be used. However, with constant room temperature excellent scanner stability is observed. Temperature should be kept constant within 0.5 degrees C and weekly normalization scans are recommended

Reference loci for RT-qPCR analysis of differentiating human embryonic stem cells

Background: Selecting stably expressed reference genes is essential for proper reverse transcription quantitative polymerase chain reaction gene expression analysis. However, this choice is not always straightforward. In the case of differentiating human embryonic stem (hES) cells, differentiation itself introduces changes whereby reference gene stability may be influenced. Results: In this study, we evaluated the stability of various references during retinoic acid-induced (2 microM) differentiation of hES cells. Out of 12 candidate references, beta-2-microglobulin, ribosomal protein L13A and Alu repeats are found to be the most stable for this experimental set-up. Conclusions: Our results show that some of the commonly used reference genes are actually not amongst the most stable loci during hES cell differentiation promoted by retinoic acid. Moreover, a novel normalization strategy based on expressed Alu repeats is validated for use in hES cell experiments

A novel and universal method for microRNA RT-qPCR data normalization

Gene expression analysis of microRNA molecules is becoming increasingly important. In this study we assess the use of the mean expression value of all expressed microRNAs in a given sample as a normalization factor for microRNA real-time quantitative PCR data and compare its performance to the currently adopted approach. We demonstrate that the mean expression value outperforms the current normalization strategy in terms of better reduction of technical variation and more accurate appreciation of biological changes