Reference gene selection in human periodontal ligament cells

Background: Real-time quantitative PCR (qPCR) is a highly sensitive and specific method which is used extensively for determining gene expression profiles in a variety of cell and tissue types. In order to obtain accurate and reliable gene expression quantification, qPCR data are generally normalised against so-called reference or housekeeping genes. Ideally, reference genes should have abundant and stable RNA transcriptomes under the experimental conditions employed. However, reference genes are often selected rather arbitrarily and indeed some have been shown to have variable expression in a variety of in vitro experimental conditions.
Objective: The objective of the current study was to investigate reference gene expression in human periodontal ligament (PDL) cells in response to treatment with lipopolysaccharide (LPS).
Method: Primary human PDL cells were grown in Dulbecco’s Modified Eagle Medium with L-glutamine supplemented with 10% fetal bovine serum, 100UI/ml penicillin and 100µg/ml streptomycin. RNA was isolated using the RNeasy Mini Kit (Qiagen) and reverse transcribed using the QuantiTect Reverse Transcription Kit (Qiagen). The expression of a total of 19 reference genes was studied in the presence and absence of LPS treatment using the Roche Reference Gene Panel. Data were analysed using NormFinder and Bestkeeper validation programs.
Results: Treatment of human PDL cells with LPS resulted in changes in expression of several commonly used reference genes, including GAPDH. On the other hand the reference genes β-actin, G6PDH and 18S were identified as stable genes following LPS treatment.
Conclusion: Many of the reference genes studied were robust to LPS treatment (up to 100 ng/ml). However several commonly employed reference genes, including GAPDH varied with LPS treatment, suggesting they would not be ideal candidates for normalisation in qPCR gene expression studies.

Reference Gene Selection for Gene Expression Analysis of Oocytes Collected from Dairy Cattle and Buffaloes during Winter and Summer

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

qPCR counts of mRNA for hepatic reference gene selection in juvenile female Atlantic salmon from perturbation experiments under artificial temperature conditions

The dataset contains raw data (quantification cycle) for a study which determined the most suitable hepatic reference genes for normalisation of qPCR data orginating from juvenile Atlantic salmon (14 days) exposed to 14 and 22 degrees C. These results will be useful for anyone wanting to study the effects of climate change/elevated temperature on reproductive physiology of fish (and perhaphs other vertebrates).

qPCR counts of mRNA for hepatic reference gene selection in adult female Atlantic salmon from perturbation experiments under artificial temperature conditions

The dataset contains raw data (quantification cycle) for a study which determined the most suitable hepatic reference genes for normalisation of qPCR data orginating from adult (entire reproductive season) Atlantic salmon (14 days) exposed to 14 and 22 degrees C. These results will be useful for anyone wanting to study the effects of climate change/elevated temperature on reproductive physiology of fish (and perhaphs other vertebrates). In addition, a target gene (vitellogenin) has normalised using an inappropriate and an 'ideal' reference gene to demonstrate the consequences of using an unstable reference gene for normalisation. For the adult experiment, maiden and repeat adult females were held at the Salmon Enterprises of Tasmania (SALTAS) Wayatinah Hatchery (Tasmania, Australia) at ambient temperature and photoperiod in either 200 (maidens) or 50 (repeats) m3 circular tanks at stocking densities of 12-18, and 24-36 kg m-3 for maidens and repeats, respectively, until transfered to the experimental tanks.

A Toolbox for Quantitative Gene Expression in Varroa destructor : RNA Degradation in Field Samples and Systematic Analysis of Reference Gene Stability

Funding: This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613960 (SMARTBEES) (http://www.smartbees-fp7.eu/) and Veterinary Medicines Directorate, Department for Environment Food & Rural Affairs (Project # VM0517) (https://www.gov.uk/government/organisations/veterinary-medicines-directorate). CHM was supported by a Biosciences Knowledge Transfer Network Biotechnology and Biological Sciences Research Council (KTN-BBSRC CASE) Studentship (BB/L502467/1) (http://www.bbsrc.ac.uk/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We gratefully acknowledge Mr Sebastian Bacz’s expert help and advice with beekeeping.

Guideline to reference gene selection for quantitative real-time PCR

Today, quantitative real-time PCR is the method of choice for rapid and reliable quantification of mRNA transcription. However, for an exact comparison of mRNA transcription in different samples or tissues it is crucial to choose the appropriate reference gene. Recently glyceraldehyde 3-phosphate dehydrogenase and P-actin have been used for that purpose. However, it has been reported that these genes as well as alternatives, like rRNA genes, are unsuitable references, because their transcription is significantly regulated in various experimental settings and variable in different tissues. Therefore, quantitative real-time PCR was used to determine the mRNA transcription profiles of 13 putative reference genes, comparing their transcription in 16 different tissues and in CCRF-HSB-2 cells stimulated with 12-O-tetradecanoylphorbol-13-acetate and ionomycin. Our results show that Classical reference genes are indeed unsuitable, whereas the RNA polymerase II gene was the gene with the most constant expression in different tissues and following stimulation in CCRF-HSB-2 cells. (C) 2003 Elsevier Inc. All rights reserved.

The Renilla luciferase gene as a reference gene for normalization of gene expression in transiently transfected cells

Background: The importance of appropriate normalization controls in quantitative real-time polymerase chain reaction (qPCR) experiments has become more apparent as the number of biological studies using this methodology has increased. In developing a system to study gene expression from transiently transfected plasmids, it became clear that normalization using chromosomally encoded genes is not ideal, at it does not take into account the transfection efficiency and the significantly lower expression levels of the plasmids. We have developed and validated a normalization method for qPCR using a co-transfected plasmid.Results: The best chromosomal gene for normalization in the presence of the transcriptional activators used in this study, cadmium, dexamethasone, forskolin and phorbol-12-myristate 13-acetate was first identified. qPCR data was analyzed using geNorm, Normfinder and BestKeeper. Each software application was found to rank the normalization controls differently with no clear correlation. Including a co-transfected plasmid encoding the Renilla luciferase gene (Rluc) in this analysis showed that its calculated stability was not as good as the optimised chromosomal genes, most likely as a result of the lower expression levels and transfection variability. Finally, we validated these analyses by testing two chromosomal genes (B2M and ActB) and a co-transfected gene (Rluc) under biological conditions. When analyzing co-transfected plasmids, Rluc normalization gave the smallest errors compared to the chromosomal reference genes.Conclusions: Our data demonstrates that transfected Rluc is the most appropriate normalization reference gene for transient transfection qPCR analysis; it significantly reduces the standard deviation within biological experiments as it takes into account the transfection efficiencies and has easily controllable expression levels. This improves reproducibility, data validity and most importantly, enables accurate interpretation of qPCR data. © 2010 Jiwaji et al; licensee BioMed Central Ltd.

Reference gene selection and RNA preservation protocol in the cat flea, Ctenocephalides felis, for gene expression studies

This work was supported by a Knowledge Transfer Network BBSRC Industrial Case (#414 BB/L502467/1) studentship in association Zoetis Inc.

Reference gene selection for gene expression studies in apple.

2011

Validation of β-actin used as endogenous control for gene expression analysis in mechanobiology studies : amendments

We write in response to the letter by Liu et al. [1] commenting on our article, ‘‘Mesenchymal Stem Cells Regulate Angiogenesis According to Their Mechanical Environment’’ [2]. The study by Liu et al. demonstrates that the commonly used endogeneous reference gene (ERG), b-actin, is upregulated by mechanical loading, indicating a potential bias in the determined target gene expression when normalizing to b-actin, such as in our report on unchanged vascular endothelial growth factor (VEGF) and hypoxia-inducible factors (HIF)-1a mRNA levels in mechanically loaded mesenchymal stem cells (MSCs).

Reference genes for quantitative RT-PCR data in gastric tissues and cell lines

AIM: To evaluate the suitability of reference genes in gastric tissue samples and cell lines.METHODS: the suitability of genes ACTB, B2M, GAPDH, RPL29, and 18S rRNA was assessed in 21 matched pairs of neoplastic and adjacent nonneoplastic gastric tissues from patients with gastric adenocarcinoma, 27 normal gastric tissues from patients without cancer, and 4 cell lines using reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR). the ranking of the best single and combination of reference genes was determined by NormFinder, geNorm (TM), BestKeeper, and DataAssist (TM). in addition, GenEx software was used to determine the optimal number of reference genes. To validate the results, the mRNA expression of a target gene, DNMT1, was quantified using the different reference gene combinations suggested by the various software packages for normalization.RESULTS: ACTB was the best reference gene for all gastric tissues, cell lines and all gastric tissues plus cell lines. GAPDH + B2M or ACTB + B2M was the best combination of reference genes for all the gastric tissues. On the other hand, ACTB + B2M was the best combination for all the cell lines tested and was also the best combination for analyses involving all the gastric tissues plus cell lines. According to the GenEx software, 2 or 3 genes were the optimal number of references genes for all the gastric tissues. the relative quantification of DNMT1 showed similar patterns when normalized by each combination of reference genes. the level of expression of DNMT1 in neoplastic, adjacent non-neoplastic and normal gastric tissues did not differ when these samples were normalized using GAPDH + B2M (P = 0.32), ACTB + B2M (P = 0.61), or GAPDH + B2M + ACTB (P = 0.44).CONCLUSION: GAPDH + B2M or ACTB + B2M is the best combination of reference gene for all the gastric tissues, and ACTB + B2M is the best combination for the cell lines tested. (C) 2013 Baishideng Publishing Group Co., Limited. All rights reserved.

sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background
Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.

Results
This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies.

Conclusion
The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Background

Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006), Science 313, 1929–1935] to make successful connections among small molecules, genes, and diseases using genomic signatures.

Results

Here we have built on the principles of the Connectivity Map to present a simpler and more robust method for the construction of reference gene-expression profiles and for the connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with two randomly generated gene signatures and three experimentally derived gene signatures (for HDAC inhibitors, estrogens, and immunosuppressive drugs, respectively). Our testing with this method indicates that it achieves a higher level of specificity and sensitivity and so advances the original method.

Conclusion

The method presented here not only offers more principled statistical procedures for testing connections, but more importantly it provides effective safeguard against false connections at the same time achieving increased sensitivity. With its robust performance, the method has potential use in the drug development pipeline for the early recognition of pharmacological and toxicological properties in chemicals and new drug candidates, and also more broadly in other 'omics sciences.