RDML: structured language and reporting guidelines for real-time quantitative PCR data

Improved molecular diagnostics of idiopathic short stature and allied disorders: quantitative polymerase chain reaction-based copy number profiling of SHOX and pseudoautosomal region 1

CONTEXT

Short stature has an incidence of three in 100 in children. Reliable molecular genetic testing may be crucial in the context of beneficial disease management. Deletions spanning or surrounding the SHOX gene account for a significant proportion of patients with idiopathic short stature (ISS) and allied disorders, such as Leri-Weill dyschondrosteosis.

OBJECTIVE

Several shortcomings of current strategies for copy number profiling of the SHOX region prompted us to develop an improved test for molecular diagnostics of the SHOX region.

DESIGN AND RESULTS

We introduced a quantitative PCR (qPCR)-based copy number profiling test, consisting of 11 amplicons targeting clinically relevant regions, i.e. the SHOX gene and regulatory regions. To ensure an optimal sensitivity and specificity, this test was validated in 32 controls and 18 probands with previously identified copy number changes. In addition, 152 probands with SHOX-associated phenotypes were screened, revealing 10 novel copy number changes.

CONCLUSION

This highly validated qPCR test supersedes other approaches for copy number screening of the SHOX region in terms of reliability, accuracy, and cost efficiency. In addition, another strong point is the fact that it can be easily implemented in any standard equipped molecular laboratory. Our qPCR-based test is highly recommended for molecular diagnostics of idiopathic short stature and allied disorders.

Transcribed-ultra conserved region expression profiling from low-input total RNA

Background

Ultra Conserved Regions (UCRs) are a class of 481 noncoding sequences located in both intra- and inter-genic regions of the genome. The recent findings that they are significantly altered in adult chronic lymphocytic leukemias, carcinomas, and pediatric neuroblastomas lead to the hypothesis that UCRs may play a role in tumorigenesis.

Results

We present a novel application of Ribo-SPIA™ isothermal linear amplification of minute RNA quantities for quantifying Transcribed-UCR (T-UCR) expression by quantitative PCR. Direct comparison of non-amplified with amplified cDNA in two neuroblastoma cell lines showed that the amplification approach increases sensitivity and repeatability in T-UCR quantification. It is noteworthy that the Ribo-SPIA™ step allowed us to analyze all 481 T-UCRs by using 150 ng of RNA, while introducing a minimal bias and preserving the magnitude of relative expression. Only the less abundant T-UCRs have high intra-assay variability, consistently with the Poisson distribution statistics and stochastic effects on PCR repeatability.

Conclusions

We demonstrated that the quantification procedure shown here is an accurate and reliable technique for genome-wide non coding gene (i.e., UCRs) profiling using small amounts of RNA. This issue is particularly important because studies of transcription regulation are increasingly conducted in small homogeneous samples, such as laser capture microdissected or sorted cell populations.

The most likely time and place of introduction of BTV8 into Belgian ruminants

BACKGROUND

In northern Europe, bluetongue (BT) caused by the BT virus (BTV), serotype 8, was first notified in August 2006 and numerous ruminant herds were affected in 2007 and 2008. However, the origin and the time and place of the original introduction have not yet been determined.

METHODS AND PRINCIPAL FINDINGS

Four retrospective epidemiological surveys have been performed to enable determination of the initial spatiotemporal occurrence of this emerging disease in southern Belgium: investigations of the first recorded outbreaks near to the disease epicenter; a large anonymous, random postal survey of cattle herds and sheep flocks; a random historical milk tank survey of samples tested with an indirect ELISA and a follow-up survey of non-specific health indicators. The original introduction of BTV into the region probably occurred during spring 2006 near to the National Park of Hautes Fagnes and Eifel when Culicoides become active.

CONCLUSIONS/SIGNIFICANCE

The determination of the most likely time and place of introduction of BTV8 into a country is of paramount importance to enhance awareness and understanding and, to improve modeling of vector-borne emerging infectious diseases.

External oligonucleotide standards enable cross laboratory comparison and exchange of real-time quantitative PCR data

The quantitative polymerase chain reaction (qPCR) is widely utilized for gene expression analysis. However, the lack of robust strategies for cross laboratory data comparison hinders the ability to collaborate or perform large multicentre studies conducted at different sites. In this study we introduced and validated a workflow that employs universally applicable, quantifiable external oligonucleotide standards to address this question. Using the proposed standards and data-analysis procedure, we obtained a perfect concordance between expression values from eight different genes in 366 patient samples measured on three different qPCR instruments and matching software, reagents, plates and seals, demonstrating the power of this strategy to detect and correct inter-run variation and to enable exchange of data between different laboratories, even when not using the same qPCR platform.

Transcribed-Ultra Conserved Region expression is associated with outcome in high-risk neuroblastoma

Background

Neuroblastoma is the most common, pediatric, extra-cranial, malignant solid tumor. Despite multimodal therapeutic protocols, outcome for children with a high-risk clinical phenotype remains poor, with long-term survival still less than 40%. Hereby, we evaluated the potential of non-coding RNA expression to predict outcome in high-risk, stage 4 neuroblastoma.

Methods

We analyzed expression of 481 Ultra Conserved Regions (UCRs) by reverse transcription-quantitative real-time PCR and of 723 microRNAs by microarrays in 34 high-risk, stage 4 neuroblastoma patients.

Results

First, the comparison of 8 short- versus 12 long-term survivors showed that 54 UCRs were significantly (P < 0.0491) over-expressed in the former group. For 48 Ultra Conserved Region (UCRs) the expression levels above the cut-off values defined by ROC curves were strongly associated with good-outcome (OS: 0.0001 <P < 0.0185, EFS: 0.0001 <P < 0.0491). Then we tested the Transcribed-UCR (T-UCR) threshold risk-prediction model on an independent cohort of 14 patients. The expression profile of 28 T-UCRs was significantly associated to prognosis and at least 15 up-regulated T-UCRs are needed to discriminate (P < 0.0001) short- from long-survivors at the highest sensitivity and specificity (94.12%). We also identified a signature of 13 microRNAs differently expressed between long- and short-surviving patients. The comparative analysis of the two classes of non-coding RNAs disclosed that 9 T-UCRs display their expression level that are inversely correlated with expression of 5 complementary microRNAs of the signature, indicating a negative regulation of T-UCRs by direct interaction with microRNAs. Moreover, 4 microRNAs down-regulated in tumors of long-survivors target 3 genes implicated in neuronal differentiation, that are known to be over-expressed in low-risk tumors.

Conclusions

Our pilot study suggests that a deregulation of the microRNA/T-UCR network may play an important role in the pathogenesis of neuroblastoma. After further validation on a larger independent set of samples, such findings may be applied as the first T-UCR prognostic signature for high-risk neuroblastoma patients.

How to do successful gene expression analysis using real-time PCR

Reverse transcription quantitative PCR (RT-qPCR) is considered today as the gold standard for accurate, sensitive and fast measurement of gene expression. Unfortunately, what many users fail to appreciate is that numerous critical issues in the workflow need to be addressed before biologically meaningful and trustworthy conclusions can be drawn. Here, we review the entire workflow from the planning and preparation phase, over the actual real-time PCR cycling experiments to data-analysis and reporting steps. This process can be captured with the appropriate acronym PCR: plan/prepare, cycle and report. The key message is that quality assurance and quality control are essential throughout the entire RT-qPCR workflow; from living cells, over extraction of nucleic acids, storage, various enzymatic steps such as DNase treatment, reverse transcription and PCR amplification, to data-analysis and finally reporting.

QPCR: Application for real-time PCR data management and analysis

Background

Since its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. Its high sensitivity, large dynamic range, and accuracy led to the development of numerous applications with an increasing number of samples to be analyzed. Data analysis consists of a number of steps, which have to be carried out in several different applications. Currently, no single tool is available which incorporates storage, management, and multiple methods covering the complete analysis pipeline.

Results

QPCR is a versatile web-based Java application that allows to store, manage, and analyze data from relative quantification qPCR experiments. It comprises a parser to import generated data from qPCR instruments and includes a variety of analysis methods to calculate cycle-threshold and amplification efficiency values. The analysis pipeline includes technical and biological replicate handling, incorporation of sample or gene specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Moreover, the application supports assessment of error propagation throughout all analysis steps and allows conducting statistical tests on biological replicates. Results can be visualized in customizable charts and exported for further investigation.

Conclusion

We have developed a web-based system designed to enhance and facilitate the analysis of qPCR experiments. It covers the complete analysis workflow combining parsing, analysis, and generation of charts into one single application. The system is freely available at

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

The mean expression value: a new method for accurate and reliable normalization of microRNA expression data from RT-qPCR experiments.

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.