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

qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data

Although quantitative PCR (qPCR) is becoming the method of choice for expression profiling of selected genes, accurate and straightforward processing of the raw measurements remains a major hurdle. Here we outline advanced and universally applicable models for relative quantification and inter-run calibration with proper error propagation along the entire calculation track. These models and algorithms are implemented in qBase, a free program for the management and automated analysis of qPCR data

Positional gene enrichment analysis of gene sets for high-resolution identification of overrepresented chromosomal regions

The search for feature enrichment is a widely used method to characterize a set of genes. While several tools have been designed for nominal features such as Gene Ontology annotations or KEGG Pathways, very little has been proposed to tackle numerical features such as the chromosomal positions of genes. For instance, microarray studies typically generate gene lists that are differentially expressed in the sample subgroups under investigation, and when studying diseases caused by genome alterations, it is of great interest to delineate the chromosomal regions that are significantly enriched in these lists. In this article, we present a positional gene enrichment analysis method (PGE) for the identification of chromosomal regions that are significantly enriched in a given set of genes. The strength of our method relies on an original query optimization approach that allows to virtually consider all the possible chromosomal regions for enrichment, and on the multiple testing correction which discriminates truly enriched regions versus those that can occur by chance. We have developed a Web tool implementing this method applied to the human genome (http://www.esat.kuleuven.be/~bioiuser/pge). We validated PGE on published lists of differentially expressed genes. These analyses showed significant overrepresentation of known aberrant chromosomal regions

RTPrimerDB: the real-time PCR primer and probe database, major update 2006

The RTPrimerDB () project provides a freely accessible data retrieval system and an in silico assay evaluation pipeline for real-time quantitative PCR assays. Over the last year the number of user submitted assays has grown to 3500. Data conveyance from Entrez Gene by establishing an assay-to-gene relationship enables the addition of new primer assays for one of the 1.5 million different genes from 2300 species stored in the system. Easy access to the primer and probe data is possible by using multiple search criteria. Assay reports contain gene information, assay details (such as oligonucleotide sequences, detection chemistry and reaction conditions), publication information, users' experimental evaluation feedback and submitter's contact details. Gene expression assays are extended with a scalable assay viewer that provides detailed information on the alignment of primer and probe sequences on the known transcript variants of a gene, along with Single Nucleotide Polymorphisms (SNP) positions and peptide domain information. Furthermore, an mfold module is implemented to predict the secondary structure of the amplicon sequence, as this has been reported to impact the efficiency of the PCR. RTPrimerDB is also extended with an in silico analysis pipeline to streamline the evaluation of custom designed primer and probe sequences prior to ordering and experimental evaluation. In a secured environment, the pipeline performs automated BLAST specificity searches, mfold secondary structure prediction, SNP or plain sequence error identification, and graphical visualization of the aligned primer and probe sequences on the target gene

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

BACKGROUND: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. RESULTS: We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. CONCLUSIONS: The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences

Quantitative Real Time Polymerase Chain Reaction for measurement of human Interleukin – 5 receptor alpha spliced isoforms mRNA

BACKGROUND: Expression of human Interleukin-5 receptor alpha (hIL-5Rα) is controlled by alternative splicing, which generates two different transcripts encoding a membrane-anchored and a soluble form of the receptor, respectively. Although the study of the expression and regulation of hIL-5Rα is of crucial importance in the field of immunological processing, methods and techniques until now described lack sufficient sensitivity for detection of small differences in the expression of these isoforms. The aim of this study was to develop a reliable and sensitive real-time quantitative PCR assay to analyse the expression level of each isoform. METHODS: For the quantitative real-time PCR assay, two standard curves specific for each splice variant were constructed. PCR amplifications were performed on CDNA from peripheral blood, eosinophilic chronic rhinosinusitis and normal nasal tissue using a common forward and two specific reverse primers, in combination with SYBR Green I as the detection format. RESULTS AND CONCLUSION: We have developed an accurate and reliable assay for quantification of interleukin-5 receptor alpha mRNA isoforms over a broad dynamic range of input molecules. Importantly, excess of one isoform did not influence accurate quantification of the other isoform. Quantification of hIL-5Rα variants in human samples demonstrated an overexpression of both membrane-anchored and soluble encoding variants in eosinophilic chronic rhinosinusitis tissue and peripheral blood in patients with eosinophilic chronic rhinosinusitis compared to healthy subjects. The implementation of this assay will allow a better understanding of the regulatory mechanisms of the hIL-5Rα gene and hence its role in the pathogenesis of chronic inflammatory diseases

Measurable impact of RNA quality on gene expression results from quantitative PCR

Compromised RNA quality is suggested to lead to unreliable results in gene expression studies. Therefore, assessment of RNA integrity and purity is deemed essential prior to including samples in the analytical pipeline. This may be of particular importance when diagnostic, prognostic or therapeutic conclusions depend on such analyses. In this study, the comparative value of six RNA quality parameters was determined using a large panel of 740 primary tumour samples for which real-time quantitative PCR gene expression results were available. The tested parameters comprise of microfluidic capillary electrophoresis based 18S/28S rRNA ratio and RNA Quality Index value, HPRT1 5′–3′ difference in quantification cycle (Cq) and HPRT1 3′ Cq value based on a 5′/3′ ratio mRNA integrity assay, the Cq value of expressed Alu repeat sequences and a normalization factor based on the mean expression level of four reference genes. Upon establishment of an innovative analytical framework to assess impact of RNA quality, we observed a measurable impact of RNA quality on the variation of the reference genes, on the significance of differential expression of prognostic marker genes between two cancer patient risk groups, and on risk classification performance using a multigene signature. This study forms the basis for further rational assessment of reverse transcription quantitative PCR based results in relation to RNA quality

methBLAST and methPrimerDB: web-tools for PCR based methylation analysis

BACKGROUND: DNA methylation plays an important role in development and tumorigenesis by epigenetic modification and silencing of critical genes. The development of PCR-based methylation assays on bisulphite modified DNA heralded a breakthrough in speed and sensitivity for gene methylation analysis. Despite this technological advancement, these approaches require a cumbersome gene by gene primer design and experimental validation. Bisulphite DNA modification results in sequence alterations (all unmethylated cytosines are converted into uracils) and a general sequence complexity reduction as cytosines become underrepresented. Consequently, standard BLAST sequence homology searches cannot be applied to search for specific methylation primers. RESULTS: To address this problem we developed methBLAST, a sequence similarity search program, based on the original BLAST algorithm but querying in silico bisulphite modified genome sequences to evaluate oligonucleotide sequence similarities. Apart from the primer specificity analysis tool, we have also developed a public database termed methPrimerDB for the storage and retrieval of validated PCR based methylation assays. The web interface allows free public access to perform methBLAST searches or database queries and to submit user based information. Database records can be searched by gene symbol, nucleotide sequence, analytical method used, Entrez Gene or methPrimerDB identifier, and submitter's name. Each record contains a link to Entrez Gene and PubMed to retrieve additional information on the gene, its genomic context and the article in which the methylation assay was described. To assure and maintain data integrity and accuracy, the database is linked to other reference databases. Currently, the database contains primer records for the most popular PCR-based methylation analysis methods to study human, mouse and rat epigenetic modifications. methPrimerDB and methBLAST are available at and . CONCLUSION: We have developed two integrated and freely available web-tools for PCR based methylation analysis. methBLAST allows in silico assessment of primer specificity in PCR based methylation assays that can be stored in the methPrimerDB database, which provides a search portal for validated methylation assays

Combined subtractive cDNA cloning and array CGH: an efficient approach for identification of overexpressed genes in DNA amplicons

BACKGROUND: Activation of proto-oncogenes by DNA amplification is an important mechanism in the development and maintenance of cancer cells. Until recently, identification of the targeted genes relied on labour intensive and time consuming positional cloning methods. In this study, we outline a straightforward and efficient strategy for fast and comprehensive cloning of amplified and overexpressed genes. RESULTS: As a proof of principle, we analyzed neuroblastoma cell line IMR-32, with at least two amplification sites along the short arm of chromosome 2. In a first step, overexpressed cDNA clones were isolated using a PCR based subtractive cloning method. Subsequent deposition of these clones on a custom microarray and hybridization with IMR-32 DNA, resulted in the identification of clones that were overexpressed due to gene amplification. Using this approach, amplification of all previously reported amplified genes in this cell line was detected. Furthermore, four additional clones were found to be amplified, including the TEM8 gene on 2p13.3, two anonymous transcripts, and a fusion transcript, resulting from 2p13.3 and 2p24.3 fused sequences. CONCLUSIONS: The combinatorial strategy of subtractive cDNA cloning and array CGH analysis allows comprehensive amplicon dissection, which opens perspectives for improved identification of hitherto unknown targeted oncogenes in cancer cells

The emerging molecular pathogenesis of neuroblastoma: implications for improved risk assessment and targeted therapy

Neuroblastoma is one of the most common solid tumors of childhood, arising from immature sympathetic nervous system cells. The clinical course of patients with neuroblastoma is highly variable, ranging from spontaneous regression to widespread metastatic disease. Although the outcome for children with cancer has improved considerably during the past decades, the prognosis of children with aggressive neuroblastoma remains dismal. The clinical heterogeneity of neuroblastoma mirrors the biological and genetic heterogeneity of these tumors. Ploidy and MYCN amplification have been used as genetic markers for risk stratification and therapeutic decision making, and, more recently, gene expression profiling and genome-wide DNA copy number analysis have come into the picture as sensitive and specific tools for assessing prognosis. The applica tion of new genetic tools also led to the discovery of an important familial neuroblastoma cancer gene, ALK, which is mutated in approximately 8% of sporadic tumors, and genome-wide association studies have unveiled loci with risk alleles for neuroblastoma development. For some of the genomic regions that are deleted in some neuroblastomas, on 1p, 3p and 11q, candidate tumor suppressor genes have been identified. In addition, evidence has emerged for the contribution of epigenetic disturbances in neuroblastoma oncogenesis. As in other cancer entities, altered microRNA expression is also being recognized as an important player in neuroblastoma. The recent successes in unraveling the genetic basis of neuroblastoma are now opening opportunities for development of targeted therapies