Selecting control genes for RT-QPCR using public microarray data

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable

RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization

Background RT-qPCR is a sensitive and increasingly used method for gene expression quantification. To normalize RT-qPCR measurements between samples, most laboratories use endogenous reference genes as internal controls. There is increasing evidence, however, that the expression of commonly used reference genes can vary significantly in certain contexts. Results Using the Genevestigator database of normalized and well-annotated microarray experiments, we describe the expression stability characteristics of the transciptomes of several organisms. The results show that a) no genes are universally stable, b) most commonly used reference genes yield very high transcript abundances as compared to the entire transcriptome, and c) for each biological context a subset of stable genes exists that has smaller variance than commonly used reference genes or genes that were selected for their stability across all conditions. Conclusion We therefore propose the normalization of RT-qPCR data using reference genes that are specifically chosen for the conditions under study. RefGenes is a community tool developed for that purpose. Validation RT-qPCR experiments across several organisms showed that the candidates proposed by RefGenes generally outperformed commonly used reference genes. RefGenes is available within Genevestigator at http://www.genevestigator.com

Elucidation of the RamA Regulon in Klebsiella pneumoniae Reveals a Role in LPS Regulation

Klebsiella pneumoniae is a significant human pathogen, in part due to high rates of multidrug resistance. RamA is an intrinsic regulator in K. pneumoniae established to be important for the bacterial response to antimicrobial challenge; however, little is known about its possible wider regulatory role in this organism during infection. In this work, we demonstrate that RamA is a global transcriptional regulator that significantly perturbs the transcriptional landscape of K. pneumoniae, resulting in altered microbe-drug or microbe-host response. This is largely due to the direct regulation of 68 genes associated with a myriad of cellular functions. Importantly, RamA directly binds and activates the lpxC, lpxL-2 and lpxO genes associated with lipid A biosynthesis, thus resulting in modifications within the lipid A moiety of the lipopolysaccharide. RamA-mediated alterations decrease susceptibility to colistin E, polymyxin B and human cationic antimicrobial peptide LL-37. Increased RamA levels reduce K. pneumoniae adhesion and uptake into macrophages, which is supported by in vivo infection studies, that demonstrate increased systemic dissemination of ramA overexpressing K. pneumoniae. These data establish that RamA-mediated regulation directly perturbs microbial surface properties, including lipid A biosynthesis, which facilitate evasion from the innate host response. This highlights RamA as a global regulator that confers pathoadaptive phenotypes with implications for our understanding of the pathogenesis of Enterobacter, Salmonella and Citrobacter spp. that express orthologous RamA proteins

Role of differentially expressed microRNA-139-5p in the regulation of phenotypic internal anal sphincter smooth muscle tone.

The present study focused on the role of microRNA-139-5p (miRNA-139-5p) in the regulation of basal tone in internal anal sphincter (IAS). Applying genome-wide miRNA microarrays on the phenotypically distinct smooth muscle cells (SMCs) within the rat anorectrum, we identified miRNA-139-5p as differentially expressed RNA repressor with highest expression in the purely phasic smooth muscle of anococcygeus (ASM) vs. the truly tonic smooth muscle of IAS. This pattern of miRNA-139-5p expression, previously shown to target ROCK2, was validated by target prediction using ingenuity pathway (IPA) and by qPCR analyses. Immunoblotting, immunocytochemistry (ICC), and functional assays using IAS tissues and cells subjected to overexpression/knockdown of miRNA-139-5p confirmed the inverse relationship between miRNA-139-5p and ROCK2 expressions/IAS tone. Overexpression of miRNA-139-5p caused a decrease, while knockdown by anti-miRNA-139-5p caused an increase in the IAS tone; these tissue contractile responses were confirmed by single-cell contraction using magnetic twisting cytometry (MTC). These findings suggest miRNA-139-5p is capable of significantly influencing the phenotypic tonicity in smooth muscle via ROCK2: a lack of tone in ASM may be associated with the suppression of ROCK2 by high expression of miRNA-139-5p, whereas basal IAS tone may be associated with the persistence of ROCK2 due to low expression of miRNA-139-5p

Identification of new reference genes for the normalisation of canine osteoarthritic joint tissue transcripts from microarray data

<p>Abstract</p> <p>Background</p> <p>Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RT-qPCR) is the most accurate measure of gene expression in biological systems. The comparison of different samples requires the transformation of data through a process called normalisation. Reference or housekeeping genes are candidate genes which are selected on the basis of constitutive expression across samples, and allow the quantification of changes in gene expression. At present, no reference gene has been identified for any organism which is universally optimal for use across different tissue types or disease situations. We used microarray data to identify new reference genes generated from total RNA isolated from normal and osteoarthritic canine articular tissues (bone, ligament, cartilage, synovium and fat). RT-qPCR assays were designed and applied to each different articular tissue. Reference gene expression stability and ranking was compared using three different mathematical algorithms.</p> <p>Results</p> <p>Twelve new potential reference genes were identified from microarray data. One gene (mitochondrial ribosomal protein S7 [<it>MRPS7</it>]) was stably expressed in all five of the articular tissues evaluated. One gene HIRA interacting protein 5 isoform 2 [<it>HIRP5</it>]) was stably expressed in four of the tissues evaluated. A commonly used reference gene glyceraldehyde-3-phosphate dehydrogenase (<it>GAPDH</it>) was not stably expressed in any of the tissues evaluated. Most consistent agreement between rank ordering of reference genes was observed between <it>Bestkeeper©</it> and geNorm, although each method tended to agree on the identity of the most stably expressed genes and the least stably expressed genes for each tissue. New reference genes identified using microarray data normalised in a conventional manner were more stable than those identified by microarray data normalised by using a real-time RT-qPCR methodology.</p> <p>Conclusion</p> <p>Microarray data normalised by a conventional manner can be filtered using a simple stepwise procedure to identify new reference genes, some of which will demonstrate good measures of stability. Mitochondrial ribosomal protein S7 is a new reference gene worthy of investigation in other canine tissues and diseases. Different methods of reference gene stability assessment will generally agree on the most and least stably expressed genes, when co-regulation is not present.</p

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes.

With defined culture protocol, human embryonic stem cells (hESCs) are able to generate cardiomyocytes in vitro, therefore providing a great model for human heart development, and holding great potential for cardiac disease therapies. In this study, we successfully generated a highly pure population of human cardiomyocytes (hCMs) (&gt;95% cTnT(+)) from hESC line, which enabled us to identify and characterize an hCM-specific signature, at both the gene expression and DNA methylation levels. Gene functional association network and gene-disease network analyses of these hCM-enriched genes provide new insights into the mechanisms of hCM transcriptional regulation, and stand as an informative and rich resource for investigating cardiac gene functions and disease mechanisms. Moreover, we show that cardiac-structural genes and cardiac-transcription factors have distinct epigenetic mechanisms to regulate their gene expression, providing a better understanding of how the epigenetic machinery coordinates to regulate gene expression in different cell types

A Pipeline to Determine RT-QPCR Control Genes for Evolutionary Studies: Application to Primate Gene Expression across Multiple Tissues

Because many species-specific phenotypic differences are assumed to be caused by differential regulation of gene expression, many recent investigations have focused on measuring transcript abundance. Despite the availability of high-throughput platforms, quantitative real-time polymerase chain reaction (RT-QPCR) is often the method of choice because of its low cost and wider dynamic range. However, the accuracy of this technique heavily relies on the use of multiple valid control genes for normalization. We created a pipeline for choosing genes potentially useful as RT-QPCR control genes for measuring expression between human and chimpanzee samples across multiple tissues, using published microarrays and a measure of tissue-specificity. We identified 13 genes from the pipeline and from commonly used control genes: ACTB, USP49, ARGHGEF2, GSK3A, TBP, SDHA, EIF2B2, GPDH, YWHAZ, HPTR1, RPL13A, HMBS, and EEF2. We then tested these candidate genes and validated their expression stability across species. We established the rank order of the most preferable set of genes for single and combined tissues. Our results suggest that for at least three tissues (cerebral cortex, liver, and skeletal muscle), EIF2B2, EEF2, HMBS, and SDHA are useful genes for normalizing human and chimpanzee expression using RT-QPCR. Interestingly, other commonly used control genes, including TBP, GAPDH, and, especially ACTB do not perform as well. This pipeline could be easily adapted to other species for which expression data exist, providing taxonomically appropriate control genes for comparisons of gene expression among species

Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis

The accuracy of quantitative real-time PCR (qRT-PCR) is highly dependent on reliable reference gene(s). Some housekeeping genes which are commonly used for normalization are widely recognized as inappropriate in many experimental conditions. This study aimed to identify reference genes for clinical studies through microarray meta-analysis of human clinical samples.After uniform data preprocessing and data quality control, 4,804 Affymetrix HU-133A arrays performed by clinical samples were classified into four physiological states with 13 organ/tissue types. We identified a list of reference genes for each organ/tissue types which exhibited stable expression across physiological states. Furthermore, 102 genes identified as reference gene candidates in multiple organ/tissue types were selected for further analysis. These genes have been frequently identified as housekeeping genes in previous studies, and approximately 71% of them fall into Gene Expression (GO:0010467) category in Gene Ontology.Based on microarray meta-analysis of human clinical sample arrays, we identified sets of reference gene candidates for various organ/tissue types and then examined the functions of these genes. Additionally, we found that many of the reference genes are functionally related to transcription, RNA processing and translation. According to our results, researchers could select single or multiple reference gene(s) for normalization of qRT-PCR in clinical studies

Impact of Agriculture on the Selection of Insecticide Resistance in the Malaria Vector Anopheles gambiae : A Multigenerational Study in Controlled Conditions.

Resistance of mosquitoes to insecticides is mainly attributed to their adaptation to vector control interventions. Although pesticides used in agriculture have been frequently mentioned as an additional force driving the selection of resistance, only a few studies were dedicated to validate this hypothesis and characterise the underlying mechanisms. While insecticide resistance is rising dramatically in Africa, deciphering how agriculture affects resistance is crucial for improving resistance management strategies. In this context, the multigenerational effect of agricultural pollutants on the selection of insecticide resistance was examined in Anopheles gambiae. An urban Tanzanian An. gambiae population displaying a low resistance level was used as a parental strain for a selection experiment across 20 generations. At each generation larvae were selected with a mixture containing pesticides and herbicides classically used in agriculture in Africa. The resistance levels of adults to deltamethrin, DDT and bendiocarb were compared between the selected and non-selected strains across the selection process together with the frequency of kdr mutations. A microarray approach was used for pinpointing transcription level variations selected by the agricultural pesticide mixture at the adult stage. A gradual increase of adult resistance to all insecticides was observed across the selection process. The frequency of the L1014S kdr mutation rose from 1.6% to 12.5% after 20 generations of selection. Microarray analysis identified 90 transcripts over-transcribed in the selected strain as compared to the parental and the non-selected strains. Genes encoding cuticle proteins, detoxification enzymes, proteins linked to neurotransmitter activity and transcription regulators were mainly affected. RT-qPCR transcription profiling of candidate genes across multiple generations supported their link with insecticide resistance. This study confirms the potency of agriculture in selecting for insecticide resistance in malaria vectors. We demonstrated that the recurrent exposure of larvae to agricultural pollutants can select for resistance mechanisms to vector control insecticides at the adult stage. Our data suggest that in addition to selected target-site resistance mutations, agricultural pollutants may also favor cuticle, metabolic and synaptic transmission-based resistance mechanisms. These results emphasize the need for integrated resistance management strategies taking into account agriculture activities