 qPCR array - page 1 qPCR array - page 2
Introduction - qPCR arrays qPCR arrays are the most
reliable tools for parallel quantitative analysis of gene expression
signatures of a
focused panel of genes. They are available for mRNAs
and microRNAs expression profiling in
96-well, 384-well and
(hopefully soon) in 1536-well formats. The detection chemistry used in
qPCR arrays is either SYBR
Green I (or comparable DNA binding dyes) or optimized probe-based
primer sets (mainly TaqMan
probes or LNA probes).
They can screen the entire panel of expressed microRNA or sub-panels,
e.g. pathway- or disease-focused gene families.
qPCR arrays can also be customized to contain a panel of genes tailored
to your specific research interests.
Why using qPCR arrays?
qPCR array performance
Simple workflow
Simply mix your cDNA template with the appropriate ready-to-use PCR master mix, aliquot equal volumes to each well of the same plate, and then run the real-time PCR cycling program. PCR Arrays are compatible with any block based real-time cycling system => http://cyclers.gene-quantification.info/ Well designed plate layout and multiple
controls on various levels
The PCR Arrays are available in both 96-well, 384-well and 1536-well plates and are used to monitor the expression of 84 up to over 1000 genes related to a disease state or pathway plus multiple reference genes. Multiple controls are also included on each array for genomic DNA contamination, RNA quality, and general PCR performance. Following controls are added to the qPCR array:
Easy-to-use normalisation and expression
profiling data analysis
Data analysis can be done in a simple version on the basis of Excel-based data analysis template, or by the GPR method (see below) or using high complex analysis software tools like Genex (MultiD, Sweden). Data analysis is mainly based on the ΔΔCt method (Livak & Schmittgen, 2001) with normalization of the raw data to either housekeeping genes or an external RNA control. See this nice webinar about real-time PCR data analysis by Prof. Mikael Kubista on "Statistical approaches to gene expression profiling with GenEx 4" The new software versions are available here => http://genex.gene-quantification.info/ qPCR array application papers PCR’s next frontier PCR The workhorse of modern molecular biologyis charging forward using both conventional and digital methods to explore single cells and even single molecules. Nathan Blow reports. NATURE METHODS VOL 4(10) 2007: 869 Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis. Chen Y, Gelfond JA, McManus LM, Shireman PK. Department of Surgery, University of Texas Health Science Center, San Antonio, TX 78229, USA BMC Genomics. 2009 Aug 28;10: 407. BACKGROUND: MicroRNAs
(miRNAs) have critical functions in various
biological processes. MiRNA profiling is an important tool for the
dentification of differentially expressed miRNAs in normal cellular
and disease processes. A technical challenge remains for
high-throughput miRNA expression analysis as the number of miRNAs
continues to increase with in silico prediction and experimental
verification. Our study critically evaluated the performance of a novel
miRNA expression profiling approach, quantitative RT-PCR array
(qPCR-array), compared to miRNA detection with oligonucleotide
microchip (microarray).
RESULTS: High
reproducibility with qPCR-array was demonstrated by
comparing replicate results from the same RNA sample. Pre-amplification
of the miRNA cDNA improved sensitivity of the qPCR-array and increased
the number of detectable miRNAs. Furthermore, the relative expression
levels of miRNAs were maintained after pre-amplification. When the
performance of qPCR-array and microarrays were compared using different
aliquots of the same RNA, a low correlation between the two methods
(r=-0.443) indicated considerable variability between the two assay
platforms. Higher variation between replicates was observed in miRNAs
with low expression in both assays. Finally, a higher false positive
rate of differential miRNA expression was observed using the microarray
compared to the qPCR-array.
CONCLUSION: Our studies
demonstrated high reproducibility of TaqMan
qPCR-array. Comparison between different reverse transcription
reactions and qPCR-arrays performed on different days indicated that
reverse transcription reactions did not introduce significant variation
in the results. The use of cDNA pre-amplification increased the
sensitivity of miRNA detection. Although there was
variability associated with pre-amplification in low abundance
miRNAs, the latter did not involve any systemic bias in the estimation
of miRNA expression. Comparison between microarray and qPCR-array
indicated superior sensitivity and specificity of qPCR-array.
Customized Molecular Phenotyping by Quantitative Gene Expression and Pattern Recognition Analysis Shreeram Akilesh, Daniel J. Shaffer, and Derry Roopenian Genome Res. 2003 13(7): 1719-1727 The Jackson Laboratory, Bar Harbor, Maine 04609, USA Description of the
molecular phenotypes of pathobiological processes in vivo is a pressing
need in genomic biology.We have implemented a high-throughput real-time
PCR strategy to establish quantitative expression profiles of a
customized set of target genes.It enables rapid, reproducible data
acquisition from limited quantities of RNA, permitting serial sampling
of mouse blood during disease progression.We developed an easy to use
statistical algorithm—Global Pattern Recognition—to readily identify
genes whose expression has changed significantly from healthy baseline
profiles.This approach provides unique molecular signatures for
rheumatoid arthritis, systemic lupus erythematosus, and graft versus
host disease, and can also be applied to defining the molecular
phenotype of a variety of other normal and pathological processes.
Activated NKT Cells Inhibit Autoimmune Diabetes through Tolerogenic Recruitment of Dendritic Cells to Pancreatic Lymph Nodes Yi-Guang Chen, Caroline-Morgane Choisy-Rossi, Thomas M. Holl, Harold D. Chapman, Gurdyal S. Besra, Steven A. Porcelli, Daniel J. Shaffer, Derry Roopenian, S. Brian Wilson, and David V. Serreze The Journal of Immunology, 2005, 174: 1196-1204 This paper tried to
determine why a drug (a-GalCer or a-galactosylceramide) could inhibit
the onset of autoimmune diabetes. Among many experiments, GPR was
used to determine why a systemic drug (a-GalCer) treatment elicited the
migration of mature Dendritic Cells (DC) and T cells into the
Pancreatic Lymph Nodes (PLNs), but not the Mesenteric Lymph Nodes
(MLNs) of Non-Obese Diabetic (NOD) mice. They compared the expression
levels by real-time PCR of genes encoding 19 different chemokines and
11 of their receptors in the PLNs and MLNs of NOD mice that were either
untreated or injected 24 h previously with a-GalCer. There were
no significant differences between PLNs and MLNs from untreated mice.
However, CCL17 (5.3-fold), CCL19 (2.4-fold), CCL5 (1.8-fold), and
CXCL16 (1.6-fold) gene expression levels were significantly higher in
the PLNs than MLNs of a-GalCer-treated NOD mice. Conversely, CCR4
(3.3-fold) and CCR6 (1.7-fold) were expressed at higher levels in the
MLNs of the a-GalCer-treated NOD mice. This differential level of
chemokine expression may underlie the migration of DCs and T cells to
the PLNs, but not the MLNs, of a-GalCer-treated NOD mice thus resulting
in an inhibition of autoimmune diabetes.
A Real-Time PCR Array for Hierarchical Identification of Francisella Isolates Kerstin Svensson1,2, Malin Granberg1, Linda Karlsson1, Vera Neubauerova3, Mats Forsman1, Anders Johansson1,2 1 Division of CBRN Defense and Security, Swedish Defense Research Agency, Umeå, Sweden, 2 Department of Clinical Microbiology, Infectious Diseases and Bacteriology, Umeå University, Umeå, Sweden, 3 Central Military Health Institute, Prague, Czech Republic PLoS ONE 4(12): e8360 A robust, rapid and
flexible real-time PCR assay for hierarchical genetic typing of
clinical and environmental isolates of Francisella is presented. Typing
markers were found by multiple genome and gene comparisons, from which
23 canonical single nucleotide polymorphisms (canSNPs) and 11 canonical
insertion-deletion mutations (canINDELs) were selected to provide
phylogenetic guidelines for classification from genus to isolate level.
The specificity of the developed assay, which uses 68 wells of a
96-well real-time PCR format with a detection limit of 100 pg DNA, was
assessed using 62 Francisella isolates of diverse genetic and
geographical origins. It was then successfully used for typing 14 F.
tularensis subsp. holarctica isolates obtained from tularemia patients
in Sweden in 2008 and five more genetically diverse Francisella
isolates of global origins. When applied to human ulcer specimens for
direct pathogen detection the results were incomplete due to scarcity
of DNA, but sufficient markers were identified to detect
fine-resolution differences among F. tularensis subsp. holarctica
isolates causing infection in the patients. In contrast to other
real-time PCR assays for Francisella, which are typically designed for
specific detection of a species, subspecies, or strain, this type of
assay can be easily tailored to provide appropriate phylogenetic and/or
geographical resolution to meet the objectives of the analysis.
The nonhomologous end joining factor Artemis suppresses multi-tissue tumor formation and prevents loss of heterozygosity Y Woo, SM Wright, SA Maas1,7, TL Alley1, LB Caddle1, S Kamdar1, J Affourtit, O Foreman1, EC Akeson, D Shaffer, RT Bronson, HC Morse, D Roopenian and KD Mills Oncogene. 2007 26(41): 6010-6020 Used an early version of
the StellARray to confirm
CGH (Comparative Genome Hybridization) results in a mouse model to
cancer however they did not publish their use of GPR but instead used
classical statistical measures.Nonhomologous end
joining (NHEJ) is a critical DNA repair pathway, with proposed tumor
suppression functions in many tissues. Mutations in the NHEJ factor
ARTEMIS cause radiation-sensitive severe combined immunodeficiency in
humans and may increase susceptibility to lymphoma in some settings. We
now report that deficiency for Artemis (encoded by Dclre1c/Art in
mouse) accelerates tumorigenesis in several tissues in a Trp53
heterozygous setting, revealing tumor suppression roles for NHEJ in
lymphoid and non-lymphoid cells. We also show that B-lineage lymphomas
in these mice undergo loss of Trp53 heterozygosity by allele
replacement, but arise by mechanisms distinct from those in Art Trp53
double null mice. These findings demonstrate a general tumor
suppression function for NHEJ, and reveal that interplay between NHEJ
and Trp53 loss of heterozygosity influences the sequence of multi-hit
oncogenesis. We present a model where p53 status at the time of tumor
initiation is a key determinant of subsequent oncogenic mechanisms.
Because Art deficient mice represent a model for radiation-sensitive
severe combined immunodeficiency, our findings suggest that these
patients may be at risk for both lymphoid and non-lymphoid cancers.
General Normalistion Stategies in real-time PCR Real-Time PCR:
Current Technology and Applications
Publisher: Caister Academic Press Editor: Julie Logan, Kirstin Edwards and Nick Saunders Applied and Functional Genomics, Health Protection Agency, London (2009) ISBN: 978-1-904455-39-4 http://www.horizonpress.com/realtimePCR Chapter 4 - Reference Gene Validation Software for Improved Normalization J. Vandesompele, M. Kubista and M. W. Pfaffl (2009) Real-time PCR is the
method of choice for expression
analysis of a
limited number of genes. The measured gene expression variation between
subjects is the sum of the true biological variation and several
confounding factors resulting in non-specific variation. The purpose of
normalization is to remove the non-biological variation as much as
possible. Several normalization strategies have been proposed, but the
use of one or more reference genes is currently the preferred way of
normalization. While these reference genes constitute the best possible
normalizers, a major problem is that these genes have no constant
expression under all experimental conditions. The experimenter
therefore needs to carefully assess whether a certain reference gene is
stably expressed in the experimental system under study. This is not
trivial and represents a circular problem. Fortunately, several
algorithms and freely available software have been developed to address
this problem. This chapter aims to provide an overview of the different
concepts.
Chapter 5 - Data Analysis Software M. W. Pfaffl, J. Vandesompele and M. Kubista (2009) Quantitative real-time
RT-PCR (qRT-PCR) is widely and
increasingly used
in any kind of mRNA quantification, because of its high sensitivity,
good reproducibility and wide dynamic quantification range. While
qRT-PCR has a tremendous potential for analytical and quantitative
applications, a comprehensive understanding of its underlying
principles is important. Beside the classical RT-PCR parameters, e.g.
primer design, RNA quality, RT and polymerase performances, the
fidelity of the quantification process is highly dependent on a valid
data analysis. This review will cover all aspects of data acquisition
(trueness, reproducibility, and robustness), potentials in data
modification and will focus particularly on relative quantification
methods. Furthermore useful bioinformatical, biostatical as well as
multi-dimensional expression software tools will be presented.
Real-Time PCR:
Current Technology and Applications - Book reviews:
Companies providing qPCR arrays:
LONZA & Bar Harbor Biotechnology White Paper: StellARray Gene Expression System - Revealing Profiles with Unbiased Significance Daniel Shaffer, Aaron Brown, William Olver Bar Harbor BioTechnology, Inc. and Marjorie Smithhisler, Lonza Walkersville, Inc. In this paper, we
present three application ex-amples demonstrating the utility of the
StellARray Gene Expression System to reveal gene expression level
changes in diverse biological contexts such as toxicology, cancer, and
stem cell differentiation. By combining Clonetics and
Poietics Primary Human Cells with the StellARray Gene Expression
System, all from Lonza, the researcher is pro-vided with a synergistic
system to reveal gross and subtle changes in gene expression when
analyzing in vitro models of human tissues. This is accomplished
easily in 96- and 384-well formatted StellARrayqPCR Arrays using a
stan-dard qPCR instrument and a generic SYBR® Green-based Reagent
Master Mix. The Global Pattern
Recognition (GPR) Data Analysis Tool is
optimally suited to generate a ranked list of significantly changed
genes within a qPCR dataset. GPR overcomes the inconsistencies
associated with con-ventional single gene normalization procedures by
eliminat-ing a priori normalizer selection. Overall, the results show
how the StellARray Gene Expression System eliminates false positives
and provides TRUE results that are backed by a rigorous statistical
analysis.
Simple and accurate analysis of Real-Time PCR data using Bar Harbor Biotechnology GPR software http://www.bhbio.com/products/gpr/ Bar Harbor Biotechnology has solved one of the most fundamental problems facing experimentation using Real-Time PCR. How do I analyze the data and determine REAL changes in gene expression? The answer to this question is found in Bar Harbor Biotechnology, Inc.'s patent pending Global Pattern Recognition (GPR) algorithm, which makes gene expression analysis simple, fast and reliable. Here are some reasons why we developed this algorithm. Real-time
dogma #1 - using single gene normalizers
The traditional approach to measure gene expression changes from Real-Time PCR data has been to normalize the results of a gene of interest with respect to a housekeeping gene (aka. a reference or normalizer gene). The general assumption is that the level of expression of the normalizer gene does not change in the context of the experiment and can be used to normalize the variability in RNA quantity between individual samples. By normalizing to a housekeeping gene, in theory, a magnitude of change can be calculated between groups of samples for a gene of interest. However, this mode of analysis is greatly complicated by the fact that housekeeping genes commonly used as normalizers (e.g., GAPDH, β-actin, and HPRT) themselves can change in apparent expression when comparing tissues or cells in different states (Bustin 2000; Schmittgen et al. 2000; Goidin et al. 2001; Hamalainen et al. 2001). 18S rRNA is another normalizer that intuitively and experimentally seems more stable, but even 18S can vary in comparison to other genes when analyzed by sensitive Real-Time PCR techniques (Bustin 2000, Akilesh et al., 2003). Any small variation in the normalizer amplification would therefore compromise the analysis of the complete Real-Time PCR data set. Real-time
dogma #2 - ranking genes strictly by fold change
When a single gene normalizer is selected, gene expression changes are typically ranked by their magnitude of change using the ΔΔCt method, with those genes showing the largest fold changes ranked as most significant. Unfortunately, these large changes in gene expression may mask small, but biologically important changes in gene expression, such as master regulator genes (e.g., transcription factors). In biology, however, larger is not always synonymous with importance. To combat the above mentioned problems, Bar Harbor Biotechnology, Inc. developed a modified Global Pattern Recognition™ algorithm (Akilesh et al., 2003), which is optimally suited to generate a ranked list of significantly changed genes within a Real-Time PCR dataset. This unique algorithm and accompanying software overcomes the problem of identifying invariant normalizers and the pitfalls of producing faulty statistics based merely on magnitude of change. Global Pattern Recognition provides a true statistical analysis of results based on consistency in the data, which makes Global Pattern Recognition™ optimally suited to detect small, but reproducible changes. Only after the genes are statistically ranked is the magnitude of the change calculated. A typical experiment would utilize 'biological replicates' (Bio-Reps). Bio-Reps are defined as samples collected from separate and closely matched biological samples. They are processed individually under closely matched conditions. Advisedly, it is best to analyze at least 3 bio-reps in each of two groups, representing for example '3 sick vs. 3 healthy' or '3 treated vs. 3 untreated' groups (but Global Pattern Recognition can handle much larger data sets). Global Pattern Recognition processes the data derived from groups of Bio-Reps and reveals the 'constellation' of changing genes. Each constellation can be evaluated for the most likely biological context providing the researcher with a better understanding of the overall results. Just as early sea navigators used the stars to triangulate their position on the ocean, Global Pattern Recognition globally positions the expression level of each gene with respect to all genes within an experiment. This can be done without prior assumption that a gene (normalizer) has an invariant expression level. Global Pattern Recognition is unbiased in that it enables the experimental data to define the invariant normalizer genes, not the experimenter. The use of any gene as a potential normalizer also maximizes the use of the limited real-estate on a StellARray™ plate by eliminating the loss of wells used to contain potentially erroneously predefined normalizers. Global Pattern Recognition is extremely simple to use and reliably tabulates statistical significance (p-value) of gene expression changes on the fly allowing you to immediately focus on the real biology. Simply log into GPR, select the StellARray that you ran on your Real-Time PCR instrument, upload your data and submit for analysis. An HTML or Excel® formatted file will be generated that gives a ranked list of genes by p-value, fold change value, and links to MGI and NCBI gene pages. With each purchase of a StellARray™ pack your account will be receive analysis query credits sufficient to analyze each plate.
 SA Biosciences (a QIAGEN company) SABiosciences
leads the field in high-performance SYBR Green real-time PCR analysis.
Our RT² Profiler PCR Arrays (patent pending) analyze expression of
a panel of genes associated with any one of over 100 biological
pathways or specific disease states. The RT² qPCR primer Assays
are experimentally tested and validated qRT-PCR primer sets for every
human, mouse, rat, rhesus macaque, or even fruit fly gene. These qPCR
primer assays are ready-to-use for gene-by-gene expression analysis,
microarray data validation, biomarker discovery and siRNA knock-down
verification. In combination with our special formulated and
instrument-specific PCR master mixes, our complete RT² qPCR
products provide the accurate, reliable, and convenient SYBR Green
analysis needed by today's research. Trust the experts in SYBR Green
real-time PCR detection.
Genome-wide microRNA detection by real-time PCR => Download White Paper
Roche Applied Science
Exiqon
Life Technologies Custom TaqMan® Assay Manufacturing & Plating Service If your research application requires special manufacturing modifications - such as a different dye or assay volume, or you would like to have your assays plated in a specific way, our custom services can help. TaqMan® Gene Expression Assays TaqMan® Gene Expression Assays provide over 1.2 million predesigned primer/probe sets covering 19 species, the most comprehensive set of quantitative gene expression assays available. Alternatively, custom assays enable you to study the expression of any gene or splice variant in any organism. TaqMan® MicroRNA Assays Innovative TaqMan® Assays for microRNA and other small RNAs, as well as longer noncoding RNA transcripts such as pri-miRNAs and long noncoding RNA. We offer products for noncoding RNA discovery, profiling, quantitation, validation, and functional analysis. TaqMan® Assays for Genotyping & Genetic Variation Analysis The precision of TaqMan® probe-based chemistry makes SNP genotyping and copy number variation studies more accurate than ever. Choose from 4.5 million human and mouse TaqMan® SNP Genotyping Assays or design your own Custom TaqMan® SNP Genotyping Assays. For analysis of SNPs in genes for drug metabolizing enzymes (DMEs), Life Technologies offers 2,700 unique TaqMan® DME Assays that detect polymorphisms in 221 genes for DMEs and associated transporter targets. For copy number variation studies, Life Technologies offer over 1.6 million predesigned TaqMan® Copy Number Assays with human, genome-wide coverage, and mouse and marker/reporter assays. Custom and Custom Plus TaqMan® Copy Number Assay options are ideal when a predesigned assay for a target is not available.
TaqMan® Protein Assays Revolutionary TaqMan® Protein Assays enable fast, easy identification, and relative quantification of protein markers from limited quantities of cultured cells. Choose from predesigned assays for human stem cell pluripotency markers and control proteins, or create your own assay from your biotinylated antibodies. OpenArray OpenArray represents a major breakthrough for life science researchers, enabling massively parallel, high quality nanoliter assays. It’s ideal for low-volume solution-phase reactions including analysis of genetic, genomic, biochemical, and cellular samples. For more information on specific OpenArray technology products, click on the appropriate link below: The OpenArray Real-Time qPCR System enables nearly three thousand real-time qPCR assays to be run on a single OpenArray plate Researchers can test one to 48 different samples against a wide array of assays. The system enables flexibility in experimental design in many research areas: * Quantitative expression analysis * Pathogen detection * Methylation studies * Pathway analysis * Infectious disease studies * Forensics * Genetic identification WaferGen Next Generation Real-time PCR Comes of Age The WaferGen SmartChip System enables profiling and validation workflows on a single platform, by combining high-throughput, cost-effective target discovery with the sensitivity, precision, and dynamic range of real-time PCR for validation studies. Gene Expression Profiling - Discover More Gene expression profiling of specific diseases has become increasingly important in drug development. Comparison of gene expression patterns between normal and diseased patients or expression profiles in the presence or absence of drugs leads to discovery of genes or a set of genes that can be used in drug development. This requires monitoring of tens, hundreds or thousands of mRNAs in large numbers. The WaferGen SmartChip System offers the capability to achieve this level of throughput with a high degree of accuracy. MicroRNA Profiling - Comprehensive human microRNA profile on a single chip MicroRNAs (miRNA) are post-transcriptional regulators of cell proliferation, tissue differentiation, embryonic development, and apoptosis. Specific miRNA expression profiles may be characteristic of diseases or disease states and used as biomarkers. The identification of miRNA profiles has become important for streamlining drug development processes. The comparison of miRNA patterns from normal and disease samples; or contrasting miRNA profiles of the same sample in the presence or absence of a drug leads to a greater understanding of pathways and mechanisms of action. The WaferGen SmartChip System in conjunction with the pre-validated SmartChip human miRNA panel, offers researchers the ability to carry out comprehensive, rapid miRNA profiling on their human samples simply, cost-effectively, and accurately. Fluidigm Fluidigm’s BioMark 96x96 Dynamic
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time PCR primer sets
Perform up to 200 PCR Arrays! Flexibility to design one's own experiments Microplate containing 88 targeted plus 8 housekeeping gene primer sets Note: Primer sequences unavailable for primer libraries
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