948 resultados para cDNA microarray analysis
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Die vorliegende Dissertation entstand im Rahmen eines multizentrischen EU-geförderten Projektes, das die Anwendungsmöglichkeiten von Einzelnukleotid-Polymorphismen (SNPs) zur Individualisierung von Personen im Kontext der Zuordnung von biologischen Tatortspuren oder auch bei der Identifizierung unbekannter Toter behandelt. Die übergeordnete Zielsetzung des Projektes bestand darin, hochauflösende Genotypisierungsmethoden zu etablieren und zu validieren, die mit hoher Genauigkeit aber geringen Aufwand SNPs im Multiplexformat simultan analysieren können. Zunächst wurden 29 Y-chromosomale und 52 autosomale SNPs unter der Anforderung ausgewählt, dass sie als Multiplex eine möglichst hohe Individualisierungschance aufweisen. Anschließend folgten die Validierungen beider Multiplex-Systeme und der SNaPshot™-Minisequenzierungsmethode in systematischen Studien unter Beteiligung aller Arbeitsgruppen des Projektes. Die validierte Referenzmethode auf der Basis einer Minisequenzierung diente einerseits für die kontrollierte Zusammenarbeit unterschiedlicher Laboratorien und andererseits als Grundlage für die Entwicklung eines Assays zur SNP-Genotypisierung mittels der elektronischen Microarray-Technologie in dieser Arbeit. Der eigenständige Hauptteil dieser Dissertation beschreibt unter Verwendung der zuvor validierten autosomalen SNPs die Neuentwicklung und Validierung eines Hybridisierungsassays für die elektronische Microarray-Plattform der Firma Nanogen Dazu wurden im Vorfeld drei verschiedene Assays etabliert, die sich im Funktionsprinzip auf dem Microarray unterscheiden. Davon wurde leistungsorientiert das Capture down-Assay zur Weiterentwicklung ausgewählt. Nach zahlreichen Optimierungsmaßnahmen hinsichtlich PCR-Produktbehandlung, gerätespezifischer Abläufe und analysespezifischer Oligonukleotiddesigns stand das Capture down-Assay zur simultanen Typisierung von drei Individuen mit je 32 SNPs auf einem Microarray bereit. Anschließend wurde dieses Verfahren anhand von 40 DNA-Proben mit bekannten Genotypen für die 32 SNPs validiert und durch parallele SNaPshot™-Typisierung die Genauigkeit bestimmt. Das Ergebnis beweist nicht nur die Eignung des validierten Analyseassays und der elektronischen Microarray-Technologie für bestimmte Fragestellungen, sondern zeigt auch deren Vorteile in Bezug auf Schnelligkeit, Flexibilität und Effizienz. Die Automatisierung, welche die räumliche Anordnung der zu untersuchenden Fragmente unmittelbar vor der Analyse ermöglicht, reduziert unnötige Arbeitsschritte und damit die Fehlerhäufigkeit und Kontaminationsgefahr bei verbesserter Zeiteffizienz. Mit einer maximal erreichten Genauigkeit von 94% kann die Zuverlässigkeit der in der forensischen Genetik aktuell eingesetzten STR-Systeme jedoch noch nicht erreicht werden. Die Rolle des neuen Verfahrens wird damit nicht in einer Ablösung der etablierten Methoden, sondern in einer Ergänzung zur Lösung spezieller Probleme wie z.B. der Untersuchung stark degradierter DNA-Spuren zu finden sein.
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Nach einer hämatopoetischen Stammzelltransplantation spielt die Zuordnung hämatopoetischer Zellen zum Spender oder Empfänger für viele transplantationsbezogene Fragestellungen eine wichtige Rolle. Unter anderem ist das Persistieren von dendritischen Zellen des Empfängers, welche allogene T-Zellen des Spenders stimulieren, ein wichtiger Schritt bei der Entstehung der akuten GVHD. Aus diesem Grund wurde in dieser Arbeit die Weiterentwicklung einer Methode angestrebt, die es uns erlaubt, die Zugehörigkeit isolierter hämatopoetischer Zellen dem Spender oder dem Empfänger zuzuordnen (Chimärismusbestimmung) und gleichzeitig Aussagen über das Ursprungsgewebe und den Aktivierungszustand der Zellen machen zu können. Hierfür nutzten wir Einzelbasenpolymorphismen (SNPs). Ziel dieser Arbeit war es, einen Pool von cDNA-kodierten SNPs zu definieren, mit dem auch HLA-identische Geschwister eindeutig unteschieden werden können. rnHierfür wurden zunächst aus publizierten Datenbanken solche SNPs ausgewählt, die in kodierenden Genabschnitten konstitutiv und gewebeunabhängig auf expremierten Genen lagen und zugleich eine hohe Heterozygotenfrequenz in der europäischen Population aufwiesen. Anhand dieser Kriterien wurden mittels der NCBI-Datenbank insgesamt eine Anzahl von 208 Polymorphismen auf 150 Genen identifiziert. Anschließend erfolgte die Gestaltung von Primerpaaren zur Amplifikation der SNP-kodierenden cDNA-Abschnitte. Diese mussten mindestens eine Intron/Exon-Grenze überspannen, um genomische DNA in der PCR ausschließen zu können. Mit Hilfe der etablierten PCR-Reaktion wurden die Gene in unterschiedlichen Geweben auf ihre Expression hin überprüft. Für 45 Gene ließ sich sowohl eine entsprechende PCR etablieren als auch deren konstitutive Expression in verschiedenen hämatopoetischen Zellen nachweisen. Zur Detektion der einzelnen SNPs in der Minisequenzierung wurden Minisequenzierungs-Sonden generiert und geprüft. Im Folgenden wurden für PCR und Minisequezierung Multiplex-Reaktionen aus vier bis sechs Reaktionen zusammengestellt. Zu diesem Zweck wurden die jeweiligen Primerinteraktionen und die unterschiedlichen Basenlängen des PCR-Produktes berücksichtigt.rnVon den 45 etablierten Einzelreaktionen waren 30 für den Multiplexansatz geeignet. Unter Anwendung dieser Multiplex-Reaktionen wurden 24 HLA-identische Geschwisterpaare (Spender und Empfänger) getestet. Zur Kontrolle erfolgte zusätzlich eine konventionelle Sequenzierung der SNP-kodierenden Bereiche auf der cDNA der jeweiligen Proben. Mit Hilfe der SNP-Kombinationen und der etablierten Methodik waren wir in der Lage alle 24 untersuchten Geschwisterpaare in zwischen sechs und 18 SNP-Systemen zu unterscheiden. rnDie Möglichkeiten, die die Analysen des Chimärismus mittels SNPs auf kodierenden Bereichen der DNA mit sich bringen, liegen nicht nur in der gleichzeitigen Bestimmung der Gewebszugehörigkeit und der Detektion des bestehenden Chimärismus sowie dessen Quantifizierung unter Anwendung einer Real-time-PCR. Vielmehr ermöglicht sie auch eine Aussage über die Genexpression der untersuchten Zelle zu machen. Dies ist insbesondere dann von Interesse, wenn geringe Zellzahlen von aus Gewebe isolierten Zellen zur Verfügung stehen. Die in dieser Arbeit etablierten Ansätze werden derzeit für eine Quantifizierung mittels real-time RCR weiterentwickelt und sollen mittelfristig insbesondere für Untersuchungen des Chimärismus von dermalen und epidermalen dendritischen Zellen der Haut und anderer Zielgewebe der GvHD verwendet werden.rn
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In der vorliegenden Arbeit wurde eine Top Down (TD) und zwei Bottom Up (BU) MALDI/ESI Massenspektrometrie/HPLC-Methoden entwickelt mit dem Ziel Augenoberfächenkomponenten, d.h. Tränenfilm und Konjunktivalzellen zu analysieren. Dabei wurde ein detaillierter Einblick in die Entwicklungsschritte gegeben und die Ansätze auf Eignung und methodische Grenzen untersucht. Während der TD Ansatz vorwiegend Eignung zur Analyse von rohen, weitgehend unbearbeiteten Zellproben fand, konnten mittels des BU Ansatzes bearbeitete konjunktivale Zellen, aber auch Tränenfilm mit hoher Sensitivität und Genauigkeit proteomisch analysiert werden. Dabei konnten mittels LC MALDI BU-Methode mehr als 200 Tränenproteine und mittels der LC ESI Methode mehr als 1000 Tränen- sowie konjunktivale Zellproteine gelistet werden. Dabei unterschieden sich ESI- and MALDI- Methoden deutlich bezüglich der Quantität und Qualität der Ergebnisse, weshalb differente proteomische Anwendungsgebiete der beiden Methoden vorgeschlagen wurden. Weiterhin konnten mittels der entwickelten LC MALDI/ESI BU Plattform, basierend auf den Vorteilen gegenüber dem TD Ansatz, therapeutische Einflüsse auf die Augenoberfläche mit Fokus auf die topische Anwendung von Taurin sowie Taflotan® sine, untersucht werden. Für Taurin konnten entzündungshemmende Effekte, belegt durch dynamische Veränderungen des Tränenfilms, dokumentiert werden. Außerdem konnten vorteilhafte, konzentrationsabhängige Wirkweisen auch in Studien an konjunktival Zellen gezeigt werden. Für die Anwendung von konservierungsmittelfreien Taflotan® sine, konnte mittels LC ESI BU Analyse eine Regenerierung der Augenoberfläche in Patienten mit Primärem Offenwinkel Glaukom (POWG), welche unter einem “Trockenem Auge“ litten nach einem therapeutischen Wechsel von Xalatan® basierend auf dynamischen Tränenproteomveränderungen gezeigt werden. Die Ergebnisse konnten mittels Microarray (MA) Analysen bestätigt werden. Sowohl in den Taurin Studien, als auch in der Taflotan® sine Studie, konnten charakteristische Proteine der Augenoberfläche dokumentiert werden, welche eine objektive Bewertung des Gesundheitszustandes der Augenoberfläche ermöglichen. Eine Kombination von Taflotan® sine und Taurin wurde als mögliche Strategie zur Therapie des Trockenen Auges bei POWG Patienten vorgeschlagen und diskutiert.
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PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.
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Background Parasitic wasps constitute one of the largest group of venomous animals. Although some physiological effects of their venoms are well documented, relatively little is known at the molecular level on the protein composition of these secretions. To identify the majority of the venom proteins of the endoparasitoid wasp Chelonus inanitus (Hymenoptera: Braconidae), we have randomly sequenced 2111 expressed sequence tags (ESTs) from a cDNA library of venom gland. In parallel, proteins from pure venom were separated by gel electrophoresis and individually submitted to a nano-LC-MS/MS analysis allowing comparison of peptides and ESTs sequences. Results About 60% of sequenced ESTs encoded proteins whose presence in venom was attested by mass spectrometry. Most of the remaining ESTs corresponded to gene products likely involved in the transcriptional and translational machinery of venom gland cells. In addition, a small number of transcripts were found to encode proteins that share sequence similarity with well-known venom constituents of social hymenopteran species, such as hyaluronidase-like proteins and an Allergen-5 protein. An overall number of 29 venom proteins could be identified through the combination of ESTs sequencing and proteomic analyses. The most highly redundant set of ESTs encoded a protein that shared sequence similarity with a venom protein of unknown function potentially specific of the Chelonus lineage. Venom components specific to C. inanitus included a C-type lectin domain containing protein, a chemosensory protein-like protein, a protein related to yellow-e3 and ten new proteins which shared no significant sequence similarity with known sequences. In addition, several venom proteins potentially able to interact with chitin were also identified including a chitinase, an imaginal disc growth factor-like protein and two putative mucin-like peritrophins. Conclusions The use of the combined approaches has allowed to discriminate between cellular and truly venom proteins. The venom of C. inanitus appears as a mixture of conserved venom components and of potentially lineage-specific proteins. These new molecular data enrich our knowledge on parasitoid venoms and more generally, might contribute to a better understanding of the evolution and functional diversity of venom proteins within Hymenoptera.
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Microarray technology is a powerful tool able to measure RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of crossplatform meta-analysis studies rapidly increase, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we notice that none of the previously published papers consider differences between labs. For this paper, a consortium of ten labs from the Washington DC/Baltimore (USA) area was formed to compare three heavily used platforms using identical RNA samples: Appropriate statistical analysis demonstrates that relatively large differences exist between labs using the same platform, but that the results from the best performing labs agree rather well. Supplemental material is available from http://www.biostat.jhsph.edu/~ririzarr/techcomp/
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With many different investigators studying the same disease and with a strong commitment to publish supporting data in the scientific community, there are often many different datasets available for any given disease. Hence there is substantial interest in finding methods for combining these datasets to provide better and more detailed understanding of the underlying biology. We consider the synthesis of different microarray data sets using a random effects paradigm and demonstrate how relatively standard statistical approaches yield good results. We identify a number of important and substantive areas which require further investigation.
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Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, chose an appropriate cut-off, and create a list of candidate genes. This approach has been criticized for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, many of these methods seem overly complicated. Furthermore, the most popular method, Gene Set Enrichment Analysis (GSEA), is based on a statistical test known for its lack of sensitivity. In this paper we compare the performance of a simple alternative to GSEA.We find that this simple solution clearly outperforms GSEA.We demonstrate this with eight different microarray datasets.
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Classical antibody-based serotyping of Escherichia coli is an important method in diagnostic microbiology for epidemiological purposes, as well as for a rough virulence assessment. However, serotyping is so tedious that its use is restricted to a few reference laboratories. To improve this situation we developed and validated a genetic approach for serotyping based on the microarray technology. The genes encoding the O-antigen flippase (wzx) and the O-antigen polymerase (wzy) were selected as target sequences for the O antigen, whereas fliC and related genes, which code for the flagellar monomer, were chosen as representatives for the H phenotype. Starting with a detailed bioinformatic analysis and oligonucleotide design, an ArrayTube-based assay was established: a fast and robust DNA extraction method was coupled with a site-specific, linear multiplex labeling procedure and hybridization analysis of the biotinylated amplicons. The microarray contained oligonucleotide DNA probes, each in duplicate, representing 24 of the epidemiologically most relevant of the over 180 known O antigens (O antigens 4, 6 to 9, 15, 26, 52, 53, 55, 79, 86, 91, 101, 103, 104, 111, 113, 114, 121, 128, 145, 157, and 172) as well as 47 of the 53 different H antigens (H antigens 1 to 12, 14 to 16, 18 to 21, 23 to 34, 37 to 43, 45, 46, 48, 49, 51 to 54, and 56). Evaluation of the microarray with a set of defined strains representing all O and H serotypes covered revealed that it has a high sensitivity and a high specificity. All of the conventionally typed 24 O groups and all of the 47 H serotypes were correctly identified. Moreover, strains which were nonmotile or nontypeable by previous serotyping assays yielded unequivocal results with the novel ArrayTube assay, which proved to be a valuable alternative to classical serotyping, allowing processing of single colonies within a single working day.
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Estradiol and progesterone are crucial for the acquisition of receptivity and the change in transcriptional activity of target genes in the implantation window. The aim of this study was to differentiate the regulation of genes in the endometrium of patients with recurrent implantation failure (IF) versus those who became pregnant after in vitro fertilization (IVF) treatment. Moreover, the effect of embryo-derived factors on endometrial transcriptional activity was studied. Nine women with known IVF outcome (IF, M, miscarriage, OP, ongoing pregnancy) and undergoing hysteroscopy with endometrial biopsy were enrolled. Biopsies were taken during the midluteal phase. After culture in the presence of embryo-conditioned IVF media, total RNA was extracted and submitted to reverse transcription, target cDNA synthesis, biotin labelling, fragmentation and hybridization using the Affymetrix Human Genome U133A 2.0 Chip. Differential expression of selected genes was re-analysed by quantitative PCR, in which the results were calculated as threshold cycle differences between the groups and normalized to Glyceraldehyde phosphate dehydrogenase and beta-actin. Differences were seen for several genes from endometrial tissue between the IF and the pregnancy groups, and when comparing OP with M, 1875 up- and 1807 down-regulated genes were returned. Real-time PCR analysis confirmed up-regulation for somatostatin, PLAP-2, mucin 4 and CD163, and down-regulation of glycodelin, IL-24, CD69, leukaemia inhibitory factor and prolactin receptor between Op and M. When the different embryo-conditioned media were compared, no significant differential regulation could be demonstrated. Although microarray profiling may currently not be sensitive enough for studying the effects of embryo-derived factors on the endometrium, the observed differences in gene expression between M and OP suggest that it will become an interesting tool for the identification of fertility-relevant markers produced by the endometrium.
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The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.
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Identification of dysplasia in inflammatory bowel disease represents a major challenge for both clinicians and pathologists. Clear diagnosis of dysplasia in inflammatory bowel disease is sometimes not possible with biopsies remaining "indefinite for dysplasia." Recent studies have identified molecular alterations in colitis-associated cancers, including increased protein levels of alpha-methylacyl coenzyme A racemase, p53, p16 and bcl-2. In order to analyze the potential diagnostic use of these parameters in biopsies from inflammatory bowel disease, a tissue microarray was manufactured from colons of 54 patients with inflammatory bowel disease composed of 622 samples with normal mucosa, 78 samples with inflammatory activity, 6 samples with low-grade dysplasia, 12 samples with high-grade dysplasia, and 66 samples with carcinoma. In addition, 69 colonoscopic biopsies from 36 patients with inflammatory bowel disease (28 low-grade dysplasia, 8 high-grade dysplasia, and 33 indefinite for dysplasia) were included in this study. Immunohistochemistry for alpha-methylacyl coenzyme A racemase, p53, p16 and bcl-2 was performed on both tissue microarray and biopsies. p53 and alpha-methylacyl coenzyme A racemase showed the most discriminating results, being positive in most cancers (77.3% and 80.3%) and dysplasias (94.4% and 94.4%) but only rarely in nonneoplastic epithelium (1.6% and 9.4%; P < .001). Through combining the best discriminators, p53 and alpha-methylacyl coenzyme A racemase, a stronger distinction between neoplastic tissues was possible. Of all neoplastic lesions, 75.8% showed a coexpression of alpha-methylacyl coenzyme A racemase and p53, whereas this was found in only 4 of 700 nonneoplastic samples (0.6%). alpha-methylacyl coenzyme A racemase/p53 coexpression was also found in 10 of 33 indefinite for dysplasia biopsies (30.3 %), suggesting a possible neoplastic transformation in these cases. Progression to dysplasia or carcinoma was observed in 3 of 10 p53/alpha-methylacyl coenzyme A racemase-positive, indefinite-for-dysplasia cases, including 1 of 7 cases without and 2 of 3 cases with p53 mutation. It is concluded that combined alpha-methylacyl coenzyme A racemase/p53 analysis may represent a helpful tool to confirm dysplasia in inflammatory bowel disease.
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We improved, evaluated, and used Sanger sequencing for quantification of single nucleotide polymorphism (SNP) variants in transcripts and gDNA samples. This improved assay resulted in highly reproducible relative allele frequencies (e.g., for a heterozygous gDNA 50.0+/-1.4%, and for a missense mutation-bearing transcript 46.9+/-3.7%) with a lower detection limit of 3-9%. It provided excellent accuracy and linear correlation between expected and observed relative allele frequencies. This sequencing assay, which can also be used for the quantification of copy number variations (CNVs), methylations, mosaicisms, and DNA pools, enabled us to analyze transcripts of the FBN1 gene in fibroblasts and blood samples of patients with suspected Marfan syndrome not only qualitatively but also quantitatively. We report a total of 18 novel and 19 known FBN1 sequence variants leading to a premature termination codon (PTC), 26 of which we analyzed by quantitative sequencing both at gDNA and cDNA levels. The relative amounts of PTC-containing FBN1 transcripts in fresh and PAXgene-stabilized blood samples were significantly higher (33.0+/-3.9% to 80.0+/-7.2%) than those detected in affected fibroblasts with inhibition of nonsense-mediated mRNA decay (NMD) (11.0+/-2.1% to 25.0+/-1.8%), whereas in fibroblasts without NMD inhibition no mutant alleles could be detected. These results provide evidence for incomplete NMD in leukocytes and have particular importance for RNA-based analyses not only in FBN1 but also in other genes.
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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/~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.
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Primaquine (PQ). a clinically important derivative of 8-aminoquinoline used against the hepatic stages (hypnozoites) of Plasmodium vivax and Plasmodium ova Ie. was studied to evaluate and compare between mRNA expression. and biochemical and histological parameters of hepatic stress in adult Swiss mice (Mus musculus). Following single oral dose of PQ (40 mglkg. bw). alanine aminotransferase (ALT) and aspartate aminotransferase (AST) along with hematoxylin and eosin stained liver sections did not show any signs of hepatic stress at 6. 12 and 24 h except for ALT activity at 6 h. However. analysis at RNA transcript level revealed consistent and significant deregulation (p<0.01 and twofold) of 16 probes corresponding to important cellular processes such as protein transportation. transcription regulation. intracellular signaling. protein synthesis, hematopoiesis, cell adhesion and cell proliferation. Pathway analysis identified large number of affected genes corresponding to 40 Gene Ontology terms having a z score greaibr than 2. These results indicate that PQ at high doses may affect gene expression in liver and may produce undesirable outcomes if consumed for longer durations.