22 resultados para Affymetrix GeneChip

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Rice (Oryza sativa) varieties that are arsenate-tolerant (Bala) and -sensitive (Azucena) were used to conduct a transcriptome analysis of the response of rice seedlings to sodium arsenate (AsV) in hydroponic solution. RNA extracted from the roots of three replicate experiments of plants grown for 1 week in phosphate-free nutrient with or without 13.3 muM AsV was used to challenge the Affymetrix (52K) GeneChip Rice Genome array. A total of 576 probe sets were significantly up-regulated at least 2-fold in both varieties, whereas 622 were down-regulated. Ontological classification is presented. As expected, a large number of transcription factors, stress proteins, and transporters demonstrated differential expression. Striking is the lack of response of classic oxidative stress-responsive genes or phytochelatin synthases/synthatases. However, the large number of responses from genes involved in glutathione synthesis, metabolism, and transport suggests that glutathione conjugation and arsenate methylation may be important biochemical responses to arsenate challenge. In this report, no attempt is made to dissect differences in the response of the tolerant and sensitive variety, but analysis in a companion article will link gene expression to the known tolerance loci available in the BalaxAzucena mapping population.

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BRCA1 encodes a tumor suppressor gene that is mutated in the germ line of women with a genetic predisposition to breast and ovarian cancer. BRCA1 has been implicated in a number of important cellular functions including DNA damage repair, transcriptional regulation, cell cycle control, and ubiquitination. Using an Affymetrix U95A microarray, IRF-7 was identified as a BRCA1 transcriptional target and was also shown to be synergistically up-regulated by BRCA1 specifically in the presence of IFN-gamma, coincident with the synergistic induction of apoptosis. We show that BRCA1, signal transducer and activator of transcription (STAT)-1, and STAT2 are all required for the induction of IRF-7 following stimulation with IFN-gamma. We also show that the induction of IRF-7 by BRCA1 and IFN-gamma is dependent on the type I IFNs, IFN-alpha and IFN-beta. We show that BRCA1 is required for the up-regulation of STAT1, STAT2, and the type I IFNs in response to IFN-gamma. We show that BRCA1 is localized at the promoters of the molecules involved in type I IFN signaling leading to their up-regulation. Blocking this intermediary type I IFN step using specific antisera shows the requirement for IFN-alpha and IFN-beta in the induction of IRF-7 and apoptosis. Finally, we outline a mechanism for the BRCA1/IFN-gamma regulation of target genes involved in the innate immune response, which is dependent on type I IFN signaling.

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Transcriptome analysis using microarray technology represents a powerful unbiased approach for delineating pathogenic mechanisms in disease. Here molecular mechanisms of renal tubulointerstitial fibrosis (TIF) were probed by monitoring changes in the renal transcriptome in a glomerular disease-dependent model of TIF ( adriamycin nephropathy) using Affymetrix (mu74av2) microarray coupled with sequential primary biological function-focused and secondary

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Background
Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.

Results
This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies.

Conclusion
The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMap

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PURPOSE: Retinitis pigmentosa (RP) causes hereditary blindness in adults (prevalence, approximately 1 in 4000). Each of the more than 30 causative genes identified to date are responsible for only a small percentage of cases. Genetic diagnosis via traditional methods is problematic, and a single test with a higher probability of detecting the causative mutation would be very beneficial for the clinician. The goal of this study therefore was to develop a high-throughput screen capable of detecting both known mutations and novel mutations within all genes implicated in autosomal recessive or simplex RP. DESIGN: Evaluation of diagnostic technology. PARTICIPANTS AND CONTROLS: Participants were 56 simplex and autosomal recessive RP patients, with 360 population controls unscreened for ophthalmic disease. METHODS: A custom genechip capable of resequencing all exons containing known mutations in 19 disease-associated genes was developed (RP genechip). A second, commercially available arrayed primer extension (APEX) system was used to screen 501 individual previously reported variants. The ability of these high-throughput approaches to identify pathogenic variants was assessed in a cohort of simplex and autosomal recessive RP patients. MAIN OUTCOME MEASURES: Number of mutations and potentially pathogenic variants identified. RESULTS: The RP genechip identified 44 sequence variants: 5 previously reported mutations; 22 known single nucleotide polymorphisms (SNPs); 11 novel, potentially pathogenic variants; and 6 novel SNPs. There was strong concordance with the APEX array, but only the RP genechip detected novel variants. For example, identification of a novel mutation in CRB1 revealed a patient, who also had a single previously known CRB1 mutation, to be a compound heterozygote. In some individuals, potentially pathogenic variants were discovered in more than one gene, consistent with the existence of disease modifier effects resulting from mutations at a second locus. CONCLUSIONS: The RP genechip provides the significant advantage of detecting novel variants and could be expected to detect at least one pathogenic variant in more than 50% of patients. The APEX array provides a reliable method to detect known pathogenic variants in autosomal recessive RP and simplex RP patients and is commercially available. High-throughput genotyping for RP is evolving into a clinically useful genetic diagnostic tool.

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BACKGROUND: To date, there are no clinically reliable predictive markers of response to the current treatment regimens for advanced colorectal cancer. The aim of the current study was to compare and assess the power of transcriptional profiling using a generic microarray and a disease-specific transcriptome-based microarray. We also examined the biological and clinical relevance of the disease-specific transcriptome.

METHODS: DNA microarray profiling was carried out on isogenic sensitive and 5-FU-resistant HCT116 colorectal cancer cell lines using the Affymetrix HG-U133 Plus2.0 array and the Almac Diagnostics Colorectal cancer disease specific Research tool. In addition, DNA microarray profiling was also carried out on pre-treatment metastatic colorectal cancer biopsies using the colorectal cancer disease specific Research tool. The two microarray platforms were compared based on detection of probesets and biological information.

RESULTS: The results demonstrated that the disease-specific transcriptome-based microarray was able to out-perform the generic genomic-based microarray on a number of levels including detection of transcripts and pathway analysis. In addition, the disease-specific microarray contains a high percentage of antisense transcripts and further analysis demonstrated that a number of these exist in sense:antisense pairs. Comparison between cell line models and metastatic CRC patient biopsies further demonstrated that a number of the identified sense:antisense pairs were also detected in CRC patient biopsies, suggesting potential clinical relevance.

CONCLUSIONS: Analysis from our in vitro and clinical experiments has demonstrated that many transcripts exist in sense:antisense pairs including IGF2BP2, which may have a direct regulatory function in the context of colorectal cancer. While the functional relevance of the antisense transcripts has been established by many studies, their functional role is currently unclear; however, the numbers that have been detected by the disease-specific microarray would suggest that they may be important regulatory transcripts. This study has demonstrated the power of a disease-specific transcriptome-based approach and highlighted the potential novel biologically and clinically relevant information that is gained when using such a methodology.

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Chronic myelomonocytic leukaemia (CMML) is a heterogeneous haematopoietic disorder characterized by myeloproliferative or myelodysplastic features. At present, the pathogenesis of this malignancy is not completely understood. In this study, we sought to analyse gene expression profiles of CMML in order to characterize new molecular outcome predictors. A learning set of 32 untreated CMML patients at diagnosis was available for TaqMan low-density array gene expression analysis. From 93 selected genes related to cancer and cell cycle, we built a five-gene prognostic index after multiplicity correction. Using this index, we characterized two categories of patients with distinct overall survival (94% vs. 19% for good and poor overall survival, respectively; P = 0.007) and we successfully validated its strength on an independent cohort of 21 CMML patients with Affymetrix gene expression data. We found no specific patterns of association with traditional prognostic stratification parameters in the learning cohort. However, the poor survival group strongly correlated with high-risk treated patients and transformation to acute myeloid leukaemia. We report here a new multigene prognostic index for CMML, independent of the gene expression measurement method, which could be used as a powerful tool to predict clinical outcome and help physicians to evaluate criteria for treatments.

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PURPOSE. Myopia is a complex trait affected by both genetic and environmental factors. High myopia is associated with increased risk of sight-threatening eye disorders such as retinal detachment. The purpose of this genome-wide association study was to identify susceptibility genes contributing to high myopia in the French population. METHODS. High myopic cases were genotyped using Affymetrix SNP 6.0 chips and population controls were selected from the GABRIEL French dataset in which samples were genotyped by Illumina Human610 quad array. The association study was conducted using 152,234 single nucleotide polymorphisms that were present on both manufacturers' chips in 192 high myopic cases and 1064 controls to identify associated regions. Imputation was performed on peak regions. RESULTS. Associations were found at known myopia locus MYP10 on chromosome 8p23 and MYP15 on chromosome 10q21.1. Rs189798 (8p23) and rs10825992 (10q21.1) showed the strongest associations in these regions (P=6.32x10-7 and P=2.17x10-5, respectively). The imputed results at 8p23 showed 2 peaks of interest. The first spanned 30kb including rs189798 between MIR4660 and PPP1R3B with the most significant association at rs17155227 (P=1.07x10-10). The second novel peak was 4kb in length, encompassing MIR124-1 and the MSRA gene, with the strongest association at rs55864141 (P=1.30x10-7). The peak of imputed data at 10q21.1 was 70kb in length between ZWINT and MIR3924, with rs3107503 having the lowest P value (P=1.54x10-7). CONCLUSION. We provide evidence for the association of MYP10 at 8p23 and MYP15 at 10p21.1 with high myopia in the French population and refine these regions of association.

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NuGO, the European Nutrigenomics Organization, utilizes 31 powerful computers for, e.g., data storage and analysis. These so-called black boxes (NBXses) are located at the sites of different partners. NuGO decided to use GenePattern as the preferred genomic analysis tool on each NBX. To handle the custom made Affymetrix NuGO arrays, new NuGO modules are added to GenePattern. These NuGO modules execute the latest Bioconductor version ensuring up-to-date annotations and access to the latest scientific developments. The following GenePattern modules are provided by NuGO: NuGOArrayQualityAnalysis for comprehensive quality control, NuGOExpressionFileCreator for import and normalization of data, LimmaAnalysis for identification of differentially expressed genes, TopGoAnalysis for calculation of GO enrichment, and GetResultForGo for retrieval of information on genes associated with specific GO terms. All together, these NuGO modules allow comprehensive, up-to-date, and user friendly analysis of Affymetrix data. A special feature of the NuGO modules is that for analysis they allow the use of either the standard Affymetrix or the MBNI custom CDF-files, which remap probes based on current knowledge. In both cases a .chip-file is created to enable GSEA analysis. The NuGO GenePattern installations are distributed as binary Ubuntu (.deb) packages via the NuGO repository.

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Background: The interleukin 10 knockout mouse (IL10-KO) is a model of human inflammatory bowel disease (IBD) used to Study host microbial interactions and the action of potential therapeutics. Using Affymetrix data analysis, important signaling pathways and transcription factors relevant to gut inflammation and antiinflammatory probiotics were identified.

Methods: Affymetrix microarray analysis on both wildtype (WT) and IL10-KO mice orally administered with and without the probiotic VSL#3 was performed and the results validated by real-time polymerase chain reaction (PCR), immunocytochemistry, proteomics, and histopathology. Changes in metabolically active bacteria were assessed with denaturing gradient gel electrophoresis (DGGE).

Results: Inflammation in IL10-KO mice was characterized by differential regulation of inflammatory, nuclear receptor, lipid, and xenobiotic signaling pathways. Probiotic intervention resulted in downregulation of CXCL9 (fold change [FC] = -3.98, false discovery rate [FDR] = 0.019), CXCL10 (FC = -4.83, FDR = 0.0008), CCL5 (FC -3.47 FDR = 0.017), T-cell activation (Itgal [FC = -4.72, FDR = 0.00009], Itgae [FC = -2.54 FDR = 0.0044]) and the autophagy gene IRGM (FC = -1.94, FDR = 0.01), a recently identified susceptibility gene in human IBD. Consistent with a marked reduction in integrins, probiotic treatment decreased the number of CCL5+ CD3+ double-positive T Cells and upregulated galectin2, which triggers apoptosis of activated T cells. Importantly, genes associated with lipid and PPAR signaling (PPAR alpha [FC = 2.36, FDR = 0.043], PPARGC1 alpha [FC 2.58, FDR = 0.016], Nrld2 [FC = 3.11, FDR = 0.0067]) were also upregulated. Altered microbial diversity was noted in probiotic-treated mice.

Conclusions: Bioinformatics analysis revealed important immune response. phagocytic and inflammatory pathways dominated by elevation of T-helper cell 1 type (TH1) transcription factors in IL10-KO mice. Probiotic intervention resulted in a site-specific reduction of these pathways but importantly upregulated PPAR, xenobiotic, and lipid signaling genes. potential antagonists of NF-kappa B inflammatory pathways.

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Chronic myelomonocytic leukemia is similar to but a separate entity from both myeloproliferative neoplasms and myelodysplastic syndromes, and shows either myeloproliferative or myelodysplastic features. We ask whether this distinction may have a molecular basis. We established the gene expression profiles of 39 samples of chronic myelomonocytic leukemia (including 12 CD34-positive) and 32 CD34-positive samples of myelodysplastic syndromes by using Affymetrix microarrays, and studied the status of 18 genes by Sanger sequencing and array-comparative genomic hybridization in 53 samples. Analysis of 12 mRNAS from chronic myelomonocytic leukemia established a gene expression signature of 122 probe sets differentially expressed between proliferative and dysplastic cases of chronic myelomonocytic leukemia. As compared to proliferative cases, dysplastic cases over-expressed genes involved in red blood cell biology. When applied to 32 myelodysplastic syndromes, this gene expression signature was able to discriminate refractory anemias with ring sideroblasts from refractory anemias with excess of blasts. By comparing mRNAS from these two forms of myelodysplastic syndromes we derived a second gene expression signature. This signature separated the myelodysplastic and myeloproliferative forms of chronic myelomonocytic leukemias. These results were validated using two independent gene expression data sets. We found that myelodysplastic chronic myelomonocytic leukemias are characterized by mutations in transcription/epigenetic regulators (ASXL1, RUNX1, TET2) and splicing genes (SRSF2) and the absence of mutations in signaling genes. Myelodysplastic chronic myelomonocytic leukemias and refractory anemias with ring sideroblasts share a common expression program suggesting they are part of a continuum, which is not totally explained by their similar but not, however, identical mutation spectrum. © 2013 Ferrata Storti Foundation.

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Myeloproliferative neoplasms (MPNs) are rare diseases that include classic entities; polycythaemia vera, essential thrombocythaemia and primary myelofibrosis. In this short report, minor allele frequencies of common MPN mutations are compared between the Irish blood donor population and other populations of European descent using data from the Haplotype Map project. The Affymetrix array 6.0 platform was utilised identifying nine single nucleotide polymorphisms (SNPs) and six proxy SNPs. The variability of allele frequencies for MPN mutations could account for the different incidence rates seen between populations of European ancestry, giving a better understanding of the genetic predisposition to MPNs. 

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Background:
Ovarian cancer is the fifth leading cause of cancer in women and has poor
long-term survival, in part, due to chemoresistance. Tumour hypoxia is associated with
chemoresistance in ovarian cancer. However, relatively little is known about the genes
activated in ovarian cancer which cause chemoresistance due to hypoxia. This study
aimed to firstly identify genes whose expression is associated with hypoxia-induced
chemoresistance, and secondly select hypoxia-associated biomarkers and evaluate their
expression in ovarian tumours.
Design:
Cisplatin-sensitive (A2780) and cisplatin-resistant (A2780cis) ovarian cancer
cell lines were exposed to combinations of hypoxia and/or cisplatin as part of a matrix
designed to reflect clinically relevant scenarios. RNA was extracted and interrogated
on Affymetrix Human Gene arrays. Differential gene expression was analysed for cells
exposed to hypoxia and/or treated with cisplatin. Potential markers of chemoresistance
were selected for evaluation in a cohort of ovarian tumour samples by R
T-PCR.
Results:
A wide range of genes associated with chemoresistance were differentially
expressed in cells exposed to hypoxia and/or cisplatin. Selected genes [ANGPTL4,
HER3 and HIF-1
α
] were chosen for further validation in a cohort of ovarian tumour
samples. High expression of ANGPTL4 trended towards reduced progression-free and
overall survival. High expression of HER3 trended to increased progression-free but
reduced overall survival, while high expression of HIF-1
α
trended towards reduced
progression-free and increased overall survival.
Conclusions:
In conclusion, this study has further characterized the relationship between
hypoxia and chemoresistance in an ovarian cancer model. We have also identified many
potential biomarkers of hypoxia and platinum resistance and provided initial validation
of a subset of these markers in ovarian cancer tissues.