969 resultados para SNP microarray
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La investigació entre les relacions dels nivells d’expressió dels gens aporta molta informació sobre els processos biològics i patològics. Mitjançant la tècnica de les microarrays es possibilita la investigació de les relacions d’expressió de milers de gens a la vegada. La finalitat d’aquest projecte es fent ús de l’aplicatiu web PCOPGene-Net, permetre la identificació dels gens per les relacions d’expressió no lineals que tenen amb la resta de gens i permetre també la identificació de les relacions d’expressió no lineals entre els gens d’una microarray.
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En la presente memoria se detalla con precisión las diversas fases del trabajo para construir una aplicación web en el servidor http://revolutionresearch.uab.es que permite enriquecer los clusters de la microarray del usuario con información biomédica de una base de datos remota. Los clusters de origen estadístico (o no) de la microarray del usuario se enriquecen a partir de cruzar sus genes marcadores con la base de datos de genes marcadores de microarrays (base de datos remota) con clusters basados en información biomédica. La base de datos de genes marcadores de microarrays ha sido obtenida a partir de la base de datos de GEO Profiles del NCBI.
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Human genetic variation contributes to differences in susceptibility to HIV-1 infection. To search for novel host resistance factors, we performed a genome-wide association study (GWAS) in hemophilia patients highly exposed to potentially contaminated factor VIII infusions. Individuals with hemophilia A and a documented history of factor VIII infusions before the introduction of viral inactivation procedures (1979-1984) were recruited from 36 hemophilia treatment centers (HTCs), and their genome-wide genetic variants were compared with those from matched HIV-infected individuals. Homozygous carriers of known CCR5 resistance mutations were excluded. Single nucleotide polymorphisms (SNPs) and inferred copy number variants (CNVs) were tested using logistic regression. In addition, we performed a pathway enrichment analysis, a heritability analysis, and a search for epistatic interactions with CCR5 Δ32 heterozygosity. A total of 560 HIV-uninfected cases were recruited: 36 (6.4%) were homozygous for CCR5 Δ32 or m303. After quality control and SNP imputation, we tested 1 081 435 SNPs and 3686 CNVs for association with HIV-1 serostatus in 431 cases and 765 HIV-infected controls. No SNP or CNV reached genome-wide significance. The additional analyses did not reveal any strong genetic effect. Highly exposed, yet uninfected hemophiliacs form an ideal study group to investigate host resistance factors. Using a genome-wide approach, we did not detect any significant associations between SNPs and HIV-1 susceptibility, indicating that common genetic variants of major effect are unlikely to explain the observed resistance phenotype in this population.
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The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 x 10(-8); odds ratio = 0.87; 95% confidence interval, 0.83-0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.
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The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.
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PURPOSE: The purpose of this work was to study the influence of cell differentiation on the mRNA expression of transporters and channels in Caco-2 cells and to assess Caco-2 cells as a model for carrier-mediated drug transport in the intestines. METHOD: Gene mRNA expression was measured using a custom-designed microarray chip with 750 deoxyoligonucleotide probes (70mers). Each oligomer was printed four times on poly-lysine-coated glass slides. Expression profiles were expressed as ratio values between fluorescence intensities of Cy3 and Cy5 dye-labeled cDNA derived from poly(A) + RNA samples of Caco-2 cells and total RNA of human intestines. RESULTS: Significant differences in the mRNA expression profile of transporters and channels were observed upon differentiation of Caco-2 cells from 5 days to 2 weeks in culture, including changes for MAT8, S-protein, and Nramp2. Comparing Caco-2 cells of different passage number revealed few changes in mRNAs except for GLUT3, which was down-regulated 2.4-fold within 13 passage numbers. Caco-2 cells had a similar expression profile when either cultured in flasks or on filters but differed more strongly from human small and large intestine, regardless of the differentiation state of Caco-2 cells. Expression of several genes highly transcribed in small or large intestines differed fourfold or more in Caco-2 cells. CONCLUSIONS: Although Caco-2 cells have proven a suitable model for studying carrier-mediated transport in human intestines, the expression of specific transporter and ion channel genes may differ substantially.
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It has recently been proposed that the SSAT gene plays a role in the predisposition to suicidal behavior. SSAT expression was found to be down-regulated in the brain of suicide completers. In addition, a single nucleotide polymorphism (SNP) rs6526342 was associated both with variation in SSAT expression and with suicidal behavior. In this study, we aimed to characterize the relationship between SSAT dysregulation and suicide behavior. To this end, we measured SSAT expression levels in the ventral prefrontal cortex (VPFC) of suicide completers (n = 20) and controls (n = 20) and found them to be significantly down-regulated in suicide victims (P = 0.007). To identify the basis of the regulation of SSAT expression, we performed an association analysis of 309 SNPs with SSAT transcript levels in 53 lymphoblastoid cell lines from the CEPH collection. We then examined the methylation status of the SSAT promoter region in males and females suicide completers and control subjects whose SSAT brain expression had been measured. We found no evidence to support a role for SNPs in controlling the level of SSAT expression. SSAT promoter methylation levels were not different between suicide completers and controls and did not correlate with SSAT expression levels. In addition, we found no indication of a genetic association between suicidal behavior and SNPs located within the SSAT gene. Our study provides new results which show that dysregulation of SSAT expression does play a role in suicide behavior. However, our data do not support any association between rs6526342 and variation in SSAT expression or suicidal behavior.
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BACKGROUND: Vitamin D insufficiency has been associated with the occurrence of various types of cancer, but causal relationships remain elusive. We therefore aimed to determine the relationship between genetic determinants of vitamin D serum levels and the risk of developing hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC). METHODOLOGYPRINCIPAL FINDINGS: Associations between CYP2R1, GC, and DHCR7 genotypes that are determinants of reduced 25-hydroxyvitamin D (25[OH]D3) serum levels and the risk of HCV-related HCC development were investigated for 1279 chronic hepatitis C patients with HCC and 4325 without HCC, respectively. The well-known associations between CYP2R1 (rs1993116, rs10741657), GC (rs2282679), and DHCR7 (rs7944926, rs12785878) genotypes and 25(OH)D3 serum levels were also apparent in patients with chronic hepatitis C. The same genotypes of these single nucleotide polymorphisms (SNPs) that are associated with reduced 25(OH)D3 serum levels were found to be associated with HCV-related HCC (P = 0.07 [OR = 1.13, 95% CI = 0.99-1.28] for CYP2R1, P = 0.007 [OR = 1.56, 95% CI = 1.12-2.15] for GC, P = 0.003 [OR = 1.42, 95% CI = 1.13-1.78] for DHCR7; ORs for risk genotypes). In contrast, no association between these genetic variations and liver fibrosis progression rate (P>0.2 for each SNP) or outcome of standard therapy with pegylated interferon-α and ribavirin (P>0.2 for each SNP) was observed, suggesting a specific influence of the genetic determinants of 25(OH)D3 serum levels on hepatocarcinogenesis. CONCLUSIONSSIGNIFICANCE: Our data suggest a relatively weak but functionally relevant role for vitamin D in the prevention of HCV-related hepatocarcinogenesis.
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The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10(-8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ~115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.
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Inter-individual differences in gene expression are likely to account for an important fraction of phenotypic differences, including susceptibility to common disorders. Recent studies have shown extensive variation in gene expression levels in humans and other organisms, and that a fraction of this variation is under genetic control. We investigated the patterns of gene expression variation in a 25 Mb region of human chromosome 21, which has been associated with many Down syndrome (DS) phenotypes. Taqman real-time PCR was used to measure expression variation of 41 genes in lymphoblastoid cells of 40 unrelated individuals. For 25 genes found to be differentially expressed, additional analysis was performed in 10 CEPH families to determine heritabilities and map loci harboring regulatory variation. Seventy-six percent of the differentially expressed genes had significant heritabilities, and genomewide linkage analysis led to the identification of significant eQTLs for nine genes. Most eQTLs were in trans, with the best result (P=7.46 x 10(-8)) obtained for TMEM1 on chromosome 12q24.33. A cis-eQTL identified for CCT8 was validated by performing an association study in 60 individuals from the HapMap project. SNP rs965951 located within CCT8 was found to be significantly associated with its expression levels (P=2.5 x 10(-5)) confirming cis-regulatory variation. The results of our study provide a representative view of expression variation of chromosome 21 genes, identify loci involved in their regulation and suggest that genes, for which expression differences are significantly larger than 1.5-fold in control samples, are unlikely to be involved in DS-phenotypes present in all affected individuals.
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Wounding in multicellular eukaryotes results in marked changes in gene expression that contribute to tissue defense and repair. Using a cDNA microarray technique, we analyzed the timing, dynamics, and regulation of the expression of 150 genes in mechanically wounded leaves of Arabidopsis. Temporal accumulation of a group of transcripts was correlated with the appearance of oxylipin signals of the jasmonate family. Analysis of the coronatine-insensitive coi1-1 Arabidopsis mutant that is also insensitive to jasmonate allowed us to identify a large number of COI1-dependent and COI1-independent wound-inducible genes. Water stress was found to contribute to the regulation of an unexpectedly large fraction of these genes. Comparing the results of mechanical wounding with damage by feeding larvae of the cabbage butterfly (Pieris rapae) resulted in very different transcript profiles. One gene was specifically induced by insect feeding but not by wounding; moreover, there was a relative lack of water stress-induced gene expression during insect feeding. These results help reveal a feeding strategy of P. rapae that may minimize the activation of a subset of water stress-inducible, defense-related genes.
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SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch
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INTRODUCTION: Common variation in the CHRNA5-CHRNA3-CHRNB4 gene region is robustly associated with smoking quantity. Conversely, the association between one of the most significant single nucleotide polymorphisms (SNPs; rs1051730 within the CHRNA3 gene) with perceived difficulty or willingness to quit smoking among current smokers is unknown. METHODS: Cross-sectional study including current smokers, 502 women, and 552 men. Heaviness of smoking index (HSI), difficulty, attempting, and intention to quit smoking were assessed by questionnaire. RESULTS: The rs1051730 SNP was associated with increased HSI (age, gender, and education-adjusted mean ± SE: 2.6 ± 0.1, 2.2 ± 0.1, and 2.0 ± 0.1 for AA, AG, and GG genotypes, respectively, p < .01). Multivariate logistic regression adjusting for gender, age, education, leisure-time physical activity, and personal history of cardiovascular or lung disease showed rs1051730 to be associated with higher smoking dependence (odds ratio [OR] and 95% CI for each additional A-allele: 1.38 [1.11-1.72] for smoking more than 20 cigarette equivalents/day; 1.31 [1.00-1.71] for an HSI ≥5 and 1.32 [1.05-1.65] for smoking 5 min after waking up) and borderline associated with difficulty to quit (OR = 1.29 [0.98-1.70]), but this relationship was no longer significant after adjusting for nicotine dependence. Also, no relationship was found with willingness (OR = 1.03 [0.85-1.26]), attempt (OR = 1.00 [0.83-1.20]), or preparation (OR = 0.95 [0.38-2.38]) to quit. Similar findings were obtained for other SNPs, but their effect on nicotine dependence was no longer significant after adjusting for rs1051730. Conclusions: These data confirm the effect of rs1051730 on nicotine dependence but failed to find any relationship with difficulty, willingness, and motivation to quit.
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Samples containing highly unbalanced DNA mixtures from two individuals commonly occur both in forensic mixed stains and in peripheral blood DNA microchimerism induced by pregnancy or following organ transplant. Because of PCR amplification bias, the genetic identification of a DNA that contributes trace amounts to a mixed sample represents a tremendous challenge. This means that standard genetic markers, namely microsatellites, also referred as short tandem repeats (STR), and single-nucleotide polymorphism (SNP) have limited power in addressing common questions of forensic and medical genetics. To address this issue, we developed a molecular marker, named DIP-STR that relies on pairing deletion-insertion polymorphisms (DIP) with STR. This novel analytical approach allows for the unambiguous genotyping of a minor component in the presence of a major component, where DIP-STR genotypes of the minor were successfully procured at ratios up to 1:1,000. The compound nature of this marker generates a high level of polymorphism that is suitable for identity testing. Here, we demonstrate the power of the DIP-STR approach on an initial set of nine markers surveyed in a Swiss population. Finally, we discuss the limitations and potential applications of our new system including preliminary tests on clinical samples and estimates of their performance on simulated DNA mixtures.
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Pendant ma thèse de doctorat, j'ai utilisé des espèces modèles, comme la souris et le poisson-zèbre, pour étudier les facteurs qui affectent l'évolution des gènes et leur expression. Plus précisément, j'ai montré que l'anatomie et le développement sont des facteurs clés à prendre en compte, car ils influencent la vitesse d'évolution de la séquence des gènes, l'impact sur eux de mutations (i.e. la délétion du gène est-elle létale ?), et leur tendance à se dupliquer. Où et quand il est exprimé impose à un gène certaines contraintes ou au contraire lui donne des opportunités d'évoluer. J'ai pu comparer ces tendances aux modèles classiques d'évolution de la morphologie, que l'on pensait auparavant refléter directement les contraintes s'appliquant sur le génome. Nous avons montré que les contraintes entre ces deux niveaux d'organisation ne peuvent pas être transférées simplement : il n'y a pas de lien direct entre la conservation du génotype et celle de phénotypes comme la morphologie. Ce travail a été possible grâce au développement d'outils bioinformatiques. Notamment, j'ai travaillé sur le développement de la base de données Bgee, qui a pour but de comparer l'expression des gènes entre différentes espèces de manière automatique et à large échelle. Cela implique une formalisation de l'anatomie, du développement et de concepts liés à l'homologie grâce à l'utilisation d'ontologies. Une intégration cohérente de données d'expression hétérogènes (puces à ADN, marqueurs de séquence exprimée, hybridations in situ) a aussi été nécessaire. Cette base de données est mise à jour régulièrement et disponible librement. Elle devrait contribuer à étendre les possibilités de comparaison de l'expression des gènes entre espèces pour des études d'évo-devo (évolution du développement) et de génomique. During my PhD, I used model species of vertebrates, such as mouse and zebrafish, to study factors affecting the evolution of genes and their expression. More precisely I have shown that anatomy and development are key factors to take into account, influencing the rate of gene sequence evolution, the impact of mutations (i.e. is the deletion of a gene lethal?), and the propensity of a gene to duplicate. Where and when genes are expressed imposes constraints, or on the contrary leaves them some opportunity to evolve. We analyzed these patterns in relation to classical models of morphological evolution in vertebrates, which were previously thought to directly reflect constraints on the genomes. We showed that the patterns of evolution at these two levels of organization do not translate smoothly: there is no direct link between the conservation of genotype and phenotypes such as morphology. This work was made possible by the development of bioinformatics tools. Notably, I worked on the development of the database Bgee, which aims at comparing gene expression between different species in an automated and large-scale way. This involves the formalization of anatomy, development, and concepts related to homology, through the use of ontologies. A coherent integration of heterogeneous expression data (microarray, expressed sequence tags, in situ hybridizations) is also required. This database is regularly updated and freely available. It should contribute to extend the possibilities for comparison of gene expression between species in evo-devo and genomics studies.