15 resultados para SNP microarray

em CentAUR: Central Archive University of Reading - UK


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The tagged microarray marker (TAM) method allows high-throughput differentiation between predicted alternative PCR products. Typically, the method is used as a molecular marker approach to determining the allelic states of single nucleotide polymorphisms (SNPs) or insertion-deletion (indel) alleles at genomic loci in multiple individuals. Biotin-labeled PCR products are spotted, unpurified, onto a streptavidin-coated glass slide and the alternative products are differentiated by hybridization to fluorescent detector oligonucleotides that recognize corresponding allele-specific tags on the PCR primers. The main attractions of this method are its high throughput (thousands of PCRs are analyzed per slide), flexibility of scoring (any combination, from a single marker in thousands of samples to thousands of markers in a single sample, can be analyzed) and flexibility of scale (any experimental scale, from a small lab setting up to a large project). This protocol describes an experiment involving 3,072 PCRs scored on a slide. The whole process from the start of PCR setup to receiving the data spreadsheet takes 2 d.

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Accurately and reliably identifying the actual number of clusters present with a dataset of gene expression profiles, when no additional information on cluster structure is available, is a problem addressed by few algorithms. GeneMCL transforms microarray analysis data into a graph consisting of nodes connected by edges, where the nodes represent genes, and the edges represent the similarity in expression of those genes, as given by a proximity measurement. This measurement is taken to be the Pearson correlation coefficient combined with a local non-linear rescaling step. The resulting graph is input to the Markov Cluster (MCL) algorithm, which is an elegant, deterministic, non-specific and scalable method, which models stochastic flow through the graph. The algorithm is inherently affected by any cluster structure present, and rapidly decomposes a graph into cohesive clusters. The potential of the GeneMCL algorithm is demonstrated with a 5730 gene subset (IGS) of the Van't Veer breast cancer database, for which the clusterings are shown to reflect underlying biological mechanisms. (c) 2005 Elsevier Ltd. All rights reserved.

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Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particulary in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process. Genet Epidemiol 25:106-114, 2003. (C) 2003 Wiley-Liss, Inc.

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Neoglycolipid technology is the basis of a microarray platform for assigning oligosaccharide ligands for carbohydrate-binding proteins. The strategy for generating the neoglycolipid probes by reductive amination results in ring opening of the core monosaccharides. This often limits applicability to short-chain saccharides, although the majority of recognition motifs are satisfactorily presented with neoglycolipids of longer oligosaccharides. Here, we describe neoglycolipids prepared by oxime ligation. We provide evidence from NMR studies that a significant proportion of the oxime-linked core monosaccharide is in the ring-closed form, and this form selectively interacts with a carbohydrate-binding protein. By microarray analyses we demonstrate the effective presentation with oxime-linked neoglycolipids of (1) Lewis(x) trisaccharide to antibodies to Lewisx, (2) sialyllactose analogs to the sialic acid-binding receptors, siglecs, and (3) N-glycans to a plant lectin that requires an intact N-acetylglucosamine core.

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The Phenotype MicroArray (TM) (PM) technology was used to study the metabolic characteristics of 29 Salmonella strains belonging to seven serotypes of S. enterica spp. enterica. Strains of serotypes Typhimurium (six strains among definite phage types DTs 1, 40 and 104) and Agona (two strains) were tested for 949 substrates, Enteritidis (six strains of phage type PT1), Give, Hvittingfoss, Infantis and Newport strains (two of each) were tested for 190 substrates and seven other Agona strains for 95 substrates. The strains represented 18 genotypes in pulsed-field gel electrophoresis (PFGE). Among 949 substrates, 18 were identified that could be used to differentiate between the strains of those seven serotypes or within a single serotype. Unique metabolic differences between the Finnish endemic Typhimurium DT1 and Agona strains were detected, for example, in the metabolism of d-tagatose, d-galactonic acid gamma-lactone and l-proline as a carbon source. Thus, the PM technique is a useful tool for identifying potential differential markers on a metabolic basis that could be used for epidemiological surveillance.

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Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

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We describe the development of a miniaturised microarray for the detection of antimicrobial resistance genes in Gram-negative bacteria. Included on the array are genes encoding resistance to aminoglycosides, trimethoprim, sulphonamides, tetracyclines and beta-lactams, including extended-spectrum beta-lactamases. Validation of the array with control strains demonstrated a 99% correlation between polymerase chain reaction and array results. There was also good correlation between phenotypic and genotypic results for a large panel of Escherichia coli and Salmonella isolates. Some differences were also seen in the number and type of resistance genes harboured by E. coli and Salmonella strains. The array provides an effective, fast and simple method for detection of resistance genes in clinical isolates suitable for use in diagnostic laboratories, which in future will help to understand the epidemiology of isolates and to detect gene linkage in bacterial populations. (C) 2008 Published by Elsevier B.V. and the International Society of Chemotherapy.

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Background A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNPbased linkage map of an apple rootstock progeny. Results Of the 7,867 Malus SNP markers on the array, 1,823 (23.2 %) were heterozygous in one of the two parents of the progeny, 1,007 (12.8 %) were heterozygous in both parental genotypes, whilst just 2.8 % of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the ‘Golden Delicious’ genome sequence. A total of 311 markers (13.7 % of all mapped markers) mapped to positions that conflicted with their predicted positions on the ‘Golden Delicious’ pseudo-chromosomes, indicating the presence of paralogous genomic regions or misassignments of genome sequence contigs during the assembly and anchoring of the genome sequence. Conclusions We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the ‘Golden Delicious’ reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

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We have performed microarray hybridization studies on 40 clinical isolates from 12 common serovars within Salmonella enterica subspecies I to identify the conserved chromosomal gene pool. We were able to separate the core invariant portion of the genome by a novel mathematical approach using a decision tree based on genes ranked by increasing variance. All genes within the core component were confirmed using available sequence and microarray information for S. enterica subspecies I strains. The majority of genes within the core component had conserved homologues in Escherichia coli K-12 strain MG1655. However, many genes present in the conserved set which were absent or highly divergent in K-12 had close homologues in pathogenic bacteria such as Shigella flexneri and Pseudomonas aeruginosa. Genes within previously established virulence determinants such as SPI1 to SPI5 were conserved. In addition several genes within SPI6, all of SPI9, and three fimbrial operons (fim, bcf, and stb) were conserved within all S. enterica strains included in this study. Although many phage and insertion sequence elements were missing from the core component, approximately half the pseudogenes present in S. enterica serovar Typhi were conserved. Furthermore, approximately half the genes conserved in the core set encoded hypothetical proteins. Separation of the core and variant gene sets within S. enterica subspecies I has offered fundamental biological insight into the genetic basis of phenotypic similarity and diversity across S. enterica subspecies I and shown how the core genome of these pathogens differs from the closely related E. coli K-12 laboratory strain.

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Developments in high-throughput genotyping provide an opportunity to explore the application of marker technology in distinctness, uniformity and stability (DUS) testing of new varieties. We have used a large set of molecular markers to assess the feasibility of a UPOV Model 2 approach: “Calibration of threshold levels for molecular characteristics against the minimum distance in traditional characteristics”. We have examined 431 winter and spring barley varieties, with data from UK DUS trials comprising 28 characteristics, together with genotype data from 3072 SNP markers. Inter varietal distances were calculated and we found higher correlations between molecular and morphological distances than have been previously reported. When varieties were grouped by kinship, phenotypic and genotypic distances of these groups correlated well. We estimated the minimum marker numbers required and showed there was a ceiling after which the correlations do not improve. To investigate the possibility of breaking through this ceiling, we attempted genomic prediction of phenotypes from genotypes and higher correlations were achieved. We tested distinctness decisions made using either morphological or genotypic distances and found poor correspondence between each method.

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The availability of crop specimens archived in herbaria and old seed collections represent valuable resources for the analysis of plant genetic diversity and crop domestication. The ability to extract ancient DNA (aDNA) from such samples has recently allowed molecular genetic investigations to be undertaken in ancient materials. While analyses of aDNA initially focused on the use of markers which occur in multiple copies such as the internal transcribed spacer region (ITS) within ribosomal DNA and those requiring amplification of short DNA regions of variable length such as simple sequence repeats (SSRs), emphasis is now moving towards the genotyping of single nucleotide polymorphisms (SNPs), traditionally undertaken in aDNA by Sanger sequencing. Here, using a panel of barley aDNA samples previously surveyed by Sanger sequencing for putative causative SNPs within the flowering-time gene PPD-H1, we assess the utility of the Kompetitive Allele Specific PCR (KASP) genotyping platform for aDNA analysis. We find KASP to out-perform Sanger sequencing in the genotyping of aDNA samples (78% versus 61% success, respectively), as well as being robust to contamination. The small template size (≥46 bp) and one-step, closed-tube amplification/genotyping process make this platform ideally suited to the genotypic analysis of aDNA, a process which is often hampered by template DNA degradation and sample cross-contamination. Such attributes, as well as its flexibility of use and relatively low cost, make KASP particularly relevant to the genetic analysis of aDNA samples. Furthermore, KASP provides a common platform for the genotyping and analysis of corresponding SNPs in ancient, landrace and modern plant materials. The extended haplotype analysis of PPD-H1 undertaken here (allelic variation at which is thought to be important for the spread of domestication and local adaptation) provides further resolution to the previously identified geographic cline of flowering-time allele distribution, illustrating how KASP can be used to aid genetic analyses of aDNA from plant species. We further demonstrate the utility of KASP by genotyping ten additional genetic markers diagnostic for morphological traits in barley, shedding light on the phenotypic traits, alleles and allele combinations present in these unviable ancient specimens, as well as their geographic distributions.

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Faba bean (Vicia faba L.) is a globally important nitrogen-fixing legume, which is widely grown in a diverse range of environments. In this work, we mine and validate a set of 845 SNPs from the aligned transcriptomes of two contrasting inbred lines. Each V. faba SNP is assigned by BLAST analysis to a single Medicago orthologue. This set of syntenically anchored polymorphisms were then validated as individual KASP assays, classified according to their informativeness and performance on a panel of 37 inbred lines, and the best performing 757 markers used to genotype six mapping populations. The six resulting linkage maps were merged into a single consensus map on which 687 SNPs were placed on six linkage groups, each presumed to correspond to one of the six V. faba chromosomes. This sequence-based consensus map was used to explore synteny with the most closely-related crop species, lentil, and the most closely related fully sequenced genome, Medicago. Large tracts of uninterrupted colinearity were found between faba bean and Medicago, making it relatively straightforward to predict gene content and order in mapped genetic interval. As a demonstration of this, we mapped a flower colour gene to a 2 cM interval of Vf chromosome 2 which was highly collinear with Mt3. The obvious candidate gene from 77 gene models in the collinear Medicago chromosome segment was the previously characterized MtWD40-1 gene (Mt3g092830, Mt3g092840) controlling anthocyanin production in Medicago and re-sequencing of the Vf orthologue showed a putative causative deletion of the entire 5’ end of the gene.

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The pyrimidine glycosides, vicine and convicine, limit the use of faba bean (Vicia faba L.) as food and feed. A single recessive gene, vc-, is responsible for a lowered vicine–convicine concentration. The biosynthetic pathway of these closely related compounds is not known, and the nearest available markers are several cM away from vc-. Improved markers would assist breeding and help to identify candidate genes. A segregating population of 210 F5 recombinant inbred lines was developed from the cross of Mélodie/2 (low vicine–convicine) × ILB 938/2 (normal vicine–convicine), and vicine–convicine concentrations were determined twice on each line. The population was genotyped with a set of 188 SNPs. A strong, single QTL for vicine–convicine concentration was identified on chromosome I, flanked by markers 1.0 cM away on one side and 2.6 cM on the other. The interval defined by these markers in the model species Medicago truncatula includes about 340 genes, but no candidate genes were identified. Further fine mapping should lead to the identification of tightly linked markers as well as narrowing down the search for candidate regulatory or biosynthetic genes which could underlie the vc- locus.

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SCOPE: A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. METHODS AND RESULTS: We used mathematical modelling to predict levels of PUFA in whole blood, based on MHT and bolasso selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1,607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Amongst other food items, fish, pizza, chicken and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26% to 43% of the variability in PUFA concentrations in the training set and 22% to 33% in the test set. CONCLUSIONS: Selecting food items using MHT is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set.

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Background— T NADPH oxidase, by generating reactive oxygen species, is involved in the pathophysiology of many cardiovascular diseases and represents a therapeutic target for the development of novel drugs. A single-nucleotide polymorphism (SNP) C242T of the p22phox subunit of NADPH oxidase has been reported to be negatively associated with coronary heart disease (CHD) and may predict disease prevalence. However, the underlying mechanisms remain unknown. Methods and Results— Using computer molecular modelling we discovered that C242T SNP causes significant structural changes in the extracellular loop of p22phox and reduces its interaction stability with Nox2 subunit. Gene transfection of human pulmonary microvascular endothelial cells showed that C242T p22phox reduced significantly Nox2 expression but had no significant effect on basal endothelial O2.- production or the expression of Nox1 and Nox4. When cells were stimulated with TNFα (or high glucose), C242T p22phox inhibited significantly TNFα-induced Nox2 maturation, O2.- production, MAPK and NFκB activation and inflammation (all p<0.05). These C242T effects were further confirmed using p22phox shRNA engineered HeLa cells and Nox2-/- coronary microvascular endothelial cells. Clinical significance was investigated using saphenous vein segments from non CHD subjects after phlebectomies. TT (C242T) allele was common (prevalence of ~22%) and compared to CC, veins bearing TT allele had significantly lower levels of Nox2 expression and O2.- generation in response to high glucose challenge. Conclusions— C242T SNP causes p22phox structural changes that inhibit endothelial Nox2 activation and oxidative response to TNFα or high glucose stimulation. C242T SNP may represent a natural protective mechanism against inflammatory cardiovascular diseases.