891 resultados para sequence database


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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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Starting from a biologically active recombinant DNA clone of exogenous unintegrated GR mouse mammary tumor virus, we have generated three subclones of PstI fragments of 1.45, 1.1, and 2.0 kb in the plasmid vector PBR322. The nucleotide sequence has been determined for the clone of 1.45 kb which includes almost the complete region of the long terminal repeat (LTR) plus an adjacent stretch of unique sequence DNA. A short region of the 2.0 kb clone, containing the beginning of the LTR, has also been sequenced. Starting with the A of an initiation codon outside the LTR, we detected an open reading frame of 960 nucleotides, potentially coding for a protein of 320 amino acids (36K). Two hundred nucleotides downstream from the termination codon, and approximately 25 nucleotides upstream from the presumptive initiation site of viral RNA synthesis, we found a promoter-like sequence. The sequence AGTAAA was detected approximately 15-20 nucleotides upstream from the 3' end of virion RNA and probably serves as a polyadenylation signal. The 1.45 kb PstI fragment has been transfected into Ltk- cells together with a plasmid containing the thymidine kinase gene of herpes simplex virus. The virus-specific RNA synthesis detected in a Tk+ cell clone was strongly stimulated by the addition of dexamethasone.

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Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of nosocomial infections worldwide. To differentiate reliably among S. aureus isolates, we recently developed double locus sequence typing (DLST) based on the analysis of partial sequences of clfB and spa genes. In the present study, we evaluated the usefulness of DLST for epidemiological investigations of MRSA by routinely typing 1242 strains isolated in Western Switzerland. Additionally, particular local and international collections were typed by pulsed field gel electrophoresis (PFGE) and DLST to check the compatibility of DLST with the results obtained by PFGE, and for international comparisons. Using DLST, we identified the major MRSA clones of Western Switzerland, and demonstrated the close relationship between local and international clones. The congruence of 88% between the major PFGE and DLST clones indicated that our results obtained by DLST were compatible with earlier results obtained by PFGE. DLST could thus easily be incorporated in a routine surveillance procedure. In addition, the unambiguous definition of DLST types makes this method more suitable than PFGE for long-term epidemiological surveillance. Finally, the comparison of the results obtained by DLST, multilocus sequence typing, PFGE, Staphylococcal cassette chromosome mec typing and the detection of Panton-Valentine leukocidin genes indicated that no typing scheme should be used on its own. It is only the combination of data from different methods that gives the best chance of describing precisely the epidemiology and phylogeny of MRSA.

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Three-dimensional sequence stratigraphy is a potent exploration and development tool for the discovery of subtle stratigraphic traps. Reservoir morphology, heterogeneity and subtle stratigraphic trapping mechanisms can be better understood through systematic horizontal identification of sedimentary facies of systems tracts provided by three-dimensional attribute maps used as an important complement to the sequential analysis on the two-dimensional seismic lines and the well log data. On new prospects as well as on already-producing fields, the additional input of sequential analysis on three-dimensional data enables the identification, location and precise delimitation of new potentially productive zones. The first part of this paper presents four typical horizontal seismic facies assigned to the successive systems tracts of a third- or fourth-order sequence deposited in inner to outer neritic conditions on a elastic shelf. The construction of this synthetic representative sequence is based on the observed reproducibility of the horizontal seismic facies response to cyclic eustatic events on more than 35 sequences registered in the Gulf coast Plio-Pleistocene and Late Miocene, offshore Louisiana in the West Cameron region of the Gulf of Mexico. The second part shows how three-dimensional sequence stratigraphy can contribute in localizing and understanding sedimentary facies associated with productive zones. A case study in the early Middle Miocene Cibicides opima sands shows multiple stacked gas accumulations in the top slope fan, prograding wedge and basal transgressive systems tract of the third-order sequence between SB15.5 and SB 13.8 Ma.

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Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

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PURPOSE: To provide a mechanistic link between mutations in PRPF31, and essential and ubiquitously expressed gene, and retinitis pigmentosa, a disorder restricted to the eye. METHODS: We investigated the existence of retina-specific PRPF31 isoforms and the expression of this gene in human retina and other tissues, as well as in cultured human cell lines. PRPF31 transcripts were examined by RT-PCR, quantitative PCR, cloning and sequencing. RESULTS: Database searching revealed the presence of a retina-specific PRPF31 isoform in mouse. However, this isoform could not be experimentally identified in transcripts from human retina or from a human whole eye. Nevertheless, four different PRPF31 isoforms, that were common to all analyzed tissues and cell lines, were isolated. Three of these harbored the full-length PRPF31 coding sequence, whereas the fourth was very short and probably non-coding. The amount of PRPF31 mRNA was previously found to be lower in patients with mutations in this gene than in healthy individuals, making it likely that retinal cells are more sensitive to variation in PRPF31 expression. However, quantitative PCR experiments revealed that PRPF31 mRNA levels in human retina were comparable to those detected in other tissues. CONCLUSIONS: Our results show that the retina-restricted phenotype caused by PRPF31 mutations cannot be explained by the presence of tissue-specific isoforms, or by differential expression of PRPF31 in the retina. As a consequence, the etiology of PRPF31-associated retinitis pigmentosa likely relies on other, probably more subtle molecular mechanisms.

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Report produced by Iowa Departmment of Agriculture and Land Stewardship

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We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

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HAMAP (High-quality Automated and Manual Annotation of Proteins-available at http://hamap.expasy.org/) is a system for the automatic classification and annotation of protein sequences. HAMAP provides annotation of the same quality and detail as UniProtKB/Swiss-Prot, using manually curated profiles for protein sequence family classification and expert curated rules for functional annotation of family members. HAMAP data and tools are made available through our website and as part of the UniRule pipeline of UniProt, providing annotation for millions of unreviewed sequences of UniProtKB/TrEMBL. Here we report on the growth of HAMAP and updates to the HAMAP system since our last report in the NAR Database Issue of 2013. We continue to augment HAMAP with new family profiles and annotation rules as new protein families are characterized and annotated in UniProtKB/Swiss-Prot; the latest version of HAMAP (as of 3 September 2014) contains 1983 family classification profiles and 1998 annotation rules (up from 1780 and 1720). We demonstrate how the complex logic of HAMAP rules allows for precise annotation of individual functional variants within large homologous protein families. We also describe improvements to our web-based tool HAMAP-Scan which simplify the classification and annotation of sequences, and the incorporation of an improved sequence-profile search algorithm.

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The protein topology database KnotProt, http://knotprot.cent.uw.edu.pl/, collects information about protein structures with open polypeptide chains forming knots or slipknots. The knotting complexity of the cataloged proteins is presented in the form of a matrix diagram that shows users the knot type of the entire polypeptide chain and of each of its subchains. The pattern visible in the matrix gives the knotting fingerprint of a given protein and permits users to determine, for example, the minimal length of the knotted regions (knot's core size) or the depth of a knot, i.e. how many amino acids can be removed from either end of the cataloged protein structure before converting it from a knot to a different type of knot. In addition, the database presents extensive information about the biological functions, families and fold types of proteins with non-trivial knotting. As an additional feature, the KnotProt database enables users to submit protein or polymer chains and generate their knotting fingerprints.

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For the ∼1% of the human genome in the ENCODE regions, only about half of the transcriptionally active regions (TARs) identified with tiling microarrays correspond to annotated exons. Here we categorize this large amount of “unannotated transcription.” We use a number of disparate features to classify the 6988 novel TARs—array expression profiles across cell lines and conditions, sequence composition, phylogenetic profiles (presence/absence of syntenic conservation across 17 species), and locations relative to genes. In the classification, we first filter out TARs with unusual sequence composition and those likely resulting from cross-hybridization. We then associate some of those remaining with proximal exons having correlated expression profiles. Finally, we cluster unclassified TARs into putative novel loci, based on similar expression and phylogenetic profiles. To encapsulate our classification, we construct a Database of Active Regions and Tools (DART.gersteinlab.org). DART has special facilities for rapidly handling and comparing many sets of TARs and their heterogeneous features, synchronizing across builds, and interfacing with other resources. Overall, we find that ∼14% of the novel TARs can be associated with known genes, while ∼21% can be clustered into ∼200 novel loci. We observe that TARs associated with genes are enriched in the potential to form structural RNAs and many novel TAR clusters are associated with nearby promoters. To benchmark our classification, we design a set of experiments for testing the connectivity of novel TARs. Overall, we find that 18 of the 46 connections tested validate by RT-PCR and four of five sequenced PCR products confirm connectivity unambiguously.

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The goals of the human genome project did not include sequencing of the heterochromatic regions. We describe here an initial sequence of 1.1 Mb of the short arm of human chromosome 21 (HSA21p), estimated to be 10% of 21p. This region contains extensive euchromatic-like sequence and includes on average one transcript every 100 kb. These transcripts show multiple inter- and intrachromosomal copies, and extensive copy number and sequence variability. The sequencing of the "heterochromatic" regions of the human genome is likely to reveal many additional functional elements and provide important evolutionary information.

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A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

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We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels—to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human–mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments.