119 resultados para high throughput sequencing

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


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BACKGROUND:
The genetic heterogeneity of many Mendelian disorders, such as retinitis pigmentosa which results from mutations in over 40 genes, is a major obstacle to obtaining a molecular diagnosis in clinical practice. Targeted high-throughput DNA sequencing offers a potential solution and was used to develop a molecular diagnostic screen for patients with retinitis pigmentosa.
METHODS:
A custom sequence capture array was designed to target the coding regions of all known retinitis pigmentosa genes and used to enrich these sequences from DNA samples of five patients. Enriched DNA was subjected to high-throughput sequencing singly or in pools, and sequence variants were identified by alignment of up to 10 million reads per sample to the normal reference sequence. Potential pathogenicity was assessed by functional predictions and frequency in controls.
RESULTS AND CONCLUSIONS:
Known homozygous PDE6B and compound heterozygous CRB1 mutations were detected in two patients. A novel homozygous missense mutation (c.2957A?T; p.N986I) in the cyclic nucleotide gated channel ß1 (CNGB1) gene predicted to have a deleterious effect and absent in 720 control chromosomes was detected in one case in which conventional genetic screening had failed to detect mutations. The detection of known and novel retinitis pigmentosa mutations in this study establishes high-throughput DNA sequencing with DNA pooling as an effective diagnostic tool for heterogeneous genetic diseases.

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The growing accessibility to genomic resources using next-generation sequencing (NGS) technologies has revolutionized the application of molecular genetic tools to ecology and evolutionary studies in non-model organisms. Here we present the case study of the European hake (Merluccius merluccius), one of the most important demersal resources of European fisheries. Two sequencing platforms, the Roche 454 FLX (454) and the Illumina Genome Analyzer (GAII), were used for Single Nucleotide Polymorphisms (SNPs) discovery in the hake muscle transcriptome. De novo transcriptome assembly into unique contigs, annotation, and in silico SNP detection were carried out in parallel for 454 and GAII sequence data. High-throughput genotyping using the Illumina GoldenGate assay was performed for validating 1,536 putative SNPs. Validation results were analysed to compare the performances of 454 and GAII methods and to evaluate the role of several variables (e.g. sequencing depth, intron-exon structure, sequence quality and annotation). Despite well-known differences in sequence length and throughput, the two approaches showed similar assay conversion rates (approximately 43%) and percentages of polymorphic loci (67.5% and 63.3% for GAII and 454, respectively). Both NGS platforms therefore demonstrated to be suitable for large scale identification of SNPs in transcribed regions of non-model species, although the lack of a reference genome profoundly affects the genotyping success rate. The overall efficiency, however, can be improved using strict quality and filtering criteria for SNP selection (sequence quality, intron-exon structure, target region score).

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The cysteine protease cathepsin S (CatS) is involved in the pathogenesis of autoimmune disorders, atherosclerosis, and obesity. Therefore, it represents a promising pharmacological target for drug development. We generated ligand-based and structure-based pharmacophore models for noncovalent and covalent CatS inhibitors to perform virtual high-throughput screening of chemical databases in order to discover novel scaffolds for CatS inhibitors. An in vitro evaluation of the resulting 15 structures revealed seven CatS inhibitors with kinetic constants in the low micromolar range. These compounds can be subjected to further chemical modifications to obtain drugs for the treatment of autoimmune disorders and atherosclerosis.

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The spontaneous formation of the neurotoxic carcinogen acrylamide in a wide range of cooked foods has recently been discovered. These foods include bread and other bakery products, crisps, chips, breakfast cereals, and coffee. To date, the diminutive size of acrylamide (71.08Da) has prevented the development of screening immunoassays for this chemical. In this study, a polyclonal antibody capable of binding the carcinogen was produced by the synthesis of an immunogen comprising acrylamide derivatised with 3-mercaptobenzoic acid (3-MBA), and its conjugation to the carrier protein bovine thyroglobulin. Antiserum from the immunised rabbit was harvested and fully characterised. it displayed no binding affinity for acrylamide or 3-MBA but had a high affinity for 3-MBA-derivitised acrylamide. The antisera produced was utilised in the development of an ELISA based detection system for acrylamide. Spiked water samples were assayed for acrylamide content using a previously published extraction method validated for coffee, crispbread, potato, milk chocolate and potato crisp matrices. Extracted acrylamide was then subjected to a rapid 1-h derivatisation with 3-MBA, pre-analysis. The ELISA was shown to have a high specificity for acrylamide, with a limit of detection in water samples of 65.7 mu g kg(-1), i.e. potentially suitable for acrylamide detection in a wide range of food commodities. Future development of this assay will increase sensitivity further. This is the first report of an immunoassay capable of detecting the carcinogen, as its small size has necessitated current analytical detection via expensive, slower, physico-chemical techniques such as Gas or Liquid Chromatography coupled to Mass Spectrometry. (c) 2007 Elsevier B.V. All rights reserved.

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Background: Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide.

Methodology: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap.

Conclusion: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.