918 resultados para high throughput


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Single nucleotide polymorphisms (SNPs) are widely acknowledged as the marker of choice for many genetic and genomic applications because they show co-dominant inheritance, are highly abundant across genomes and are suitable for high-throughput genotyping. Here we evaluated the applicability of SNP markers developed from Crassostrea gigas and C. virginica expressed sequence tags (ESTs) in closely related Crassostrea and Ostrea species. A total of 213 putative interspecific level SNPs were identified from re-sequencing data in six amplicons, yielding on average of one interspecific level SNP per seven bp. High polymorphism levels were observed and the high success rate of transferability show that genic EST-derived SNP markers provide an efficient method for rapid marker development and SNP discovery in closely related oyster species. The six EST-SNP markers identified here will provide useful molecular tools for addressing questions in molecular ecology and evolution studies including for stock analysis (pedigree monitoring) in related oyster taxa.

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Striped catfish (Pangasianodon hypophthalmus) is a commercially important freshwater fish used in inland aquaculture in the Mekong Delta, Vietnam. The culture industry is facing a significant challenge however from saltwater intrusion into many low topographical coastal provinces across the Mekong Delta as a result of predicted climate change impacts. Developing genomic resources for this species can facilitate the production of improved culture lines that can withstand raised salinity conditions, and so we have applied high-throughput Ion Torrent sequencing of transcriptome libraries from six target osmoregulatory organs from striped catfish as a genomic resource for use in future selection strategies. We obtained 12,177,770 reads after trimming and processing with an average length of 97 bp. De novo assemblies were generated using CLC Genomic Workbench, Trinity and Velvet/Oases with the best overall contig performance resulting from the CLC assembly. De novo assembly using CLC yielded 66,451 contigs with an average length of 478 bp and N50 length of 506 bp. A total of 37,969 contigs (57%) possessed significant similarity with proteins in the non-redundant database. Comparative analyses revealed that a significant number of contigs matched sequences reported in other teleost fishes, ranging in similarity from 45.2% with Atlantic cod to 52% with zebrafish. In addition, 28,879 simple sequence repeats (SSRs) and 55,721 single nucleotide polymorphisms (SNPs) were detected in the striped catfish transcriptome. The sequence collection generated in the current study represents the most comprehensive genomic resource for P. hypophthalmus available to date. Our results illustrate the utility of next-generation sequencing as an efficient tool for constructing a large genomic database for marker development in non-model species.

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The possibility to selectively modulate the charge carrier transport in semiconducting materials is extremely challenging for the development of high performance and low-power consuming logic circuits. Systematical control over the polarity (electrons and holes) in transistor based on solution processed layer by layer polymer/graphene oxide hybrid system has been demonstrated. The conversion degree of the polarity is well controlled and reversible by trapping the opposite carriers. Basically, an electron device is switched to be a hole only device or vice versa. Finally, a hybrid layer ambipolar inverter is demonstrated in which almost no leakage of opposite carrier is found. This hybrid material has wide range of applications in planar p-n junctions and logic circuits for high-throughput manufacturing of printed electronic circuits.

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This article corrects: Brief Report: High-Throughput Sequencing of IL23R Reveals a Low-Frequency, Nonsynonymous Single-Nucleotide Polymorphism That Is Associated With Ankylosing Spondylitis in a Han Chinese Population Vol. 65, Issue 7, 1747–1752, Article first published online: 2 JUL 2013

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Antigen selection of B cells within the germinal center reaction generally leads to the accumulation of replacement mutations in the complementarity-determining regions (CDRs) of immunoglobulin genes. Studies of mutations in IgE-associated VDJ gene sequences have cast doubt on the role of antigen selection in the evolution of the human IgE response, and it may be that selection for high affinity antibodies is a feature of some but not all allergic diseases. The severity of IgE-mediated anaphylaxis is such that it could result from higher affinity IgE antibodies. We therefore investigated IGHV mutations in IgE-associated sequences derived from ten individuals with a history of anaphylactic reactions to bee or wasp venom or peanut allergens. IgG sequences, which more certainly experience antigen selection, served as a control dataset. A total of 6025 unique IgE and 5396 unique IgG sequences were generated using high throughput 454 pyrosequencing. The proportion of replacement mutations seen in the CDRs of the IgG dataset was significantly higher than that of the IgE dataset, and the IgE sequences showed little evidence of antigen selection. To exclude the possibility that 454 errors had compromised analysis, rigorous filtering of the datasets led to datasets of 90 core IgE sequences and 411 IgG sequences. These sequences were present as both forward and reverse reads, and so were most unlikely to include sequencing errors. The filtered datasets confirmed that antigen selection plays a greater role in the evolution of IgG sequences than of IgE sequences derived from the study participants.

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The advent of high-throughput SNP genotyping methods has advanced research into the genetics of common complex genetic diseases such as ankylosing spondylitis (AS) rapidly in recent times. The identification of associations with the genes IL23R and ERAP1 have been robustly replicated, and advances have been made in studies of the major histocompatibility complex genetics of AS, and of KIR gene variants and the disease. The findings are already being translated into increased understanding of the immunological pathways involved in AS, and raising novel potential therapies. The current studies in AS remain underpowered, and no full genomewide association study has yet been reported in AS; such studies are likely to add to the significant advances that have already been made.

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Osteoporosis and disorders of bone fragility are highly heritable, but despite much effort the identities of few of the genes involved has been established. Recent developments in genetics such as genome-wide association studies are revolutionizing research in this field, and it is likely that further contributions will be made through application of next-generation sequencing technologies, analysis of copy number variation polymorphisms, and high-throughput mouse mutagenesis programs. This article outlines what we know about osteoporosis genetics to date and the probable future directions of research in this field.

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There is a growing need for new biodiagnostics that combine high throughput with enhanced spatial resolution and sensitivity. Gold nanoparticle (NP) assemblies with sub-10 nm particle spacing have the benefits of improving detection sensitivity via Surface enhanced Raman scattering (SERS) and being of potential use in biomedicine due to their colloidal stability. A promising and versatile approach to form solution-stable NP assemblies involves the use of multi-branched molecular linkers which allows tailoring of the assembly size, hot-spot density and interparticle distance. We have shown that linkers with multiple anchoring end-groups can be successfully employed as a linker to assemble gold NPs into dimers, linear NP chains and clustered NP assemblies. These NP assemblies with diameters of 30-120 nm are stable in solution and perform better as SERS substrates compared with single gold NPs, due to an increased hot-spot density. Thus, tailored gold NP assemblies are potential candidates for use as biomedical imaging agents. We observed that the hot-spot density and in-turn the SERS enhancement is a function of the linker polymer concentration and polymer architecture. New deep Raman techniques like Spatially Offset Raman Spectroscopy (SORS) have emerged that allow detection from beneath diffusely scattering opaque materials, including biological media such as animal tissue. We have been able to demonstrate that the gold NP assemblies could be detected from within both proteinaceous and high lipid containing animal tissue by employing a SORS technique with a backscattered geometry.

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Single nucleotide polymorphisms (SNPs) have been classically used for dissecting various human complex disorders using candidate gene studies. During the last decade, large scale SNP analysis i.e. genome-wide association studies (GWAS) have provided an agnostic approach to identify possible genetic loci associated with heterogeneous disease such as cancer susceptibility, prognosis of survival or drug response. Further, the advent of new technologies, including microarray based genotyping as well as high throughput next generation sequencing has opened new avenues for SNPs to be used in clinical practice. It is speculated that the utility of SNPs to understand the mechanisms, biology of variable drug response and ultimately treatment individualization based on the individual’s genome composition will be indispensable in the near future. In the current review, we discuss the advantages and disadvantages of the clinical utility of genetic variants in disease risk-prediction, prognosis, clinical outcome and pharmacogenomics. The lessons and challenges for the utility of SNP based biomarkers are also discussed, including the need for additional functional validation studies.

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Ankylosing spondylitis (AS), the prototypic seronegative arthropathy, is known to be highly heritable, with >90% of the risk of developing the disease determined genetically. As with most common heritable diseases, progress in identifying the genes involved using family-based or candidate gene approaches has been slow. The recent development of the genome-wide association study approach has revolutionized genetic studies of such diseases. Early studies in ankylosing spondylitis have produced two major breakthroughs in the identification of genes contributing roughly one third of the population attributable risk of the disease, and pointing directly to a potential therapy. These exciting findings highlight the potential of future more comprehensive genetic studies of determinants of disease risk and clinical manifestations, and are the biggest advance in our understanding of the causation of the disease since the discovery of the association with HLA-B27.

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We have developed and validated a semi-automated fluorescent method of genotyping human leucocyte antigen (HLA)-DRB1 alleles, HLA-DRB1*01-16, by multiplex primer extension reactions. This method is based on the extension of a primer that anneals immediately adjacent to the single-nucleotide polymorphism with fluorescent dideoxynucleotide triphosphates (minisequencing), followed by analysis on an ABI Prism 3700 capillary electrophoresis instrument. The validity of the method was confirmed by genotyping 261 individuals using both this method and polymerase chain reaction with sequence-specific primer (PCR-SSP) or sequencing and by demonstrating Mendelian inheritance of HLA-DRB1 alleles in families. Our method provides a rapid means of performing high-throughput HLA-DRB1 genotyping using only two PCR reactions followed by four multiplex primer extension reactions and PCR-SSP for some allele groups. In this article, we describe the method and discuss its advantages and limitations.

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This project established a large and well characterised prospective breast cancer DNA biobank and used this biobank to conduct genetic studies in breast cancer. The thesis presented the results of these high-throughput genotyping studies in two separate Australian Caucasian case-control populations and identified association between three novel genetic variants in microRNA genes and breast cancer risk.

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Recognizing similarities and deriving relationships among protein molecules is a fundamental requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison. Results: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. A comparison with other site matching algorithms is also presented. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless combined with chemical nature of amino acids. Conclusion: A new algorithm has been developed to compare binding sites in accurate, efficient and high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250(th) second for one comparison on a single processor. A parallel version on BlueGene has also been implemented.

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Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

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Uropathogenic Escherichia coli (UPEC) are the major cause of urinary tract infections. For successful colonisation of the urinary tract, UPEC employ multiple surface-exposed or secreted virulence factors, including adhesins and iron uptake systems. Whilst individual UPEC strains and their virulence factors have been the focus of extensive research, there have been no outer membrane (OM) proteomic studies based on large clinical UPEC collections, primarily due to limitations of traditional methods. In this study, a high-throughput method based on tandem mass-spectrometry of EDTA heat-induced outer membrane vesicles (OMVs) was developed for the characterisation of the UPEC surface-associated proteome. The method was applied to compare the OM proteome of fifty-four UPEC isolates, resulting in the identification of 8789 proteins, consisting of 619 unique proteins, which were subsequently interrogated for their subcellular origin, prevalence and homology to characterised virulence factors. Multiple distinct virulence-associated proteins were identified, including two novel putative iron uptake proteins, an uncharacterised type of chaperone-usher fimbriae and various highly prevalent hypothetical proteins. Our results give fundamental insight into the physiology of UPEC and provide a framework for understanding the composition of the UPEC OM proteome.