13 resultados para genome analysis

em Deakin Research Online - Australia


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Solving modern biological problems requires advanced computational methods. This book describes the application of well-established concepts and techniques from areas like data mining, machine learning, database technologies, and visualization techniques to problems like protein data analysis, genome analysis, and sequence databases. Chen has collected contributions from leading researchers in each area.

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Background: Constraint-based modeling of reconstructed genome-scale metabolic networks has been successfully applied on several microorganisms. In constraint-based modeling, in order to characterize all allowable phenotypes, network-based pathways, such as extreme pathways and elementary flux modes, are defined. However, as the scale of metabolic network rises, the number of extreme pathways and elementary flux modes increases exponentially. Uniform random sampling solves this problem to some extent to study the contents of the available phenotypes. After uniform random sampling, correlated reaction sets can be identified by the dependencies between reactions derived from sample phenotypes. In this paper, we study the relationship between extreme pathways and correlated reaction sets.

Results: Correlated reaction sets are identified for E. coli core, red blood cell and Saccharomyces cerevisiae metabolic networks respectively. All extreme pathways are enumerated for the former two metabolic networks. As for Saccharomyces cerevisiae metabolic network, because of the large scale, we get a set of extreme pathways by sampling the whole extreme pathway space. In most cases, an extreme pathway covers a correlated reaction set in an 'all or none' manner, which means either all reactions in a correlated reaction set or none is used by some extreme pathway. In rare cases, besides the 'all or none' manner, a correlated reaction set may be fully covered by combination of a few extreme pathways with related function, which may bring redundancy and flexibility to improve the survivability of a cell. In a word, extreme pathways show strong complementary relationship on usage of reactions in the same correlated reaction set.

Conclusion: Both extreme pathways and correlated reaction sets are derived from the topology information of metabolic networks. The strong relationship between correlated reaction sets and extreme pathways suggests a possible mechanism: as a controllable unit, an extreme pathway is regulated by its corresponding correlated reaction sets, and a correlated reaction set is further regulated by the organism's regulatory network.

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Databases of mutations causing Mendelian disease play a crucial role in research, diagnostic and genetic health care and can play a role in life and death decisions. These databases are thus heavily used, but only gene or locus specific databases have been previously reviewed for completeness, accuracy, currency and utility. We have performed a review of the various general mutation databases that derive their data from the published literature and locus specific databases. Only two—the Human Gene Mutation Database (HGMD) and Online Mendelian Inheritance in Man (OMIM)—had useful numbers of mutations. Comparison of a number of characteristics of these databases indicated substantial inconsistencies between the two databases that included absent genes and missing mutations. This situation strengthens the case for gene specific curation of mutations and the need for an overall plan for collection, curation, storage and release of mutation data.

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Malaria is a major human health problem and is responsible for over 2 million deaths per year. It is caused by a number of species of the genus Plasmodium, and Plasmodium falciparum is the causative agent of the most lethal form. Consequently, the development of a vaccine against this parasite is a priority. There are a number of stages of the parasite life cycle that are being targeted for the development of vaccines. Important candidate antigens include proteins on the surface of the asexual merozoite stage, the form that invades the host erythrocyte. The development of methods to manipulate the genome of Plasmodium species has enabled the construction of gain-of-function and loss-of-function mutants and provided new strategies to analyse the role of parasite proteins. This has provided new information on the role of merozoite antigens in erythrocyte invasion and also allows new approaches to address their potential as vaccine candidates.

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All retroviruses contain two copies of genomic RNA that are linked noncovalently. The dimeric RNA of human immunodeficiency virus type 1 (HIV-1) undergoes rearrangement during virion maturation, whereby the dimeric RNA genome assumes a more stable conformation. Previously, we have shown that the packaging of the HIV-1 polymerase (Pol) proteins reverse transcriptase (RT) and integrase (IN) is essential for the generation of the mature RNA dimer conformation. Analysis of HIV-1 mutants that are defective in processing of Pol showed that these mutant virions contained altered dimeric RNA conformation, indicating that the mature RNA dimer conformation in HIV-1 requires the correct proteolytic processing of Pol. The HIV-1 Pol proteins are multimeric in their mature enzymatically active forms; RT forms a heterodimer, and IN appears to form a homotetramer. Using RT and IN multimerization defective mutants, we have found that dimeric RNA from these mutant virions has the same stability and conformation as wild-type RNA dimers, showing that the mature enzymatically active RT and IN proteins are dispensable for the generation of mature RNA dimer conformation. This also indicated that formation of the mature RNA dimer structure occurs prior to RT or IN maturation. We have also investigated the requirement of Pol for RNA dimerization in both Mason-Pfizer monkey virus (M-PMV) and Moloney murine leukemia virus (MoMuLV) and found that in contrast to HIV-1, Pol is dispensable for RNA dimer maturation in M-PMV and MoMuLV, demonstrating that the requirement of Pol in retroviral RNA dimer maturation is not conserved among all retroviruses.

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Retroviral recombination drives viral diversity and facilitates the emergence of immune escape and drug resistant mutants that contribute to disease progression. Current estimates of retroviral recombination rates are based on indirect measurements that do not take into account the effects of multiple recombination events. In the presence of multiple template switches, any even number of template switches result in no observed recombination and any odd number is detected as a single recombination event. We demonstrate that ignoring multiple recombination events consistently underestimates the true recombination rate, especially over large genetic distances and high rates of recombination. Here, we present a novel approach to measure rates of recombination across different gene segments regardless of the effects of genetic distance and the overall rate of recombination. We apply these tools to a novel HIV-1 marker system, which mimics the recombination process between closely related genomes, analogous to those found within the quasispecies of an infected individual. We directly measure the recombination rate in gag, correcting for the effects of multiple template switches and background recombination. Furthermore, our analysis indicates that recombination rates are likely to vary across the viral genome. This system is applicable to other studies to accurately measure the recombination rate that is critical for the diversification of retroviruses.

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BACKGROUND : The pigeon crop is specially adapted to produce milk that is fed to newly hatched young. The process of pigeon milk production begins when the germinal cell layer of the crop rapidly proliferates in response to prolactin, which results in a mass of epithelial cells that are sloughed from the crop and regurgitated to the young. We proposed that the evolution of pigeon milk built upon the ability of avian keratinocytes to accumulate intracellular neutral lipids during the cornification of the epidermis. However, this cornification process in the pigeon crop has not been characterised. RESULTS: We identified the epidermal differentiation complex in the draft pigeon genome scaffold and found that, like the chicken, it contained beta-keratin genes. These beta-keratin genes can be classified, based on sequence similarity, into several clusters including feather, scale and claw keratins. The cornified cells of the pigeon crop express several cornification-associated genes including cornulin, S100-A9 and A16-like, transglutaminase 6-like and the pigeon 'lactating' crop-specific annexin cp35. Beta-keratins play an important role in 'lactating' crop, with several claw and scale keratins up-regulated. Additionally, transglutaminase 5 and differential splice variants of transglutaminase 4 are up-regulated along with S100-A10. CONCLUSIONS: This study of global gene expression in the crop has expanded our knowledge of pigeon milk production, in particular, the mechanism of cornification and lipid production. It is a highly specialised process that utilises the normal keratinocyte cellular processes to produce a targeted nutrient solution for the young at a very high turnover.

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Ionizing radiation (IR)-induced DNA double-strand breaks (DSBs) can lead to cell death, genome instability and carcinogenesis. Immunofluorescence detection of phosphorylated histone variant H2AX (γ-H2AX) is a reliable and sensitive technique to monitor external beam IR-induced DSBs in peripheral blood lymphocytes (PBL). Here, we investigated whether γ-H2AX could be used as an in vivo marker to assess normal tissue toxicity after extended internal irradiation with (177)Lu-DOTA-octreotate peptide receptor radionuclide therapy (LuTate PRRT) of neuroendocrine tumors.

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Abstract
Background: Coronary artery disease (CAD), one of the leading causes of death globally, is influenced by both environmental and genetic risk factors. Gene-centric genome-wide association studies (GWAS) involving cases and controls have been remarkably successful in identifying genetic loci contributing to CAD. Modern in silico platforms, such as candidate gene prediction tools, permit a systematic analysis of GWAS data to identify candidate genes for complex diseases like CAD. Subsequent integration of drug-target data from drug databases with the predicted candidate genes can potentially identify novel therapeutics suitable for repositioning towards treatment of CAD.
Methods: Previously, we were able to predict 264 candidate genes and 104 potential therapeutic targets for CAD using Gentrepid (www.gentrepid.org), a candidate gene prediction platform with two bioinformatic modules to reanalyze Wellcome Trust Case-Control Consortium GWAS data. In an expanded study, using five bioinformatics modules on the same data, Gentrepid predicted 647 candidate genes and successfully replicated 55% of the candidate genes identified by the more powerful CARDIoGRAMplusC4D consortium meta-analysis. Hence, Gentrepid was capable of enhancing lower quality genotype-phenotype data, using an independent knowledgebase of existing biological data. Here, we used our methodology to integrate drug data from three drug databases: the Therapeutic Target Database, PharmGKB and Drug Bank, with the 647 candidate gene predictions from Gentrepid. We utilized known CAD targets, the scientific literature, existing drug data and the CARDIoGRAMplusC4D meta-analysis study as benchmarks to validate Gentrepid predictions for CAD.
Results: Our analysis identified a total of 184 predicted candidate genes as novel therapeutic targets for CAD, and 981 novel therapeutics feasible for repositioning in clinical trials towards treatment of CAD. The benchmarks based on known CAD targets and the scientific literature showed that our results were significant (p < 0.05).
Conclusions: We have demonstrated that available drugs may potentially be repositioned as novel therapeutics for the treatment of CAD. Drug repositioning can save valuable time and money spent on preclinical and phase I clinical studies.

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BACKGROUND: Strand specific RNAseq data is now more common in RNAseq projects. Visualizing RNAseq data has become an important matter in Analysis of sequencing data. The most widely used visualization tool is the UCSC genome browser that introduced the custom track concept that enabled researchers to simultaneously visualize gene expression at a particular locus from multiple experiments. Our objective of the software tool is to provide friendly interface for visualization of RNAseq datasets.

RESULTS: This paper introduces a visualization tool (RNASeqBrowser) that incorporates and extends the functionality of the UCSC genome browser. For example, RNASeqBrowser simultaneously displays read coverage, SNPs, InDels and raw read tracks with other BED and wiggle tracks -- all being dynamically built from the BAM file. Paired reads are also connected in the browser to enable easier identification of novel exon/intron borders and chimaeric transcripts. Strand specific RNAseq data is also supported by RNASeqBrowser that displays reads above (positive strand transcript) or below (negative strand transcripts) a central line. Finally, RNASeqBrowser was designed for ease of use for users with few bioinformatic skills, and incorporates the features of many genome browsers into one platform.

CONCLUSIONS: The features of RNASeqBrowser: (1) RNASeqBrowser integrates UCSC genome browser and NGS visualization tools such as IGV. It extends the functionality of the UCSC genome browser by adding several new types of tracks to show NGS data such as individual raw reads, SNPs and InDels. (2) RNASeqBrowser can dynamically generate RNA secondary structure. It is useful for identifying non-coding RNA such as miRNA. (3) Overlaying NGS wiggle data is helpful in displaying differential expression and is simple to implement in RNASeqBrowser. (4) NGS data accumulates a lot of raw reads. Thus, RNASeqBrowser collapses exact duplicate reads to reduce visualization space. Normal PC's can show many windows of NGS individual raw reads without much delay. (5) Multiple popup windows of individual raw reads provide users with more viewing space. This avoids existing approaches (such as IGV) which squeeze all raw reads into one window. This will be helpful for visualizing multiple datasets simultaneously. RNASeqBrowser and its manual are freely available at http://www.australianprostatecentre.org/research/software/rnaseqbrowser or http://sourceforge.net/projects/rnaseqbrowser/.

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BACKGROUND: Koalas (Phascolarctos cinereus), an iconic Australian marsupial, are being heavily impacted by the spread of Chlamydia pecorum, an obligate intracellular bacterial pathogen. Koalas vary in their response to this pathogen, with some showing no symptoms, while others suffer severe symptoms leading to infertility, blindness or death. Little is known about the pathology of this disease and the immune response against it in this host. Studies have demonstrated that natural killer (NK) cells, key components of the innate immune system, are involved in the immune response to chlamydial infections in humans. These cells can directly lyse cells infected by intracellular pathogens and their ability to recognise these infected cells is mediated through NK receptors on their surface. These are encoded in two regions of the genome, the leukocyte receptor complex (LRC) and the natural killer complex (NKC). These two families evolve rapidly and different repertoires of genes, which have evolved by gene duplication, are seen in different species. METHODS: In this study we aimed to characterise genes belonging to the NK receptor clusters in the koala by searching available koala transcriptomes using a combination of search methods. We developed a qPCR assay to quantify relative expression of four genes, two encoded within the NK receptor cluster (CLEC1B, CLEC4E) and two known to play a role in NK response to Chalmydia in humans (NCR3, PRF1). RESULTS: We found that the NK receptor repertoire of the koala closely resembles that of the Tasmanian devil, with minimal genes in the NKC, but with lineage specific expansions in the LRC. Additional genes important for NK cell activity, NCR3 and PRF1, were also identified and characterised. In a preliminary study to investigate whether these genes are involved in the koala immune response to infection by its chlamydial pathogen, C. pecorum, we investigated the expression of four genes in koalas with active chlamydia infection, those with past infection and those without infection using qPCR. This analysis revealed that one of these four, CLEC4E, may be upregulated in response to chlamydia infection. CONCLUSION: We have characterised genes of the NKC and LRC in koalas and have discovered evidence that one of these genes may be upregulated in koalas with chlamydia, suggesting that these receptors may play a role in the immune response of koalas to chlamydia infection.