308 resultados para Genome resources


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This report provides an overview of the results of a collaborative research project titled "A model for research supervision of international students in engineering and information technology disciplines". This project aimed to identify factors influencing the success of culturally and linguistically diverse (CALD) higher degree research (HDR) students in the fields of Engineering and Information Technology at three Australian Universities: Queensland University of Technology, The University of Western Australia and Curtin University.

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Complementary sequences at the 5′ and 3′ ends of the dengue virus RNA genome are essential for viral replication, and are believed to cyclise the genome through long-range base pairing in cis. Although consistent with evidence in the literature, this view neglects possible biologically active multimeric forms that are equally consistent with the data. Here, we propose alternative multimeric structures, and suggest that multigenome noncovalent concatemers are more likely to exist under cellular conditions than single cyclised monomers. Concatemers provide a plausible mechanism for the dengue virus to overcome the single-stranded (+)-sense RNA virus dilemma, and can potentially assist genome transport from the virus-induced vesicles into the cytosol.

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Using a sociological approach, this study examines China’s reform of open educational resources (OER), which has prompted significant changes to the nation’s higher education sector. Through an analysis of the policy processes that have driven the reform, this study demonstrates that the reform has involved and brought significant changes to its participants as resource administrators, providers, and receivers. By using governmentality as a poststructuralist analytical framework, this study shows the particular ways in which the reform process has been governed and the ways in which the governing practices have changed the conduct of higher education. The study reveals the power relations exercised through the reform and offers a critique of China’s higher education sector.

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This paper presents an approach to assess the resilience of a water supply system under the impacts of climate change. Changes to climate characteristics such as rainfall, evapotranspiration and temperature can result in changes to the global hydrological cycle and thereby adversely impact on the ability of water supply systems to meet service standards in the future. Changes to the frequency and characteristics of floods and droughts as well as the quality of water provided by groundwater and surface water resources are the other consequences of climate change that will affect water supply system functionality. The extent and significance of these changes underline the necessity for assessing the future functionality of water supply systems under the impacts of climate change. Resilience can be a tool for assessing the ability of a water supply system to meet service standards under the future climate conditions. The study approach is based on defining resilience as the ability of a system to absorb pressure without going into failure state as well as its ability to achieve an acceptable level of function quickly after failure. In order to present this definition in the form of a mathematical function, a surrogate measure of resilience has been proposed in this paper. In addition, a step-by-step approach to estimate resilience of water storage reservoirs is presented. This approach will enable a comprehensive understanding of the functioning of a water storage reservoir under future climate scenarios and can also be a robust tool to predict future challenges faced by water supply systems under the consequence of climate change.

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Often voltage rise along low voltage (LV) networks limits their capacity to accommodate more renewable energy (RE) sources. This paper proposes a robust and effective approach to coordinate customers' resources and control voltage rise in LV networks, where photovoltaics (PVs) are considered as the RE sources. The proposed coordination algorithm includes both localized and distributed control strategies. The localized strategy determines the value of PV inverter active and reactive power, while the distributed strategy coordinates customers' energy storage units (ESUs). To verify the effectiveness of proposed approach, a typical residential LV network is used and simulated in the PSCAD-EMTC platform.

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Severe power quality problems can arise when a large number of single-phase distributed energy resources (DERs) are connected to a low-voltage power distribution system. Due to the random location and size of DERs, it may so happen that a particular phase generates excess power than its load demand. In such an event, the excess power will be fed back to the distribution substation and will eventually find its way to the transmission network, causing undesirable voltage-current unbalance. As a solution to this problem, the article proposes the use of a distribution static compensator (DSTATCOM), which regulates voltage at the point of common coupling (PCC), thereby ensuring balanced current flow from and to the distribution substation. Additionally, this device can also support the distribution network in the absence of the utility connection, making the distribution system work as a microgrid. The proposals are validated through extensive digital computer simulation studies using PSCADTM

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Migraine is a common neurological disease with a complex genetic aetiology. The disease affects ~12% of the Caucasian population and females are three times more likely than males to be diagnosed. In an effort to identify loci involved in migraine susceptibility, we performed a pedigree-based genome-wide association study of the isolated population of Norfolk Island, which has a high prevalence of migraine. This unique population originates from a small number of British and Polynesian founders who are descendents of the Bounty mutiny and forms a very large multigenerational pedigree (Bellis et al.; Human Genetics, 124(5):543-5542, 2008). These population genetic features may facilitate disease gene mapping strategies (Peltonen et al.; Nat Rev Genet, 1(3):182-90, 2000. In this study, we identified a high heritability of migraine in the Norfolk Island population (h (2) = 0.53, P = 0.016). We performed a pedigree-based GWAS and utilised a statistical and pathological prioritisation approach to implicate a number of variants in migraine. An SNP located in the zinc finger protein 555 (ZNF555) gene (rs4807347) showed evidence of statistical association in our Norfolk Island pedigree (P = 9.6 × 10(-6)) as well as replication in a large independent and unrelated cohort with >500 migraineurs. In addition, we utilised a biological prioritisation to implicate four SNPs, in within the ADARB2 gene, two SNPs within the GRM7 gene and a single SNP in close proximity to a HTR7 gene. Association of SNPs within these neurotransmitter-related genes suggests a disrupted serotoninergic system that is perhaps specific to the Norfolk Island pedigree, but that might provide clues to understanding migraine more generally.

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The high risk of metabolic disease traits in Polynesians may be partly explained by elevated prevalence of genetic variants involved in energy metabolism. The genetics of Polynesian populations has been shaped by island hoping migration events which have possibly favoured thrifty genes. The aim of this study was to sequence the mitochondrial genome in a group of Maoris in an effort to characterise genome variation in this Polynesian population for use in future disease association studies. We sequenced the complete mitochondrial genomes of 20 non-admixed Maori subjects using Affymetrix technology. DNA diversity analyses showed the Maori group exhibited reduced mitochondrial genome diversity compared to other worldwide populations, which is consistent with historical bottleneck and founder effects. Global phylogenetic analysis positioned these Maori subjects specifically within mitochondrial haplogroup - B4a1a1. Interestingly, we identified several novel variants that collectively form new and unique Maori motifs – B4a1a1c, B4a1a1a3 and B4a1a1a5. Compared to ancestral populations we observed an increased frequency of non-synonymous coding variants of several mitochondrial genes in the Maori group, which may be a result of positive selection and/or genetic drift effects. In conclusion, this study reports the first complete mitochondrial genome sequence data for a Maori population. Overall, these new data reveal novel mitochondrial genome signatures in this Polynesian population and enhance the phylogenetic picture of maternal ancestry in Oceania. The increased frequency of several mitochondrial coding variants makes them good candidates for future studies aimed at assessment of metabolic disease risk in Polynesian populations.

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Migraine is a common neurovascular disorder with a complex envirogenomic aetiology. In an effort to identify migraine susceptibility genes, we conducted a study of the isolated population of Norfolk Island, Australia. A large portion of the permanent inhabitants of Norfolk Island are descended from 18th Century English sailors involved in the infamous mutiny on the Bounty and their Polynesian consorts. In total, 600 subjects were recruited including a large pedigree of 377 individuals with lineage to the founders. All individuals were phenotyped for migraine using International Classification of Headache Disorders-II criterion. All subjects were genotyped for a genome-wide panel of microsatellite markers. Genotype and phenotype data for the pedigree were analysed using heritability and linkage methods implemented in the programme SOLAR. Follow-up association analysis was performed using the CLUMP programme. A total of 154 migraine cases (25%) were identified indicating the Norfolk Island population is high-risk for migraine. Heritability estimation of the 377-member pedigree indicated a significant genetic component for migraine (h2 = 0.53, P = 0.016). Linkage analysis showed peaks on chromosome 13q33.1 (P = 0.003) and chromosome 9q22.32 (P = 0.008). Association analysis of the key microsatellites in the remaining 223 unrelated Norfolk Island individuals showed evidence of association, which strengthen support for the linkage findings (P ≤ 0.05). In conclusion, a genome-wide linkage analysis and follow-up association analysis of migraine in the genetic isolate of Norfolk Island provided evidence for migraine susceptibility loci on chromosomes 9q22.22 and 13q33.1.

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Background Illumina's Infinium SNP BeadChips are extensively used in both small and large-scale genetic studies. A fundamental step in any analysis is the processing of raw allele A and allele B intensities from each SNP into genotype calls (AA, AB, BB). Various algorithms which make use of different statistical models are available for this task. We compare four methods (GenCall, Illuminus, GenoSNP and CRLMM) on data where the true genotypes are known in advance and data from a recently published genome-wide association study. Results In general, differences in accuracy are relatively small between the methods evaluated, although CRLMM and GenoSNP were found to consistently outperform GenCall. The performance of Illuminus is heavily dependent on sample size, with lower no call rates and improved accuracy as the number of samples available increases. For X chromosome SNPs, methods with sex-dependent models (Illuminus, CRLMM) perform better than methods which ignore gender information (GenCall, GenoSNP). We observe that CRLMM and GenoSNP are more accurate at calling SNPs with low minor allele frequency than GenCall or Illuminus. The sample quality metrics from each of the four methods were found to have a high level of agreement at flagging samples with unusual signal characteristics. Conclusions CRLMM, GenoSNP and GenCall can be applied with confidence in studies of any size, as their performance was shown to be invariant to the number of samples available. Illuminus on the other hand requires a larger number of samples to achieve comparable levels of accuracy and its use in smaller studies (50 or fewer individuals) is not recommended.

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Migraine is a common, heterogeneous and heritable neurological disorder. Its pathophysiology is incompletely understood, and its genetic influences at the population level are unknown. In a population-based genome-wide analysis including 5,122 migraineurs and 18,108 non-migraineurs, rs2651899 (1p36.32, PRDM16), rs10166942 (2q37.1, TRPM8) and rs11172113 (12q13.3, LRP1) were among the top seven associations (P < 5 × 10(-6)) with migraine. These SNPs were significant in a meta-analysis among three replication cohorts and met genome-wide significance in a meta-analysis combining the discovery and replication cohorts (rs2651899, odds ratio (OR) = 1.11, P = 3.8 × 10(-9); rs10166942, OR = 0.85, P = 5.5 × 10(-12); and rs11172113, OR = 0.90, P = 4.3 × 10(-9)). The associations at rs2651899 and rs10166942 were specific for migraine compared with non-migraine headache. None of the three SNP associations was preferential for migraine with aura or without aura, nor were any associations specific for migraine features. TRPM8 has been the focus of neuropathic pain models, whereas LRP1 modulates neuronal glutamate signaling, plausibly linking both genes to migraine pathophysiology.

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Objective: To perform a 1-stage meta-analysis of genome-wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci. Methods: We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta-analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease. Results: We meta-analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934T at 3p24.1 (odds ratio [OR], 1.17; p ¼ 1.6 � 10�8) near EOMES, rs2150702G in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p ¼ 3.3 � 10�8), and rs6718520A in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p ¼ 3.4 � 10�8). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 � 10�6, some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1). Interpretation: We have performed a meta-analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS.

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Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

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To identify multiple sclerosis (MS) susceptibility loci, we conducted a genome-wide association study (GWAS) in 1,618 cases and used shared data for 3,413 controls. We performed replication in an independent set of 2,256 cases and 2,310 controls, for a total of 3,874 cases and 5,723 controls. We identified risk-associated SNPs on chromosome 12q13-14 (rs703842, P = 5.4 x 10(-11); rs10876994, P = 2.7 x 10(-10); rs12368653, P = 1.0 x 10(-7)) and upstream of CD40 on chromosome 20q13 (rs6074022, P = 1.3 x 10(-7); rs1569723, P = 2.9 x 10(-7)). Both loci are also associated with other autoimmune diseases. We also replicated several known MS associations (HLA-DR15, P = 7.0 x 10(-184); CD58, P = 9.6 x 10(-8); EVI5-RPL5, P = 2.5 x 10(-6); IL2RA, P = 7.4 x 10(-6); CLEC16A, P = 1.1 x 10(-4); IL7R, P = 1.3 x 10(-3); TYK2, P = 3.5 x 10(-3)) and observed a statistical interaction between SNPs in EVI5-RPL5 and HLA-DR15 (P = 0.001).