888 resultados para Genome Sequence


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OBJECTIVES: To locate the acquired bla(OXA-23) carbapenem resistance gene in an Australian A. baumannii global clone 1 (GC1) isolate. METHODS: The genome of the extensively antibiotic-resistant GC1 isolate A85 harbouring bla(OXA-23) in Tn2006 was sequenced using Illumina HiSeq, and the reads were used to generate a de novo assembly. PCR was used to assemble relevant contigs. Sequences were compared with ones in GenBank. Conjugation experiments were conducted. RESULTS: The sporadic GC1 isolate A85, recovered in 2003, was extensively resistant, exhibiting resistance to imipenem, meropenem and ticarcillin/clavulanate, to cephalosporins and fluoroquinolones and to the older antibiotics gentamicin, kanamycin and neomycin, sulfamethoxazole, trimethoprim and tetracycline. Genes for resistance to older antibiotics are in the chromosome, in an AbaR3 resistance island. A second copy of the ampC gene in Tn6168 confers cephalosporin resistance and the gyrA and parC genes have mutations leading to fluoroquinolone resistance. An 86 335 bp repAci6 plasmid, pA85-3, carrying bla(OXA-23) in Tn2006 in AbaR4, was shown to transfer imipenem, meropenem and ticarcillin/clavulanate resistance into a susceptible recipient. A85 also contains two small cryptic plasmids of 2.7 and 8.7 kb. A85 is sequence type ST126 (Oxford scheme) and carries a novel KL15 capsule locus and the OCL3 outer core locus. CONCLUSIONS: A85 represents a new GC1 lineage identified by the novel capsule locus but retains AbaR3 carrying genes for resistance to older antibiotics. Resistance to imipenem, meropenem and ticarcillin/clavulanate has been introduced into A85 by pA85-3, a repAci6 conjugative plasmid carrying Tn2006 in AbaR4.

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The genomics era provides opportunities to assess the genetic overlap across phenotypes at the measured genotype level; however, current approaches require individual-level genome-wide association (GWA) single nucleotide polymorphism (SNP) genotype data in one or both of a pair of GWA samples. To facilitate the discovery of pleiotropic effects and examine genetic overlap across two phenotypes, I have developed a user-friendly web-based application called SECA to perform SNP effect concordance analysis using GWA summary results. The method is validated using publicly available summary data from the Psychiatric Genomics Consortium.

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Genetic factors contribute to risk of many common diseases affecting reproduction and fertility. In recent years, methods for genome-wide association studies(GWAS) have revolutionized gene discovery forcommontraits and diseases. Results of GWAS are documented in the Catalog of Published Genome-Wide Association Studies at the National Human Genome Research Institute and report over 70 publications for 32 traits and diseases associated with reproduction. These include endometriosis, uterine fibroids, age at menarche and age at menopause. Results that pass appropriate stringent levels of significance are generally well replicated in independent studies. Examples of genetic variation affecting twinning rate, infertility, endometriosis and age at menarche demonstrate that the spectrum of disease-related variants for reproductive traits is similar to most other common diseases.GWAS 'hits' provide novel insights into biological pathways and the translational value of these studies lies in discovery of novel gene targets for biomarkers, drug development and greater understanding of environmental factors contributing to disease risk. Results also show that genetic data can help define sub-types of disease and co-morbidity with other traits and diseases. To date, many studies on reproductive traits have used relatively small samples. Future genetic marker studies in large samples with detailed phenotypic and clinical information will yield new insights into disease risk, disease classification and co-morbidity for many diseases associated with reproduction and infertility.

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BACKGROUND Endometriosis is a heritable common gynaecological condition influenced by multiple genetic and environmental factors. Genome-wide association studies (GWASs) have proved successful in identifying common genetic variants of moderate effects for various complex diseases. To date, eight GWAS and replication studies from multiple populations have been published on endometriosis. In this review, we investigate the consistency and heterogeneity of the results across all the studies and their implications for an improved understanding of the aetiology of the condition. METHODS Meta-analyses were conducted on four GWASs and four replication studies including a total of 11 506 cases and 32 678 controls, and on the subset of studies that investigated associations for revised American Fertility Society (rAFS) Stage III/IV including 2859 cases. The datasets included 9039 cases and 27 343 controls of European (Australia, Belgium, Italy, UK, USA) and 2467 cases and 5335 controls of Japanese ancestry. Fixed and Han and Elkin random-effects models, and heterogeneity statistics (Cochran's Q test), were used to investigate the evidence of the nine reported genome-wide significant loci across datasets and populations. RESULTS Meta-analysis showed that seven out of nine loci had consistent directions of effect across studies and populations, and six out of nine remained genome-wide significant (P < 5 × 10(-8)), including rs12700667 on 7p15.2 (P = 1.6 × 10(-9)), rs7521902 near WNT4 (P = 1.8 × 10(-15)), rs10859871 near VEZT (P = 4.7 × 10(-15)), rs1537377 near CDKN2B-AS1 (P = 1.5 × 10(-8)), rs7739264 near ID4 (P = 6.2 × 10(-10)) and rs13394619 in GREB1 (P = 4.5 × 10(-8)). In addition to the six loci, two showed borderline genome-wide significant associations with Stage III/IV endometriosis, including rs1250248 in FN1 (P = 8 × 10(-8)) and rs4141819 on 2p14 (P = 9.2 × 10(-8)). Two independent inter-genic loci, rs4141819 and rs6734792 on chromosome 2, showed significant evidence of heterogeneity across datasets (P < 0.005). Eight of the nine loci had stronger effect sizes among Stage III/IV cases, implying that they are likely to be implicated in the development of moderate to severe, or ovarian, disease. While three out of nine loci were inter-genic, the remaining were in or near genes with known functions of biological relevance to endometriosis, varying from roles in developmental pathways to cellular growth/carcinogenesis. CONCLUSIONS Our meta-analysis shows remarkable consistency in endometriosis GWAS results across studies, with little evidence of population-based heterogeneity. They also show that the phenotypic classifications used in GWAS to date have been limited. Stronger associations with Stage III/IV disease observed for most loci emphasize the importance for future studies to include detailed sub-phenotype information. Functional studies in relevant tissues are needed to understand the effect of the variants on downstream biological pathways.

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In response to scientific breakthroughs in biotechnology, the development of new technologies, and the demands of a hungry capitalist marketplace, patent law has expanded to accommodate a range of biological inventions. There has been much academic and public debate as to whether gene patents have a positive impact upon research and development, health-care, and the protection of the environment. In a satire of prevailing patenting practices, the English poet and part-time casino waitress, Donna MacLean, sought a patent application - GB0000180.0 - in respect of herself. She explained that she had satisfied the usual patent criteria - in that she was novel, inventive, and useful: It has taken 30 years of hard labor for me to discover and invent myself, and now I wish to protect my invention from unauthorized exploitation, genetic or otherwise. I am new: I have led a private existence and I have not made the invention of myself public. I am not obvious (2000: 18). MacLean said she had many industrial applications. ’For example, my genes can be used in medical research to extremely profitable ends - I therefore wish to have sole control of my own genetic material' (2000: 18). She observed in an interview: ’There's a kind of unpleasant, grasping, greedy atmosphere at the moment around the mapping of the human genome ... I wanted to see if a human being could protect their own genes in law' (Meek, 2000). This special issue of Law in Context charts a new era in the long-standing debate over biological inventions. In the wake of the expansion of patentable subject matter, there has been great strain placed upon patent criteria - such as ’novelty', ’inventive step', and ’utility'. Furthermore, there has been a new focus upon legal doctrines which facilitate access to patented inventions - like the defence of experimental use, the ’Bolar' exception, patent pooling, and compulsory licensing. There has been a concerted effort to renew patent law with an infusion of ethical principles dealing with informed consent and benefit sharing. There has also been a backlash against the commercialisation of biological inventions, and a call by some activists for the abolition of patents on genetic inventions. This collection considers a wide range of biological inventions - ranging from micro-organisms, plants and flowers and transgenic animals to genes, express sequence tags, and research tools, as well as genetic diagnostic tests and pharmaceutical drugs. It is thus an important corrective to much policy work, which has been limited in its purview to merely gene patents and biomedical research. This collection compares and contrasts the various approaches of a number of jurisdictions to the legal problems in respect of biological inventions. In particular, it looks at the complexities of the 1998 European Union Directive on the Legal Protection of Biotechnological Inventions, as well as decisions of member states, such as the Netherlands, and peripheral states, like Iceland. The edition considers US jurisprudence on patent law and policy, as well as recent developments in Canada. It also focuses upon recent developments in Australia - especially in the wake of parallel policy inquiries into gene patents and access to genetic resources.

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Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

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The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

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Deficits in lentiform nucleus volume and morphometry are implicated in a number of genetically influenced disorders, including Parkinson's disease, schizophrenia, and ADHD. Here we performed genome-wide searches to discover common genetic variants associated with differences in lentiform nucleus volume in human populations. We assessed structural MRI scans of the brain in two large genotyped samples: the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 706) and the Queensland Twin Imaging Study (QTIM; N = 639). Statistics of association from each cohort were combined meta-analytically using a fixed-effects model to boost power and to reduce the prevalence of false positive findings. We identified a number of associations in and around the flavin-containing monooxygenase (FMO) gene cluster. The most highly associated SNP, rs1795240, was located in the FMO3 gene; after meta-analysis, it showed genome-wide significant evidence of association with lentiform nucleus volume (PMA = 4. 79 × 10-8). This commonly-carried genetic variant accounted for 2. 68 % and 0. 84 % of the trait variability in the ADNI and QTIM samples, respectively, even though the QTIM sample was on average 50 years younger. Pathway enrichment analysis revealed significant contributions of this gene to the cytochrome P450 pathway, which is involved in metabolizing numerous therapeutic drugs for pain, seizures, mania, depression, anxiety, and psychosis. The genetic variants we identified provide replicated, genome-wide significant evidence for the FMO gene cluster's involvement in lentiform nucleus volume differences in human populations.

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Large multisite efforts (e.g., the ENIGMA Consortium), have shown that neuroimaging traits including tract integrity (from DTI fractional anisotropy, FA) and subcortical volumes (from T1-weighted scans) are highly heritable and promising phenotypes for discovering genetic variants associated with brain structure. However, genetic correlations (rg) among measures from these different modalities for mapping the human genome to the brain remain unknown. Discovering these correlations can help map genetic and neuroanatomical pathways implicated in development and inherited risk for disease. We use structural equation models and a twin design to find rg between pairs of phenotypes extracted from DTI and MRI scans. When controlling for intracranial volume, the caudate as well as related measures from the limbic system - hippocampal volume - showed high rg with the cingulum FA. Using an unrelated sample and a Seemingly Unrelated Regression model for bivariate analysis of this connection, we show that a multivariate GWAS approach may be more promising for genetic discovery than a univariate approach applied to each trait separately.

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Human brain connectivity is disrupted in a wide range of disorders from Alzheimer's disease to autism but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain regions. We scanned a large twin cohort (N=366) with 4-Tesla high angular resolution diffusion imaging (105-gradient HARDI). Using whole brain HARDI tractography, we extracted a relatively sparse 70×70 matrix representing fiber density between all pairs of cortical regions automatically labeled in co-registered anatomical scans. Additive genetic factors accounted for 1-58% of the variance in connectivity between 90 (of 122) tested nodes. We discovered genome-wide significant associations between variants and connectivity. GWAS permutations at various levels of heritability, and split-sample replication, validated our genetic findings. The resulting genes may offer new leads for mechanisms influencing aberrant connectivity and neurodegeneration. © 2012 IEEE.

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Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, highangular resolution diffusion MRI. We adapted GWASs to screen the brain's connectivity pattern, allowing us to discover genetic variants that affect the human brain's wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer's disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

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Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes-PRDM16, PAX3, TP63, C5orf50, and COL17A1-in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

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The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10 -6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

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A phylogenetic hypothesis for the lepidopteran superfamily Noctuoidea was inferred based on the complete mitochondrial (mt) genomes of 12 species (six newly sequenced). The monophyly of each noctuoid family in the latest classification was well supported. Novel and robust relationships were recovered at the family level, in contrast to previous analyses using nuclear genes. Erebidae was recovered as sister to (Nolidae+(Euteliidae+Noctuidae)), while Notodontidae was sister to all these taxa (the putatively basalmost lineage Oenosandridae was not included). In order to improve phylogenetic resolution using mt genomes, various analytical approaches were tested: Bayesian inference (BI) vs. maximum likelihood (ML), excluding vs. including RNA genes (rRNA or tRNA), and Gblocks treatment. The evolutionary signal within mt genomes had low sensitivity to analytical changes. Inference methods had the most significant influence. Inclusion of tRNAs positively increased the congruence of topologies, while inclusion of rRNAs resulted in a range of phylogenetic relationships varying depending on other analytical factors. The two Gblocks parameter settings had opposite effects on nodal support between the two inference methods. The relaxed parameter (GBRA) resulted in higher support values in BI analyses, while the strict parameter (GBDH) resulted in higher support values in ML analyses.

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Sepsid flies (Diptera: Sepsidae) are important model insects for sexual selection research. In order to develop mitochondrial (mt) genome data for this significant group, we sequenced the first complete mt genome of the sepsid fly Nemopoda mamaevi Ozerov, 1997. The circular 15,878 bp mt genome is typical of Diptera, containing all 37 genes usually present in bilaterian animals. We discovered inaccurate annotations of fly mt genomes previously deposited on GenBank and thus re-annotated all published mt genomes of Cyclorrhapha. These re-annotations were based on comparative analysis of homologous genes, and provide a statistical analysis of start and stop codon positions. We further detected two 18 bp of conserved intergenic sequences from tRNAGlu-tRNAPhe and ND1-tRNASer(UCN) across Cyclorrhapha, which are the mtTERM binding site motifs. Additionally, we compared automated annotation software MITOS with hand annotation method. Phylogenetic trees based on the mt genome data from Cyclorrhapha were inferred by Maximum-likelihood and Bayesian methods, strongly supported a close relationship between Sepsidae and the Tephritoidea.