984 resultados para Genetic variations
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The red panda (Ailurus fulgens) is one of the flagship species in worldwide conservation and is of special interest in evolutionary studies due to its taxonomic uniqueness. We sequenced a 236-bp fragment of the mitochondrial D-loop region in a sample of 5
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Ordered gene problems are a very common classification of optimization problems. Because of their popularity countless algorithms have been developed in an attempt to find high quality solutions to the problems. It is also common to see many different types of problems reduced to ordered gene style problems as there are many popular heuristics and metaheuristics for them due to their popularity. Multiple ordered gene problems are studied, namely, the travelling salesman problem, bin packing problem, and graph colouring problem. In addition, two bioinformatics problems not traditionally seen as ordered gene problems are studied: DNA error correction and DNA fragment assembly. These problems are studied with multiple variations and combinations of heuristics and metaheuristics with two distinct types or representations. The majority of the algorithms are built around the Recentering- Restarting Genetic Algorithm. The algorithm variations were successful on all problems studied, and particularly for the two bioinformatics problems. For DNA Error Correction multiple cases were found with 100% of the codes being corrected. The algorithm variations were also able to beat all other state-of-the-art DNA Fragment Assemblers on 13 out of 16 benchmark problem instances.
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We investigated the color vision pattern in Cebus apella monkeys by means of electroretinogram measurements (ERG) and genetic analysis. Based on ERG we could discriminate among three types of dichromatic males. Among females, this classification is more complex and requires additional genetic analysis. We found five among 10 possible different phenotypes, two trichromats and three dichromats. We also found that Cebus present a new allele with spectral peak near 552 nm, with the amino acid combination SFT at positions 180, 277 and 285 of the opsin gene, in addition to the previously described SYT, AFT and AFA alleles. (C) 2009 Elsevier Ltd. All rights reserved.
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Prion diseases are characterized by the presence of the abnormal prion protein PrPSc, which is believed to be generated by the conversion of the α-helical structure that predominates in the normal PrP isoform into a β-sheet structure resistant to proteinase K (PK). In human prion diseases, two major types of PrPSc, type 1 and 2, can be distinguished based on the difference in electrophoretic migration of the PK-resistant core fragment. In this study, protein sequencing was used to identify the PK cleavage sites of PrPSc in 36 cases of prion diseases. We demonstrated two primary cleavage sites at residue 82 and residue 97 for type 1 and type 2 PrPSc, respectively, and numerous secondary cleavages distributed along the region spanning residues 74–102. Accordingly, we identify three regions in PrPSc: one N-terminal (residues 23–73) that is invariably PK-sensitive, one C-terminal (residues 103–231) that is invariably PK-resistant, and a third variable region (residues 74–102) where the site of the PK cleavage, likely reflecting the extent of the β-sheet structure, varies mostly as a function of the PrP genotype at codon 129.
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Multiple sclerosis (MS) is a chronic neurological disease characterized by central nervous system (CNS) inflammation and demyelination. The C677T substitution variant in the methylenetetrahydrofolate reductase (MTHFR) gene has been associated with increased levels of circulating homocysteine and is a mild risk factor for vascular disease. Higher blood levels of homocysteine have also been reported in MS. Thus, the C677T mutation of the MTHFR gene may influence MS susceptibility. Noradrenaline, a neurotransmitter believed to play an immunosupressive role in neuroinflammatory disorders, is catabolized by catechol-O-methyl transferase (COMT). The COMT G158A substitution results in a three- to four-fold decreased activity of the COMT enzyme, which may influence CNS synaptic catecholamine breakdown and could also play a role in MS inflammation. We tested DNA from Australian MS patients and unaffected control subjects, matched for gender, age and ethnicity. Specifically, we genotyped the MTHFR C677T and the COMT G158A mutations. Genotype distributions showed that the homozygous mutant MTHFR genotype (T/T) and the COMT (H/H) genotype were slightly over-represented in the MS group (16% versus 11% and 24% versus 19%, respectively), but both variations failed to reach statistical significance (P=0.15 and P=0.32, respectively). Hence, results from the present study do not support a major role for either functional gene mutation in MS susceptibility.
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Susceptibility to complex traits, by definition, involves aetiological polymorphisms at multiple genetic loci combined with variable contributions by environmental factors. However, the approaches taken to identifying genetic loci implicated in susceptibility to complex traits frequently overlooks the compounding contribution of multiple loci in favour of highlighting a single gene solely responsible for predisposition. It is only in a small minority of cases that this has resulted in clear disease heritability associated with polymorphisms in a single gene. More often, this approach has led to an accumulation of single-gene associations with minor contributions to disease susceptibility. As the genomic era advances and genome-wide screens become higher in resolution and throughput, the need for simultaneous consideration of multiple loci is becoming more important. With special reference to non-Hodgkin’s lymphoma (NHL), this chapter will overview the current progress made in elucidating genetic polymorphisms associated with disease susceptibility. We also present novel data from a high-resolution single nucleotide polymorphism (SNP) microarray screen for susceptibility loci that are involved in NHL. Using an ‘informed approach’, the findings are highlighted within the context of cellular pathways, and provide insight and new ideas for methods of analysis for genome-wide screens for susceptibility.
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Conjugation of chemicals with glutathione (GSH) can lead to decreased or increased toxicity. A genetic deficiency in the GSH S-transferase μ class gene M1 has been hypothesized to lead to greater risk of lung cancer in smokers. Recently a gene deletion polymorphism involving the human θ enzyme T1 has been described; the enzyme is present in erythrocytes and can be readily assayed. A rat θ class enzyme, 5-5, has structural and catalytic similarity and the protein was expressed in the Salmonella typhimurium tester strain TA1535. Expression of the cDNA vector increased the mutagenicity of ethylene dibromide and several methylene dihalides. Mutations resulting from the known GSH S-transferase substrate 1,2-epoxy-3-(4′nitrophenoxy)propane were decreased in the presence of the transferase. Expression of transferase 5-5 increased mutations when 1,2,3,4-diepoxybutane (butadiene diepoxide), 4-bromo-1,2-epoxybutane, or 1,3-dichloracetone were added. The latter compound is a model for the putative 1,2-dibromo-3-chloropropane oxidation product 1-bromo-3-chloroacetone. These genotoxicity and genotyping assays may be of use in further studies of the roles of GSH S-transferase θ enzymes in bioactivation and detoxication and any changes in risk due to polymorphism.
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Inherited genetic traits co-determine the susceptibility of an individual to a toxic chemical. Special emphasis has been put on individual responses to environmental and industrial carcinogens, but other chronic diseases are of increasing interest. Polymorphisms of relevant xenobiotic metabolising enzymes may be used as toxicological susceptibility markers. A growing number of genes encoding enzymes involved in biotransformation of toxicants and in cellular defence against toxicant-induced damage to the cells has been identified and cloned, leading to increased knowledge of allelic variants of genes and genetic defects that may result in a differential susceptibility toward environmental toxicants. "Low penetrating" polymorphisms in metabolism genes tend to be much more common in the population than allelic variants of "high penetrating" cancer genes, and are therefore of considerable importance from a public health point of view. Positive associations between cancer and CYP1A1 alleles, in particular the *2C I462V allele, were found for tissues following the aerodigestive tract. Again, in most cases, the effect of the variant CYP1A1 allele becomes apparent or clearer in connection with the GSTM1 null allele. The CYP1B1 codon 432 polymorphism (CYP1B1*3) has been identified as a susceptibility factor in smoking-related head-and-neck squameous cell cancer. The impact of this polymorphic variant of CYP1B1 on cancer risk was also reflected by an association with the frequency of somatic mutations of the p53 gene. Combined genotype analysis of CYP1B1 and the glutathione transferases GSTM1 or GSTT1 has also pointed to interactive effects. Of particular interest for the industrial and environmental field is the isozyme CYP2E1. Several genotypes of this isozyme have been characterised which seem to be associated with different levels of expression of enzyme activity. The acetylator status for NAT2 can be determined by genotyping or by phenotyping. In the pathogenesis of human bladder cancer due to occupational exposure to "classical" aromatic amines (benzidine, 4-aminodiphenyl, 1-naphthylamine) acetylation by NAT2 is regarded as a detoxication step. Interestingly, the underlying European findings of a higher susceptibility of slow acetylators towards aromatic amines are in contrast to findings in Chinese workers occupationally exposed to aromatic amines which points to different mechanisms of susceptibility between European and Chinese populations. Regarding human bladder cancer, the hypothesis has been put forward that genetic polymorphism of GSTM1 might be linked with the occurrence of this tumour type. This supports the hypothesis that exposure to PAH might causally be involved in urothelial cancers. The human polymorphic GST catalysing conjugation of halomethanes, dihalomethanes, ethylene oxide and a number of other industrial compounds could be characterised as a class theta enzyme (GSTT1) by means of molecular biology. "Conjugator" and "non-conjugator" phenotypes are coincident with the presence and absence of the GSTT1 gene. There are wide variations in the frequencies of GSTT1 deletion (GSTT1 *0/0) among different ethnicities. Human phenotyping is facilitated by the GST activity towards methyl bromide or ethylene oxide in erythrocytes which is representative of the metabolic GSTT1 competence of the entire organism. Inter-individual variations in xenobiotic metabolism capacities may be due to polymorphisms of the genes coding for the enzymes themselves or of the genes coding for the receptors or transcription factors which regulate the expression of the enzymes. Also, polymorphisms in several regions of genes may cause altered ligand affinity, transactivation activity or expression levels of the receptor subsequently influencing the expression of the downstream target genes. Studies of individual susceptibility to toxicants and gene-environment interaction are now emerging as an important component of molecular epidemiology.
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Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.
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Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.
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Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R 2 = 0.055, p = 2.1 × 10 -7) and with IQ in the entire sample (R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk. © Cambridge University Press 2013.
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Copy number variations (CNVs) as described in the healthy population are purported to contribute significantly to genetic heterogeneity. Recent studies have described CNVs using lymphoblastoid cell lines or by application of specifically developed algorithms to interrogate previously described data. However, the full extent of CNVs remains unclear. Using high-density SNP array, we have undertaken a comprehensive investigation of chromosome 18 for CNV discovery and characterisation of distribution and association with chromosome architecture. We identified 399 CNVs, of which loss represents 98%, 58% are less than 2.5 kb in size and 71% are intergenic. Intronic deletions account for the majority of copy number changes with gene involvement. Furthermore, one-third of CNVs do not have putative breakpoints within repetitive sequences. We conclude that replicative processes, mediated either by repetitive elements or microhomology, account for the majority of CNVs in the healthy population. Genomic instability involving the formation of a non-B structure is demonstrated in one region.
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We examined the co-occurrence of migraine and endometriosis within the largest known collection of families containing multiple women with surgically confirmed endometriosis and in an independent sample of 815 monozygotic and 457 dizygotic female twin pairs. Within the endometriosis families, a significantly increased risk of migrainous headache was observed in women with endometriosis compared to women without endometriosis (odds ratio [OR] 1.57, 95% confidence interval [CI]: 1.12-2.21, P=0.009). Bivariate heritability analyses indicated no evidence for common environmental factors influencing either migraine or endometriosis but significant genetic components for both traits, with heritability estimates of 69 and 49%, respectively. Importantly, a significant additive genetic correlation (r(G) = 0.27, 95% CI: 0.06-0.47) and bivariate heritability (h(2)=0.17, 95% CI: 0.08-0.27) was observed between migraine and endometriosis. Controlling for the personality trait neuroticism made little impact on this association. These results confirm the previously reported comorbidity between migraine and endometriosis and indicate common genetic influences completely explain their co-occurrence within individuals. Given pharmacological treatments for endometriosis typically target hormonal pathways and a number of findings provide support for a relationship between hormonal variations and migraine, hormone-related genes and pathways are highly plausible candidates for both migraine and endometriosis. Therefore, taking into account the status of both migraine and endometriosis may provide a novel opportunity to identify the genes underlying them. Finally, we propose that the analysis of such genetically correlated comorbid traits can increase power to detect genetic risk loci through the use of more specific, homogenous and heritable phenotypes.