987 resultados para Eukaryotic Genomes


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Nucleotides in the terminal loop of the poliovirus 2C cis-acting replication element (2C(CRE)), a 61 nt structured RNA, function as the template for the addition of two uridylate (U) residues to the viral protein VPg. This uridylylation reaction leads to the formation of VPgpUpU, which is used by the viral RNA polymerase as a nucleotide-peptide primer for genome replication. Although VPg primes both positive- and negative-strand replication, the specific requirement for 2C(CRE)-mediated uridylylation for one or both events has not been demonstrated. We have used a cell-free in vitro translation and replication reaction to demonstrate that 2C(CRE) is not required for the initiation of the negative-sense strand, which is synthesized in the absence of 2C(CRE)-mediated VPgpUpU formation. We propose that the 3' poly(A) tail could serve as the template for the formation of a VPg-poly(U) primer that functions in the initiation of negative-sense strands.

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Biological Crossover occurs during the early stages of meiosis. During this process the chromosomes undergoing crossover are synapsed together at a number of homogenous sequence sections, it is within such synapsed sections that crossover occurs. The SVLC (Synapsing Variable Length Crossover) Algorithm recurrently synapses homogenous genetic sequences together in order of length. The genomes are considered to be flexible with crossover only being permitted within the synapsed sections. Consequently, common sequences are automatically preserved with only the genetic differences being exchanged, independent of the length of such differences. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be utilised. In a simple variable length test problem the SVLC algorithm outperforms current variable length crossover techniques.

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The Synapsing Variable Length Crossover (SVLC) algorithm provides a biologically inspired method for performing meaningful crossover between variable length genomes. In addition to providing a rationale for variable length crossover it also provides a genotypic similarity metric for variable length genomes enabling standard niche formation techniques to be used with variable length genomes. Unlike other variable length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC Algorithm recurrently "glues" or synapses homogenous genetic sub-sequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable length test problem the SVLC algorithm is shown to outperform current variable length crossover techniques. The SVLC algorithm is also shown to work in a more realistic robot neural network controller evolution application.

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The synapsing variable-length crossover (SVLC algorithm provides a biologically inspired method for performing meaningful crossover between variable-length genomes. In addition to providing a rationale for variable-length crossover, it also provides a genotypic similarity metric for variable-length genomes, enabling standard niche formation techniques to be used with variable-length genomes. Unlike other variable-length crossover techniques which consider genomes to be rigid inflexible arrays and where some or all of the crossover points are randomly selected, the SVLC algorithm considers genomes to be flexible and chooses non-random crossover points based on the common parental sequence similarity. The SVLC algorithm recurrently "glues" or synapses homogenous genetic subsequences together. This is done in such a way that common parental sequences are automatically preserved in the offspring with only the genetic differences being exchanged or removed, independent of the length of such differences. In a variable-length test problem, the SVLC algorithm compares favorably with current variable-length crossover techniques. The variable-length approach is further advocated by demonstrating how a variable-length genetic algorithm (GA) can obtain a high fitness solution in fewer iterations than a traditional fixed-length GA in a two-dimensional vector approximation task.

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Members of the genus Pseudomonas inhabit a wide variety of environments, which is reflected in their versatile metabolic capacity and broad potential for adaptation to fluctuating environmental conditions. Here, we examine and compare the genomes of a range of Pseudomonas spp. encompassing plant, insect and human pathogens, and environmental saprophytes. In addition to a large number of allelic differences of common genes that confer regulatory and metabolic flexibility, genome analysis suggests that many other factors contribute to the diversity and adaptability of Pseudomonas spp. Horizontal gene transfer has impacted the capability of pathogenic Pseudomonas spp. in terms of disease severity (Pseudomonas aeruginosa) and specificity (Pseudomonas syringae). Genome rearrangements likely contribute to adaptation, and a considerable complement of unique genes undoubtedly contributes to strain- and species-specific activities by as yet unknown mechanisms. Because of the lack of conserved phenotypic differences, the classification of the genus has long been contentious. DNA hybridization and genome-based analyses show close relationships among members of P. aeruginosa, but that isolates within the Pseudomonas fluorescens and P. syringae species are less closely related and may constitute different species. Collectively, genome sequences of Pseudomonas spp. have provided insights into pathogenesis and the genetic basis for diversity and adaptation.

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The Acari is the most numerous and diverse group of the subphylum Chelicerata. With approximately 55 000 described species (and estimates of up to 1 million extant species), their adaptations for parasitism, phytophagy, mycophagy, saprophagy and predation rival other arthropods and challenge us with a wide variety of biological interactions. While a few studies have unravelled the nature of some endosymbiotic associations between mites or ticks and prokaryotes, almost nothing has been done yet regarding acarine eukaryotic ectosymbionts. Microbial ectosymbionts can benefit their hosts by providing nutrients, by aiding digestion, by enhancing communication, by assisting in mating and/or fertilization, by protecting their host against pathogenic microorganisms, against predation and so on. In this sketch, we introduce a number of described cases of fungal and protist ectosymbionts and discuss the role they might play in the life of their acarine hosts.

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Currently, the Genomic Threading Database (GTD) contains structural assignments for the proteins encoded within the genomes of nine eukaryotes and 101 prokaryotes. Structural annotations are carried out using a modified version of GenTHREADER, a reliable fold recognition method. The Gen THREADER annotation jobs are distributed across multiple clusters of processors using grid technology and the predictions are deposited in a relational database accessible via a web interface at http://bioinf.cs.ucl.ac.uk/GTD. Using this system, up to 84% of proteins encoded within a genome can be confidently assigned to known folds with 72% of the residues aligned. On average in the GTD, 64% of proteins encoded within a genome are confidently assigned to known folds and 58% of the residues are aligned to structures.

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An automatic method for recognizing natively disordered regions from amino acid sequence is described and benchmarked against predictors that were assessed at the latest critical assessment of techniques for protein structure prediction (CASP) experiment. The method attains a Wilcoxon score of 90.0, which represents a statistically significant improvement on the methods evaluated on the same targets at CASP. The classifier, DISOPRED2, was used to estimate the frequency of native disorder in several representative genomes from the three kingdoms of life. Putative, long (>30 residue) disordered segments are found to occur in 2.0% of archaean, 4.2% of eubacterial and 33.0% of eukaryotic proteins. The function of proteins with long predicted regions of disorder was investigated using the gene ontology annotations supplied with the Saccharomyces genome database. The analysis of the yeast proteome suggests that proteins containing disorder are often located in the cell nucleus and are involved in the regulation of transcription and cell signalling. The results also indicate that native disorder is associated with the molecular functions of kinase activity and nucleic acid binding.

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Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

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Life-history traits vary substantially across species, and have been demonstrated to affect substitution rates. We compute genomewide, branch-specific estimates of male mutation bias (the ratio of male-to-female mutation rates) across 32 mammalian genomes and study how these vary with life-history traits (generation time, metabolic rate, and sperm competition). We also investigate the influence of life-history traits on substitution rates at unconstrained sites across a wide phylogenetic range. We observe that increased generation time is the strongest predictor of variation in both substitution rates (for which it is a negative predictor) and male mutation bias (for which it is a positive predictor). Although less significant, we also observe that estimates of metabolic rate, reflecting replication-independent DNA damage and repair mechanisms, correlate negatively with autosomal substitution rates, and positively with male mutation bias. Finally, in contrast to expectations, we find no significant correlation between sperm competition and either autosomal substitution rates or male mutation bias. Our results support the important but frequently opposite effects of some, but not all, life history traits on substitution rates. KEY WORDS: Generation time, genome evolution, metabolic rate, sperm competition.

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Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

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The genome of the soil-dwelling heterotrophic N2-fixing Gram-negative bacterium Azotobacter chroococcum NCIMB 8003 (ATCC 4412) (Ac-8003) has been determined. It consists of 7 circular replicons totalling 5,192,291 bp comprising a circular chromosome of 4,591,803 bp and six plasmids pAcX50a, b, c, d, e, f of 10,435 bp, 13,852, 62,783, 69,713, 132,724, and 311,724 bp respectively. The chromosome has a G+C content of 66.27% and the six plasmids have G+C contents of 58.1, 55.3, 56.7, 59.2, 61.9, and 62.6% respectively. The methylome has also been determined and 5 methylation motifs have been identified. The genome also contains a very high number of transposase/inactivated transposase genes from at least 12 of the 17 recognised insertion sequence families. The Ac-8003 genome has been compared with that of Azotobacter vinelandii ATCC BAA-1303 (Av-DJ), a derivative of strain O, the only other member of the Azotobacteraceae determined so far which has a single chromosome of 5,365,318 bp and no plasmids. The chromosomes show significant stretches of synteny throughout but also reveal a history of many deletion/insertion events. The Ac-8003 genome encodes 4628 predicted protein-encoding genes of which 568 (12.2%) are plasmid borne. 3048 (65%) of these show > 85% identity to the 5050 protein-encoding genes identified in Av-DJ, and of these 99 are plasmid-borne. The core biosynthetic and metabolic pathways and macromolecular architectures and machineries of these organisms appear largely conserved including genes for CO-dehydrogenase, formate dehydrogenase and a soluble NiFe-hydrogenase. The genetic bases for many of the detailed phenotypic differences reported for these organisms have also been identified. Also many other potential phenotypic differences have been uncovered. Properties endowed by the plasmids are described including the presence of an entire aerobic corrin synthesis pathway in pAcX50f and the presence of genes for retro-conjugation in pAcX50c. All these findings are related to the potentially different environmental niches from which these organisms were isolated and to emerging theories about how microbes contribute to their communities.

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