992 resultados para Enriched genomic library


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The extensive use of buffalo in agriculture, especially in developing countries, begs for genetic resources to evaluate and improve traits important to local and regional economies. Brazil presents the largest water buffalo populations in the New World, with 1 1 million heads including swamp and river types. To design rational breeding strategies for optimum utilization and conservation of available genetic variability in the Brazilian buffalo's population, it is essential to understand their genetic architecture and relationship among various breeds. This depends, in part, on the knowledge of their genetic structure based on molecular markers like microsatellites. In the present study, we developed six enriched partial genomic libraries for river buffalo using selective hybridization methods. Genomic DNA was hybridized with six different arrays of repeat motif, 5' biotinylated - (CA)(15), (CT)(15), (AGG)(8), (GAAA)(8), (GATA)(8), (AAAAC)(8) - and bound to streptavidin coated beads. The cloning process generated a total of 1920 recombinant clones. Up to date, 487 were directly sequenced for the presence of repeats, from which 13 have been positive for presence of repeats as follows: 9 for di-nucleotide repeats, 3 for tri-nucleotide repeats and 1 for tetra-nucleotide repeat. PCR primer pairs for the isolated microsatellites are under construction to determine optimum annealing temperature. These microsatellites will be useful for studies involving phylogenetic relationships, genome mapping and genetic diversity analysis within buffalo populations worldwide.

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Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.

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Background: Current methods to find significantly under- and over-represented gene ontology (GO) terms in a set of genes consider the genes as equally probable balls in a bag, as may be appropriate for transcripts in micro-array data. However, due to the varying length of genes and intergenic regions, that approach is inappropriate for deciding if any GO terms are correlated with a set of genomic positions. Results: We present an algorithm - GONOME - that can determine which GO terms are significantly associated with a set of genomic positions given a genome annotated with (at least) the starts and ends of genes. We show that certain GO terms may appear to be significantly associated with a set of randomly chosen positions in the human genome if gene lengths are not considered, and that these same terms have been reported as significantly over-represented in a number of recent papers. This apparent over-representation disappears when gene lengths are considered, as GONOME does. For example, we show that, when gene length is taken into account, the term development is not significantly enriched in genes associated with human CpG islands, in contradiction to a previous report. We further demonstrate the efficacy of GONOME by showing that occurrences of the proteosome-associated control element (PACE) upstream activating sequence in the S. cerevisiae genome associate significantly to appropriate GO terms. An extension of this approach yields a whole-genome motif discovery algorithm that allows identification of many other promoter sequences linked to different types of genes, including a large group of previously unknown motifs significantly associated with the terms 'translation' and 'translational elongation'. Conclusion: GONOME is an algorithm that correctly extracts over-represented GO terms from a set of genomic positions. By explicitly considering gene size, GONOME avoids a systematic bias toward GO terms linked to large genes. Inappropriate use of existing algorithms that do not take gene size into account has led to erroneous or suspect conclusions. Reciprocally GONOME may be used to identify new features in genomes that are significantly associated with particular categories of genes.

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Campylobacter is a leading cause of foodborne bacterial gastroenteritis worldwide and infections can be fatal. The emergence of antibiotic-resistant Campylobacter spp. necessitates the development of new antimicrobials. We identified novel anti-Campylobacter small molecule inhibitors using a high throughput growth inhibition assay. To expedite screening, we made use of a “bioactive” library of 4,182 compounds that we have previously shown to be active against diverse microbes. Screening for growth inhibition of Campylobacter jejuni, identified 781 compounds that were either bactericidal or bacteriostatic at a concentration of 200 µM. Seventy nine of the bactericidal compounds were prioritized for secondary screening based on their physico-chemical properties. Based on the minimum inhibitory concentration against a diverse range of C. jejuni and a lack of effect on gut microbes, we selected 12 compounds. No resistance was observed to any of these 12 lead compounds when C. jejuni was cultured with lethal or sub-lethal concentrations suggesting that C. jejuni is less likely to develop resistance to these compounds. Top 12 compounds also possessed low cytotoxicity to human intestinal epithelial cells (Caco-2 cells) and no hemolytic activity against sheep red blood cells. Next, these 12 compounds were evaluated for ability to clear C. jejuni in vitro. A total of 10 compounds had an anti-C. jejuni effect in Caco-2 cells with some effective even at 25 µM concentrations. These novel 12 compounds belong to five established antimicrobial chemical classes; piperazines, aryl amines, piperidines, sulfonamide and pyridazinone. Exploitation of analogues of these chemical classes may provide Campylobacter specific drugs that can be applied in both human and animal medicine.

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• We developed the first microsatellites for Passiflora setacea and characterized new sets of markers for P. edulis and P. cincinnata, enabling further genetic diversity studies to support the conservation and breeding of passion fruit species. • We developed 69 microsatellite markers and, in conjunction with assessments of cross-amplification using primers available from the literature, present 43 new polymorphic microsatellite loci for three species of Passiflora. The mean number of alleles per locus was 3.1, and the mean values of the expected and observed levels of heterozygosity were 0.406 and 0.322, respectively. • These microsatellite markers will be valuable tools for investigating the genetic diversity and population structure of wild and commercial species of passion fruit (Passiflora spp.) and may be useful for developing conservation and improvement strategies by contributing to the understanding of the mating system and hybridization within the genus.

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A fosmid metagenomic library was constructed with total community DNA obtained from a municipal wastewater treatment plant (MWWTP), with the aim of identifying new FeFe-hydrogenase genes encoding the enzymes most important for hydrogen metabolism. The dataset generated by pyrosequencing of a fosmid library was mined to identify environmental gene tags (EGTs) assigned to FeFe-hydrogenase. The majority of EGTs representing FeFe-hydrogenase genes were affiliated with the class Clostridia, suggesting that this group is the main hydrogen producer in the MWWTP analyzed. Based on assembled sequences, three FeFe-hydrogenase genes were predicted based on detection of the L2 motif (MPCxxKxxE) in the encoded gene product, confirming true FeFe-hydrogenase sequences. These sequences were used to design specific primers to detect fosmids encoding FeFe-hydrogenase genes predicted from the dataset. Three identified fosmids were completely sequenced. The cloned genomic fragments within these fosmids are closely related to members of the Spirochaetaceae, Bacteroidales and Firmicutes, and their FeFe-hydrogenase sequences are characterized by the structure type M3, which is common to clostridial enzymes. FeFe-hydrogenase sequences found in this study represent hitherto undetected sequences, indicating the high genetic diversity regarding these enzymes in MWWTP. Results suggest that MWWTP have to be considered as reservoirs for new FeFe-hydrogenase genes.

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Based on pre-DNA racial/color methodology, clinical and pharmacological trials have traditionally considered the different geographical regions of Brazil as being very heterogeneous. We wished to ascertain how such diversity of regional color categories correlated with ancestry. Using a panel of 40 validated ancestry-informative insertion-deletion DNA polymorphisms we estimated individually the European, African and Amerindian ancestry components of 934 self-categorized White, Brown or Black Brazilians from the four most populous regions of the Country. We unraveled great ancestral diversity between and within the different regions. Especially, color categories in the northern part of Brazil diverged significantly in their ancestry proportions from their counterparts in the southern part of the Country, indicating that diverse regional semantics were being used in the self-classification as White, Brown or Black. To circumvent these regional subjective differences in color perception, we estimated the general ancestry proportions of each of the four regions in a form independent of color considerations. For that, we multiplied the proportions of a given ancestry in a given color category by the official census information about the proportion of that color category in the specific region, to arrive at a ""total ancestry"" estimate. Once such a calculation was performed, there emerged a much higher level of uniformity than previously expected. In all regions studied, the European ancestry was predominant, with proportions ranging from 60.6% in the Northeast to 77.7% in the South. We propose that the immigration of six million Europeans to Brazil in the 19(th) and 20(th) centuries - a phenomenon described and intended as the ""whitening of Brazil"" -is in large part responsible for dissipating previous ancestry dissimilarities that reflected region-specific population histories. These findings, of both clinical and sociological importance for Brazil, should also be relevant to other countries with ancestrally admixed populations.

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Background: Alternative splicing (AS) is a central mechanism in the generation of genomic complexity and is a major contributor to transcriptome and proteome diversity. Alterations of the splicing process can lead to deregulation of crucial cellular processes and have been associated with a large spectrum of human diseases. Cancer-associated transcripts are potential molecular markers and may contribute to the development of more accurate diagnostic and prognostic methods and also serve as therapeutic targets. Alternative splicing-enriched cDNA libraries have been used to explore the variability generated by alternative splicing. In this study, by combining the use of trapping heteroduplexes and RNA amplification, we developed a powerful approach that enables transcriptome-wide exploration of the AS repertoire for identifying AS variants associated with breast tumor cells modulated by ERBB2 (HER-2/neu) oncogene expression. Results: The human breast cell line (C5.2) and a pool of 5 ERBB2 over-expressing breast tumor samples were used independently for the construction of two AS-enriched libraries. In total, 2,048 partial cDNA sequences were obtained, revealing 214 alternative splicing sequence-enriched tags (ASSETs). A subset with 79 multiple exon ASSETs was compared to public databases and reported 138 different AS events. A high success rate of RT-PCR validation (94.5%) was obtained, and 2 novel AS events were identified. The influence of ERBB2-mediated expression on AS regulation was evaluated by capillary electrophoresis and probe-ligation approaches in two mammary cell lines (Hb4a and C5.2) expressing different levels of ERBB2. The relative expression balance between AS variants from 3 genes was differentially modulated by ERBB2 in this model system. Conclusions: In this study, we presented a method for exploring AS from any RNA source in a transcriptome-wide format, which can be directly easily adapted to next generation sequencers. We identified AS transcripts that were differently modulated by ERBB2-mediated expression and that can be tested as molecular markers for breast cancer. Such a methodology will be useful for completely deciphering the cancer cell transcriptome diversity resulting from AS and for finding more precise molecular markers.

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Background: Citrus canker is a disease caused by the phytopathogens Xanthomonas citri subsp. citri, Xanthomonas fuscans subsp. aurantifolli and Xanthomonas alfalfae subsp. citrumelonis. The first of the three species, which causes citrus bacterial canker type A, is the most widely spread and severe, attacking all citrus species. In Brazil, this species is the most important, being found in practically all areas where citrus canker has been detected. Like most phytobacterioses, there is no efficient way to control citrus canker. Considering the importance of the disease worldwide, investigation is needed to accurately detect which genes are related to the pathogen-host adaptation process and which are associated with pathogenesis. Results: Through transposon insertion mutagenesis, 10,000 mutants of Xanthomonas citri subsp. citri strain 306 (Xcc) were obtained, and 3,300 were inoculated in Rangpur lime (Citrus limonia) leaves. Their ability to cause citrus canker was analyzed every 3 days until 21 days after inoculation; a set of 44 mutants showed altered virulence, with 8 presenting a complete loss of causing citrus canker symptoms. Sequencing of the insertion site in all 44 mutants revealed that 35 different ORFs were hit, since some ORFs were hit in more than one mutant, with mutants for the same ORF presenting the same phenotype. An analysis of these ORFs showed that some encoded genes were previously known as related to pathogenicity in phytobacteria and, more interestingly, revealed new genes never implicated with Xanthomonas pathogenicity before, including hypothetical ORFs. Among the 8 mutants with no canker symptoms are the hrpB4 and hrpX genes, two genes that belong to type III secretion system (TTSS), two hypothetical ORFS and, surprisingly, the htrA gene, a gene reported as involved with the virulence process in animal-pathogenic bacteria but not described as involved in phytobacteria virulence. Nucleic acid hybridization using labeled cDNA probes showed that some of the mutated genes are differentially expressed when the bacterium is grown in citrus leaves. Finally, comparative genomic analysis revealed that 5 mutated ORFs are in new putative pathogenicity islands. Conclusion: The identification of these new genes related with Xcc infection and virulence is a great step towards the understanding of plant-pathogen interactions and could allow the development of strategies to control citrus canker.

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From a genomic enriched library, we developed 27 primer pairs from microsatellite flanking sequences for Colletotrichum acutatum, associated to postbloom fruit drop disease on citrus. Loci were characterized using 40 monosporic C. acutatum isolates. Nine primer pairs successfully amplified polymorphic microsatellite regions, with 3-6 alleles per locus, and mean heterozygosities ranging 0.093-0.590 across loci. The suitability of these primers was investigated in four Colletotrichum species as well. These microsatellite markers will be useful for genetic analyses and epidemiological studies of C. acutatum.

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This paper identifies research priorities in evaluating the ways in which "genomic medicine"-the use of genetic information to prevent and treat disease-may reduce tobacco-related harm by: (1) assisting more smokers to quit; (2) preventing non-smokers from beginning to smoke tobacco; and (3) reducing the harm caused by tobacco smoking. The method proposed to achieve the first aim is pharmacogenetics", the use of genetic information to optimise the selection of smoking-cessation programmes by screening smokers for polymorphisms that predict responses to different methods of smoking cessation. This method competes with the development of more effective forms of smoking cessation that involve vaccinating smokers against the effects of nicotine and using new pharmaceuticals (such as cannabinoid antagonists and nicotine agonists). The second and third aims are more speculative. They include: screening the population for genetic susceptibility to nicotine dependence and intervening (eg, by vaccinating children and adolescents against the effects of nicotine) to prevent smoking uptake, and screening the population for genetic susceptibility to tobacco-related diseases. A framework is described for future research on these policy options. This includes: epidemiological modelling and economic evaluation to specify the conditions under which these strategies are cost-effective; and social psychological research into the effect of providing genetic information on smokers' preparedness to quit, and the general views of the public on tobacco smoking.

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In recent years, the phrase 'genomic medicine' has increasingly been used to describe a new development in medicine that holds great promise for human health. This new approach to health care uses the knowledge of an individual's genetic make-up to identify those that are at a higher risk of developing certain diseases and to intervene at an earlier stage to prevent these diseases. Identifying genes that are involved in disease aetiology will provide researchers with tools to develop better treatments and cures. A major role within this field is attributed to 'predictive genomic medicine', which proposes screening healthy individuals to identify those who carry alleles that increase their susceptibility to common diseases, such as cancers and heart disease. Physicians could then intervene even before the disease manifests and advise individuals with a higher genetic risk to change their behaviour - for instance, to exercise or to eat a healthier diet - or offer drugs or other medical treatment to reduce their chances of developing these diseases. These promises have fallen on fertile ground among politicians, health-care providers and the general public, particularly in light of the increasing costs of health care in developed societies. Various countries have established databases on the DNA and health information of whole populations as a first step towards genomic medicine. Biomedical research has also identified a large number of genes that could be used to predict someone's risk of developing a certain disorder. But it would be premature to assume that genomic medicine will soon become reality, as many problems remain to be solved. Our knowledge about most disease genes and their roles is far from sufficient to make reliable predictions about a patient’s risk of actually developing a disease. In addition, genomic medicine will create new political, social, ethical and economic challenges that will have to be addressed in the near future.

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Despite the success of conventional Sanger sequencing, significant regions of many genomes still present major obstacles to sequencing. Here we propose a novel approach with the potential to alleviate a wide range of sequencing difficulties. The technique involves extracting target DNA sequence from variants generated by introduction of random mutations. The introduction of mutations does not destroy original sequence information, but distributes it amongst multiple variants. Some of these variants lack problematic features of the target and are more amenable to conventional sequencing. The technique has been successfully demonstrated with mutation levels up to an average 18% base substitution and has been used to read previously intractable poly(A), AT-rich and GC-rich motifs.