948 resultados para Genome-Wide Association


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Plant responses against pathogens cause up-and downward shifts in gene expression. To identify differentially expressed genes in a plant-virus interaction, susceptible tomato plants were inoculated with the potyvirus Pepper yellow mosaic virus (PepYMV) and a subtractive library was constructed from inoculated leaves at 72 h after inoculation. Several genes were identified as upregulated, including genes involved in plant defense responses (e. g., pathogenesis-related protein 5), regulation of the cell cycle (e. g., cytokinin-repressed proteins), signal transduction (e. g., CAX-interacting protein 4, SNF1 kinase), transcriptional regulators (e. g., WRKY and SCARECROW transcription factors), stress response proteins (e. g., Hsp90, DNA-J, 20S proteasome alpha subunit B, translationally controlled tumor protein), ubiquitins (e. g., polyubiquitin, ubiquitin activating enzyme 2), among others. Downregulated genes were also identified, which likewise display identity with genes involved in several metabolic pathways. Differential expression of selected genes was validated by macroarray analysis and quantitative real-time polymerase chain reaction. The possible roles played by some of these genes in the viral infection cycle are discussed.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Medicina Veterinária - FCAV

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pellegrino R, Sunaga DY, Guindalini C, Martins RC, Mazzotti DR, Wei Z, Daye ZJ, Andersen ML, Tufik S. Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery. Physiol Genomics 44: 1003-1012, 2012. First published September 4, 2012; doi: 10.1152/physiolgenomics.00058.2012.-Although the specific functions of sleep have not been completely elucidated, the literature has suggested that sleep is essential for proper homeostasis. Sleep loss is associated with changes in behavioral, neurochemical, cellular, and metabolic function as well as impaired immune response. Using high-resolution microarrays we evaluated the gene expression profiles of healthy male volunteers who underwent 60 h of prolonged wakefulness (PW) followed by 12 h of sleep recovery (SR). Peripheral whole blood was collected at 8 am in the morning before the initiation of PW (Baseline), after the second night of PW, and one night after SR. We identified over 500 genes that were differentially expressed. Notably, these genes were related to DNA damage and repair and stress response, as well as diverse immune system responses, such as natural killer pathways including killer cell lectin-like receptors family, as well as granzymes and T-cell receptors, which play important roles in host defense. These results support the idea that sleep loss can lead to alterations in molecular processes that result in perturbation of cellular immunity, induction of inflammatory responses, and homeostatic imbalance. Moreover, expression of multiple genes was downregulated following PW and upregulated after SR compared with PW, suggesting an attempt of the body to re-establish internal homeostasis. In silico validation of alterations in the expression of CETN3, DNAJC, and CEACAM genes confirmed previous findings related to the molecular effects of sleep deprivation. Thus, the present findings confirm that the effects of sleep loss are not restricted to the brain and can occur intensely in peripheral tissues.

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Background: The Interleukin 28B (IL28B) rs12979860 polymorphisms was recently reported to be associated with the human T-cell leukemia virus type 1 (HTLV-1) proviral load (PvL) and the development of the HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Methods: In an attempt to examine this hypothesis, we assessed the association of the rs12979860 genotypes with HTLV-1 PvL levels and clinical status in 112 unrelated Brazilian subjects (81 HTLV-1 asymptomatic carriers, 24 individuals with HAM/TSP and 7 with Adult T cell Leukemia/Lymphoma (ATLL)). Results: All 112 samples were successfully genotyped and their PvLs compared. Neither the homozygote TT nor the heterozygote CT mutations nor the combination genotypes (TT/CT) were associated with a greater PvL. We also observed no significant difference in allele distribution between asymptomatic carriers and patients with HTLV-1 associated HAM/TSP. Conclusions: Our study failed to support the previously reported positive association between the IL28B rs12979860 polymorphisms and an increased risk of developing HAM/TSP in the Brazilian population.

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Abstract Background In tropical countries, losses caused by bovine tick Rhipicephalus (Boophilus) microplus infestation have a tremendous economic impact on cattle production systems. Genetic variation between Bos taurus and Bos indicus to tick resistance and molecular biology tools might allow for the identification of molecular markers linked to resistance traits that could be used as an auxiliary tool in selection programs. The objective of this work was to identify QTL associated with tick resistance/susceptibility in a bovine F2 population derived from the Gyr (Bos indicus) × Holstein (Bos taurus) cross. Results Through a whole genome scan with microsatellite markers, we were able to map six genomic regions associated with bovine tick resistance. For most QTL, we have found that depending on the tick evaluation season (dry and rainy) different sets of genes could be involved in the resistance mechanism. We identified dry season specific QTL on BTA 2 and 10, rainy season specific QTL on BTA 5, 11 and 27. We also found a highly significant genome wide QTL for both dry and rainy seasons in the central region of BTA 23. Conclusions The experimental F2 population derived from Gyr × Holstein cross successfully allowed the identification of six highly significant QTL associated with tick resistance in cattle. QTL located on BTA 23 might be related with the bovine histocompatibility complex. Further investigation of these QTL will help to isolate candidate genes involved with tick resistance in cattle.

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Background: Even before having its genome sequence published in 2004, Kluyveromyces lactis had long been considered a model organism for studies in genetics and physiology. Research on Kluyveromyces lactis is quite advanced and this yeast species is one of the few with which it is possible to perform formal genetic analysis. Nevertheless, until now, no complete metabolic functional annotation has been performed to the proteins encoded in the Kluyveromyces lactis genome. Results: In this work, a new metabolic genome-wide functional re-annotation of the proteins encoded in the Kluyveromyces lactis genome was performed, resulting in the annotation of 1759 genes with metabolic functions, and the development of a methodology supported by merlin (software developed in-house). The new annotation includes novelties, such as the assignment of transporter superfamily numbers to genes identified as transporter proteins. Thus, the genes annotated with metabolic functions could be exclusively enzymatic (1410 genes), transporter proteins encoding genes (301 genes) or have both metabolic activities (48 genes). The new annotation produced by this work largely surpassed the Kluyveromyces lactis currently available annotations. A comparison with KEGG’s annotation revealed a match with 844 (~90%) of the genes annotated by KEGG, while adding 850 new gene annotations. Moreover, there are 32 genes with annotations different from KEGG. Conclusions: The methodology developed throughout this work can be used to re-annotate any yeast or, with a little tweak of the reference organism, the proteins encoded in any sequenced genome. The new annotation provided by this study offers basic knowledge which might be useful for the scientific community working on this model yeast, because new functions have been identified for the so-called metabolic genes. Furthermore, it served as the basis for the reconstruction of a compartmentalized, genome-scale metabolic model of Kluyveromyces lactis, which is currently being finished.

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Abstract Background The generalized odds ratio (GOR) was recently suggested as a genetic model-free measure for association studies. However, its properties were not extensively investigated. We used Monte Carlo simulations to investigate type-I error rates, power and bias in both effect size and between-study variance estimates of meta-analyses using the GOR as a summary effect, and compared these results to those obtained by usual approaches of model specification. We further applied the GOR in a real meta-analysis of three genome-wide association studies in Alzheimer's disease. Findings For bi-allelic polymorphisms, the GOR performs virtually identical to a standard multiplicative model of analysis (e.g. per-allele odds ratio) for variants acting multiplicatively, but augments slightly the power to detect variants with a dominant mode of action, while reducing the probability to detect recessive variants. Although there were differences among the GOR and usual approaches in terms of bias and type-I error rates, both simulation- and real data-based results provided little indication that these differences will be substantial in practice for meta-analyses involving bi-allelic polymorphisms. However, the use of the GOR may be slightly more powerful for the synthesis of data from tri-allelic variants, particularly when susceptibility alleles are less common in the populations (≤10%). This gain in power may depend on knowledge of the direction of the effects. Conclusions For the synthesis of data from bi-allelic variants, the GOR may be regarded as a multiplicative-like model of analysis. The use of the GOR may be slightly more powerful in the tri-allelic case, particularly when susceptibility alleles are less common in the populations.

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Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

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Membrane proteins are a large and important class of proteins. They are responsible for several of the key functions in a living cell, e.g. transport of nutrients and ions, cell-cell signaling, and cell-cell adhesion. Despite their importance it has not been possible to study their structure and organization in much detail because of the difficulty to obtain 3D structures. In this thesis theoretical studies of membrane protein sequences and structures have been carried out by analyzing existing experimental data. The data comes from several sources including sequence databases, genome sequencing projects, and 3D structures. Prediction of the membrane spanning regions by hydrophobicity analysis is a key technique used in several of the studies. A novel method for this is also presented and compared to other methods. The primary questions addressed in the thesis are: What properties are common to all membrane proteins? What is the overall architecture of a membrane protein? What properties govern the integration into the membrane? How many membrane proteins are there and how are they distributed in different organisms? Several of the findings have now been backed up by experiments. An analysis of the large family of G-protein coupled receptors pinpoints differences in length and amino acid composition of loops between proteins with and without a signal peptide and also differences between extra- and intracellular loops. Known 3D structures of membrane proteins have been studied in terms of hydrophobicity, distribution of secondary structure and amino acid types, position specific residue variability, and differences between loops and membrane spanning regions. An analysis of several fully and partially sequenced genomes from eukaryotes, prokaryotes, and archaea has been carried out. Several differences in the membrane protein content between organisms were found, the most important being the total number of membrane proteins and the distribution of membrane proteins with a given number of transmembrane segments. Of the properties that were found to be similar in all organisms, the most obvious is the bias in the distribution of positive charges between the extra- and intracellular loops. Finally, an analysis of homologues to membrane proteins with known topology uncovered two related, multi-spanning proteins with opposite predicted orientations. The predicted topologies were verified experimentally, providing a first example of "divergent topology evolution".

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The DNA topology is an important modifier of DNA functions. Torsional stress is generated when right handed DNA is either over- or underwound, producing structural deformations which drive or are driven by processes such as replication, transcription, recombination and repair. DNA topoisomerases are molecular machines that regulate the topological state of the DNA in the cell. These enzymes accomplish this task by either passing one strand of the DNA through a break in the opposing strand or by passing a region of the duplex from the same or a different molecule through a double-stranded cut generated in the DNA. Because of their ability to cut one or two strands of DNA they are also target for some of the most successful anticancer drugs used in standard combination therapies of human cancers. An effective anticancer drug is Camptothecin (CPT) that specifically targets DNA topoisomerase 1 (TOP 1). The research project of the present thesis has been focused on the role of human TOP 1 during transcription and on the transcriptional consequences associated with TOP 1 inhibition by CPT in human cell lines. Previous findings demonstrate that TOP 1 inhibition by CPT perturbs RNA polymerase (RNAP II) density at promoters and along transcribed genes suggesting an involvement of TOP 1 in RNAP II promoter proximal pausing site. Within the transcription cycle, promoter pausing is a fundamental step the importance of which has been well established as a means of coupling elongation to RNA maturation. By measuring nascent RNA transcripts bound to chromatin, we demonstrated that TOP 1 inhibition by CPT can enhance RNAP II escape from promoter proximal pausing site of the human Hypoxia Inducible Factor 1 (HIF-1) and c-MYC genes in a dose dependent manner. This effect is dependent from Cdk7/Cdk9 activities since it can be reversed by the kinases inhibitor DRB. Since CPT affects RNAP II by promoting the hyperphosphorylation of its Rpb1 subunit the findings suggest that TOP 1inhibition by CPT may increase the activity of Cdks which in turn phosphorylate the Rpb1 subunit of RNAP II enhancing its escape from pausing. Interestingly, the transcriptional consequences of CPT induced topological stress are wider than expected. CPT increased co-transcriptional splicing of exon1 and 2 and markedly affected alternative splicing at exon 11. Surprisingly despite its well-established transcription inhibitory activity, CPT can trigger the production of a novel long RNA (5’aHIF-1) antisense to the human HIF-1 mRNA and a known antisense RNA at the 3’ end of the gene, while decreasing mRNA levels. The effects require TOP 1 and are independent from CPT induced DNA damage. Thus, when the supercoiling imbalance promoted by CPT occurs at promoter, it may trigger deregulation of the RNAP II pausing, increased chromatin accessibility and activation/derepression of antisense transcripts in a Cdks dependent manner. A changed balance of antisense transcripts and mRNAs may regulate the activity of HIF-1 and contribute to the control of tumor progression After focusing our TOP 1 investigations at a single gene level, we have extended the study to the whole genome by developing the “Topo-Seq” approach which generates a map of genome-wide distribution of sites of TOP 1 activity sites in human cells. The preliminary data revealed that TOP 1 preferentially localizes at intragenic regions and in particular at 5’ and 3’ ends of genes. Surprisingly upon TOP 1 downregulation, which impairs protein expression by 80%, TOP 1 molecules are mostly localized around 3’ ends of genes, thus suggesting that its activity is essential at these regions and can be compensate at 5’ ends. The developed procedure is a pioneer tool for the detection of TOP 1 cleavage sites across the genome and can open the way to further investigations of the enzyme roles in different nuclear processes.

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The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.