954 resultados para Gene function
Resumo:
CRISPR/Cas9-mediated targeted mutagenesis allows efficient generation of loss-of-function alleles in zebrafish. To date, this technology has been primarily used to generate genetic knockout animals. Nevertheless, the study of the function of certain loci might require tight spatiotemporal control of gene inactivation. Here, we show that tissue-specific gene disruption can be achieved by driving Cas9 expression with the Gal4/UAS system. Furthermore, by combining the Gal4/UAS and Cre/loxP systems, we establish a versatile tool to genetically label mutant cell clones, enabling their phenotypic analysis. Our technique has the potential to be applied to diverse model organisms, enabling tissue-specific loss-of-function and phenotypic characterization of live and fixed tissues.
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Many homeobox genes control essential developmental processes in animals and plants. In this report, we describe the first cDNA corresponding to a homeobox gene isolated from a gymnosperm, the HBK1 gene from the conifer Picea abies (L.) Karst (Norway spruce). The sequence shows distinct similarities specifically to the KNOX (knotted-like homeobox) class of homeobox genes known from different angiosperm plants. The deduced amino acid sequence of HBK1 is strikingly similar within the homeodomain (84% identical) to the maize gene Knotted1 (Kn1), which acts to regulate cell differentiation in the shoot meristem. This similarity suggested that the phylogenetic association of HBK1 with the KNOX genes might be coupled to a conservation of gene function. In support of this suggestion, we have found HBK1 to be expressed in the apical meristem in the central population of nondifferentiated stem cells, but not in organ primordia developing at the flanks of the meristem. This pattern of expression is similar to that of Kn1 in the maize meristem. We show further that HBK1, when expressed ectopically in transgenic Arabidopsis plants, causes aberrations in leaf development that are similar to the effects of ectopic expression of angiosperm KNOX genes on Arabidopsis development. Taken together, these data suggest that HBK1 has a role, similar to the KNOX genes in angiosperms, in the control of cellular differentiation in the apical meristem of spruce. The data also indicate that KNOX-gene regulation of vegetative development is an ancient feature of seed plants that was present in the last common ancestor of conifers and angiosperms.
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High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.
Resumo:
Tight control over circulating juvenile hormone (JH) levels is of prime importance in an insect`s life cycle. Consequently, enzymes involved in JH metabolism, especially juvenile hormone esterases (JHEs), play major roles during metamorphosis and reproduction. In the highly eusocial Hymenoptera, JH has been co-opted into additional functions, primarily in the development of the queen and worker castes and in age-related behavioral development of workers. Within a set of 21 carboxylesterases predicted in the honey bee genome we identified one gene (Amjhe-like) that contained the main functional motifs of insect JHEs. Its transcript levels during larval development showed a maximum at the switch from feeding to spinning behavior, coinciding with a JH titer minimum. In adult workers, the highest levels were observed in nurse bees, where a low JH titer is required to prevent the switch to foraging. Functional assays showed that Amjhe-like expression is induced by JH-III and suppressed by 20-hydroxyecdysone. RNAi-mediated silencing of Amjhe-like gene function resulted in a six-fold increase in the JH titer in adult worker bees. The temporal profile of Amjhe-like expression in larval and adult workers, the pattern of hormonal regulation and the knockdown phenotype are consistent with the function of this gene as an authentic JHE. (C) 2008 Elsevier Inc. All rights reserved.
Resumo:
Protozoan parasites affect millions of people around the world. Treatment and control of these diseases are complicated partly due to the intricate biology of these organisms. The interactions of species of Plasmodium, Leishmania and trypanosomes with their hosts are mediated by an unusual control of gene expression that is not fully understood. The availability of the genome sequence of these protozoa sets the stage for using more comprehensive, genome-wide strategies to study gene function. Transposons are effective tools for the systematic introduction of genetic alterations and different transposition systems have been adapted to study gene function in these human pathogens. A mariner transposon toolkit for use in vivo or in vitro in Leishmania parasites has been developed and can be used in a variety of applications. These modified mariner elements not only permit the inactivation of genes, but also mediate the rescue of translational gene fusions, bringing a major contribution to the investigation of Leishmania gene function. The piggyBac and Tn5 transposons have also been shown to mobilize across Plasmodium spp. genomes circumventing the current limitations in the genetic manipulation of these organisms.
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Rapid access to genetic information is central to the revolution presently occurring in the pharmaceutical industry, particularly In relation to novel drug target identification and drug development. Genetic variation, gene expression, gene function and gene structure are just some of the important research areas requiring efficient methods of DNA screening. Here, we highlight state-of-the-art techniques and devices for gene screening that promise cheaper and higher-throughput yields than currently achieved with DNA microarrays. We include an overview of existing and proposed bead-based strategies designed to dramatically increase the number of probes that can be interrogated in one assay. We focus, in particular, on the issue of encoding and/or decoding (bar-coding) large bead-based libraries for HTS.
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Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.
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During my PhD, my aim was to provide new tools to increase our capacity to analyse gene expression patterns, and to study on a large-scale basis the evolution of gene expression in animals. Gene expression patterns (when and where a gene is expressed) are a key feature in understanding gene function, notably in development. It appears clear now that the evolution of developmental processes and of phenotypes is shaped both by evolution at the coding sequence level, and at the gene expression level.Studying gene expression evolution in animals, with complex expression patterns over tissues and developmental time, is still challenging. No tools are available to routinely compare expression patterns between different species, with precision, and on a large-scale basis. Studies on gene expression evolution are therefore performed only on small genes datasets, or using imprecise descriptions of expression patterns.The aim of my PhD was thus to develop and use novel bioinformatics resources, to study the evolution of gene expression. To this end, I developed the database Bgee (Base for Gene Expression Evolution). The approach of Bgee is to transform heterogeneous expression data (ESTs, microarrays, and in-situ hybridizations) into present/absent calls, and to annotate them to standard representations of anatomy and development of different species (anatomical ontologies). An extensive mapping between anatomies of species is then developed based on hypothesis of homology. These precise annotations to anatomies, and this extensive mapping between species, are the major assets of Bgee, and have required the involvement of many co-workers over the years. My main personal contribution is the development and the management of both the Bgee database and the web-application.Bgee is now on its ninth release, and includes an important gene expression dataset for 5 species (human, mouse, drosophila, zebrafish, Xenopus), with the most data from mouse, human and zebrafish. Using these three species, I have conducted an analysis of gene expression evolution after duplication in vertebrates.Gene duplication is thought to be a major source of novelty in evolution, and to participate to speciation. It has been suggested that the evolution of gene expression patterns might participate in the retention of duplicate genes. I performed a large-scale comparison of expression patterns of hundreds of duplicated genes to their singleton ortholog in an outgroup, including both small and large-scale duplicates, in three vertebrate species (human, mouse and zebrafish), and using highly accurate descriptions of expression patterns. My results showed unexpectedly high rates of de novo acquisition of expression domains after duplication (neofunctionalization), at least as high or higher than rates of partitioning of expression domains (subfunctionalization). I found differences in the evolution of expression of small- and large-scale duplicates, with small-scale duplicates more prone to neofunctionalization. Duplicates with neofunctionalization seemed to evolve under more relaxed selective pressure on the coding sequence. Finally, even with abundant and precise expression data, the majority fate I recovered was neither neo- nor subfunctionalization of expression domains, suggesting a major role for other mechanisms in duplicate gene retention.
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Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom+ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod+ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom+ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom+ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.
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Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.
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The cupin superfamily is a group of functionally diverse proteins that are found in all three kingdoms of life, Archaea, Eubacteria, and Eukaryota. These proteins have a characteristic signature domain comprising two histidine- containing motifs separated by an intermotif region of variable length. This domain consists of six beta strands within a conserved beta barrel structure. Most cupins, such as microbial phosphomannose isomerases (PMIs), AraC- type transcriptional regulators, and cereal oxalate oxidases (OXOs), contain only a single domain, whereas others, such as seed storage proteins and oxalate decarboxylases (OXDCs), are bi-cupins with two pairs of motifs. Although some cupins have known functions and have been characterized at the biochemical level, the majority are known only from gene cloning or sequencing projects. In this study, phylogenetic analyses were conducted on the conserved domain to investigate the evolution and structure/function relationships of cupins, with an emphasis on single- domain plant germin-like proteins (GLPs). An unrooted phylogeny of cupins from a wide spectrum of evolutionary lineages identified three main clusters, microbial PMIs, OXDCs, and plant GLPs. The sister group to the plant GLPs in the global analysis was then used to root a phylogeny of all available plant GLPs. The resulting phylogeny contained three main clades, classifying the GLPs into distinct subfamilies. It is suggested that these subfamilies correlate with functional categories, one of which contains the bifunctional barley germin that has both OXO and superoxide dismutase (SOD) activity. It is proposed that GLPs function primarily as SODs, enzymes that protect plants from the effects of oxidative stress. Closer inspection of the DNA sequence encoding the intermotif region in plant GLPs showed global conservation of thymine in the second codon position, a character associated with hydrophobic residues. Since many of these proteins are multimeric and enzymatically inactive in their monomeric state, this conservation of hydrophobicity is thought to be associated with the need to maintain the various monomer- monomer interactions. The type of structure-based predictive analysis presented in this paper is an important approach for understanding gene function and evolution in an era when genomes from a wide range of organisms are being sequenced at a rapid rate.
Resumo:
Over the past decade genomic approaches have begun to revolutionise the study of animal diversity. In particular, genome sequencing programmes have spread beyond the traditional model species to encompass an increasing diversity of animals from many different phyla, as well as unicellular eukaryotes that are closely related to the animals. Whole genome sequences allow researchers to establish, with reasonable confidence, the full complement of any particular family of genes in a genome. Comparison of gene complements from appropriate genomes can reveal the evolutionary history of gene families, indicating when both gene diversification and gene loss have occurred. More than that, however, assembled genomes allow the genomic environment in which individual genes are found to be analysed and compared between species. This can reveal how gene diversification occurred. Here, we focus on the Fox genes, drawing from multiple animal genomes to develop an evolutionary framework explaining the timing and mechanism of origin of the diversity of animal Fox genes. Ancient linkages between genes are a prominent feature of the Fox genes, depicting a history of gene clusters, some of which may be relevant to understanding Fox gene function.
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A strain of Staphylococcus isolated by Dr. Fekete at the Sandia National Laboratory toxic metal dumping site in Sandia, New Mexico. has been found to reduce toxic Cr(VI) to the less toxic Cr(IlI) state. We have ascertained the environmental parameters for optimal bacterial growth and Cr(VI) reduction. This knowledge may be employed in a comprehensive bioremediation scheme designed to accelerate natural reparation of that Sandia ecosystem. In addition we have investigated the genetic and enzymatic basis for this Cr(VI) reducing ability. This information may allow us to create more effective bioremediation schemes based on the comprehensive knowledge of enzyme and gene function. Preliminary investigations have been carried out toward this end which may serve as the basis for a more thorough investigation.
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Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.
Resumo:
Introduction: Brief overview of Bone Development Disorders of the Skeleton Cartilage-Hair-Hypoplasia The RMRP gene Specific Aims Material and Methods Results: Clinical Studies Mutation Screen of CHH patients Search for Modifiers Functional Studies of human RMRP Mouse Studies Yeast Studies Discussion: Conclusions Summmary Appendix