964 resultados para transcriptional regulatory networks


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Huntington's disease (HD) is a devastating disorder that affects approximately 1 in 10,000 people and is accompanied by neuronal dysfunction and neurodegeneration. HD manifests as a progressive chorea, a decline in mental abilities accompanied by behavioural, emotional and psychiatric problems followed by, dementia, and ultimately, death. The molecular pathology of HD is complex but includes widespread transcriptional dysregulation. Although many transcriptional regulatory molecules have been implicated in the pathogenesis of HD, a growing body of evidence points to the pivotal role of RE1 Silencing Transcription Factor (REST). In HD, REST, translocates from the cytoplasm to the nucleus in neurons resulting in repression of key target genes such as BDNF. Since these original observations, several thousand direct target genes of REST have been identified, including numerous non-coding RNAs including both microRNAs and long non-coding RNAs, several of which are dysregulated in HD. More recently, evidence is emerging that hints at epigenetic abnormalities in HD brain. This in turn, promotes the notion that targeting the epigenetic machinery may be a useful strategy for treatment of some aspects of HD. REST also recruits a host of histone and chromatin modifying activities that can regulate the local epigenetic signature at REST target genes. Collectively, these observations present REST as a hub that coordinates transcriptional, posttranscriptional and epigenetic programmes, many of which are disrupted in HD. We identify several spokes emanating from this REST hub that may represent useful sites to redress REST dysfunction in HD.

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Transcription factors (TFs) are major players in gene regulatory networks and interactions between TFs and their target genes furnish spatiotemporal patterns of gene expression. Establishing the architecture of regulatory networks requires gathering information on TFs, their targets in the genome, and the corresponding binding sites. We have developed GRASSIUS (Grass Regulatory Information Services) as a knowledge-based Web resource that integrates information on TFs and gene promoters across the grasses. In its initial implementation, GRASSIUS consists of two separate, yet linked, databases. GrassTFDB holds information on TFs from maize (Zea mays), sorghum (Sorghum bicolor), sugarcane (Saccharum spp.), and rice (Oryza sativa). TFs are classified into families and phylogenetic relationships begin to uncover orthologous relationships among the participating species. This database also provides a centralized clearinghouse for TF synonyms in the grasses. GrassTFDB is linked to the grass TFome collection, which provides clones in recombination-based vectors corresponding to full-length open reading frames for a growing number of grass TFs. GrassPROMDB contains promoter and cis-regulatory element information for those grass species and genes for which enough data are available. The integration of GrassTFDB and GrassPROMDB will be accomplished through GrassRegNet as a first step in representing the architecture of grass regulatory networks. GRASSIUS can be accessed from www.grassius.org.

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Pós-graduação em Ciências Biológicas (Genética) - IBB

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To understand how biological phenomena emerge, the nonlinear interactions among the components envolved in these and the correspondent connected elements, like genes, proteins, etc., can be represented by a mathematical object called graph or network, where interacting elements are represented by edges connecting pairs of nodes. The analysis of various graph-related properties of biological networks has revealed many clues about biological processes. Among these properties, the community structure, i.e. groups of nodes densely connected among themselves, but sparsely connected to other groups, are important for identifying separable functional modules within biological systems for the comprehension of the high-level organization of the cell. Communities' detection can be performed by many algorithms, but most of them are based on the density of interactions among nodes of the same community. So far, the detection and analysis of network communities in biological networks have only been pursued for networks composed by one type of interaction (e.g. protein-protein interactions or metabolic interactions). Since a real biological network is simultaneously composed by protein-protein, metabolic and transcriptional regulatory interactions, it would be interesting to investigate how communities are organized in this type of network. For this purpose, we detected the communities in an integrated biological network of the Escherichia coli and Saccharomyces cerevisiae by using the Clique Percolation Method and we veri ed, by calculating the frequency of each type of interaction and its related entropy, if components of communities... (Complete abstract click electronic access below)

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Modern sugarcane cultivars are complex hybrids resulting from crosses among several Saccharum species. Traditional breeding methods have been employed extensively in different countries over the past decades to develop varieties with increased sucrose yield and resistance to pests and diseases. Conventional variety improvement, however, may be limited by the narrow pool of suitable genes. Thus, molecular genetics is seen as a promising tool to assist in the process of developing improved varieties. The SUCEST-FUN Project (http://sucest-fun.org) aims to associate function with sugarcane genes using a variety of tools, in particular those that enable the study of the sugarcane transcriptome. An extensive analysis has been conducted to characterise, phenotypically, sugarcane genotypes with regard to their sucrose content, biomass and drought responses. Through the analysis of different cultivars, genes associated with sucrose content, yield, lignin and drought have been identified. Currently, tools are being developed to determine signalling and regulatory networks in grasses, and to sequence the sugarcane genome, as well as to identify sugarcane promoters. This is being implemented through the SUCEST-FUN (http://sucest-fun.org) and GRASSIUS databases (http://grassius.org), the cloning of sugarcane promoters, the identification of cis-regulatory elements (CRE) using Chromatin Immunoprecipitation-sequencing (ChIP-Seq) and the generation of a comprehensive Signal Transduction and Transcription gene catalogue (SUCAST Catalogue).

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Transposable elements (TEs) account for a large portion of plant genomes, particularly in grasses, in which they correspond to 50%-80% of the genomic content. TEs have recently been shown to be a source of new genes and new regulatory networks. The most striking contribution of TEs is referred as "molecular domestication", by which the element coding sequence loses its movement capacity and acquires cellular function. Recently, domesticated transposases known as mustang and derived from the Mutator element have been described in sugarcane. In order to improve our understanding of the function of these proteins, we identified mustang genes from Sorghum bicolor and Zea mays and performed a phenetic analysis to assess the diversity and evolutionary history of this gene family. This analysis identified orthologous groups and showed that mustang genes are highly conserved in grass genomes. We also explored the transcriptional activity of sugarcane mustang genes in heterologous and homologous systems. These genes were found to be ubiquitously transcribed, with shoot apical meristem having the highest expression levels, and were downregulated by phytohormones. Together, these findings suggest the possible involvement of mustang proteins in the maintenance of hormonal homeostasis.

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Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

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Abstract Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks.

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Die zeitliche und räumliche Expression von Genen trägt zu einem entscheidenden Ausmaß zu der Entwicklung eines Organismus bei. Unter vielen Faktoren spielt dabei die transkriptionelle Regulation eine wichtige Rolle. Diese basiert auf Anwesenheit und Binden von regulatorischen Proteinen an cis-regulatorischen Sequenzen (CRMs) und deren Einfluss auf die Transkriptionsmaschinerie am Promotor. Veränderungen der CRMs können zu Veränderungen der Genexpression führen, und somit einen Beitrag zur morphologischen Evolution leisten. rnIn dieser Arbeit wurde die transkriptionelle Regulation des Drosophila melanogaster Gens optomotor-blind insbesondere in den pupalen Tergiten untersucht. In einem Enhancer-Reporter screen wurde eine regulatorische Region in Intron IV, die Reportergen-Expression in den pupalen Tergiten treibt, identifiziert. Große Teile dieser Region (ombTU10 und ombTU11) trieben Reportergen-Expression in einem omb-ähnlichen Muster. Eine weitere Region (ombTU12) trieb Expression in einem für Hh-Zielgene typischen Expressionsmuster. Für ombTU12 konnte eine Hh-Abhängigkeit nachgewiesen werden. Die für Hh-Zielgene typische Enhanceraktivität konnte in dem Subfragment ombTU12Amin lokalisiert werden, welches zwei konservierte Bindestellen des Effektors der Hh-Signaltransduktionskaskase, Cubitus interruptus (Ci), enthält. Eine deutliche Abhängigkeit der Expression dieses Fragments von den Ci-Bindestellen konnte bisher aber noch nicht nachgewiesen werden.rnDeletionen verschiedener Bereiche dieser Tergitenenhancer-Region aus dem endogenen Gen sollten Aufschluss über deren Notwendigkeit in der Regulation von omb geben. Die Deletion des Fragments ombTU10 (ΔombTU10-2) führte zu einer Variabilität in der Pigmentierung der Abdominalsegmente A5 und A6 der Weibchen. Eine Deletion von Teilen des hh-responsiven Fragments ombTU12 (ΔombTU12A) zeigte keinen abdominalen Phänotyp. Dies deutet auf eine redundante Wirkung der Fragmente untereinander, oder mit einem weiteren bisher nicht identifizierten Tergitenenhancer im omb-Locus hin.rnFragmente, die in den pupalen Tergiten Reportergen-Expression trieben, waren zum Teil auch in Imaginalscheiben von Larven aktiv. Desweiteren wurde gezeigt, dass Fragmente, die in Isolation Reportergen-Expression trieben, als Fusionskonstrukt mit benachbarten genomischen Sequenzen keine Expression zeigten und somit im genomischen Kontext inaktiv sein können. Demzufolge sind nicht nur Aktivator- sondern auch Repressorregionen für die korrekte Expression eines Gens von Bedeutung.rnDie Analyse von omb Enhancer-Trap Insertionen zeigte, dass von drei untersuchten Typen (PlacW, PGalW und PGawB) nur Insertionen vom letzteren in den pupalen Tergiten aktiv waren. Von vier PGawB Insertionen waren nur drei aktiv. Es ist denkbar, dass die Orientierung der inaktiven Insertion für die mangelnde Responsivität verantwortlich ist.rn

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Real living cell is a complex system governed by many process which are not yet fully understood: the process of cell differentiation is one of these. In this thesis work we make use of a cell differentiation model to develop gene regulatory networks (Boolean networks) with desired differentiation dynamics. To accomplish this task we have introduced techniques of automatic design and we have performed experiments using various differentiation trees. The results obtained have shown that the developed algorithms, except the Random algorithm, are able to generate Boolean networks with interesting differentiation dynamics. Moreover, we have presented some possible future applications and developments of the cell differentiation model in robotics and in medical research. Understanding the mechanisms involved in biological cells can gives us the possibility to explain some not yet understood dangerous disease, i.e the cancer. Le cellula è un sistema complesso governato da molti processi ancora non pienamente compresi: il differenziamento cellulare è uno di questi. In questa tesi utilizziamo un modello di differenziamento cellulare per sviluppare reti di regolazione genica (reti Booleane) con dinamiche di differenziamento desiderate. Per svolgere questo compito abbiamo introdotto tecniche di progettazione automatica e abbiamo eseguito esperimenti utilizzando vari alberi di differenziamento. I risultati ottenuti hanno mostrato che gli algoritmi sviluppati, eccetto l'algoritmo Random, sono in grado di poter generare reti Booleane con dinamiche di differenziamento interessanti. Inoltre, abbiamo presentato alcune possibili applicazioni e sviluppi futuri del modello di differenziamento in robotica e nella ricerca medica. Capire i meccanismi alla base del funzionamento cellulare può fornirci la possibilità di spiegare patologie ancora oggi non comprese, come il cancro.

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It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

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I have cloned cDNAs corresponding to two distinct genes, Xlmf1 and Xlmf25, which encode skeletal muscle-specific, transcriptional regulatory proteins. These proteins are members of the helix-loop-helix family of DNA binding factors, and are most homologous to MyoD1. These two genes have disparate temporal expression patterns during early embryogenesis; although, both transcripts are present exclusively in skeletal muscle of the adult. Xlmf1 is first detected 7 hours after fertilization, shortly after the midblastula transition. Xlmf25 is detected in maternal stores of mRNA, during early cleavage stages of the embryo and throughout later development. Both Xlmf1 and Xlmf25 transcripts are detected prior to the expression of other, previously characterized, muscle-specific genes. The ability of Xlmf1 and Xlmf25 to convert mouse 10T1/2 fibroblasts to a myogenic phenotype demonstrates their activity as myogenic regulatory factors. Additionally, Xlmf1 and Xlmf25 can directly transactivate a reporter gene linked to the muscle-specific, muscle creatine kinase (MCK) enhancer. The functional properties of Xlmf1 and Xlmf25 proteins were further explored by investigating their interactions with the binding site in the MCK enhancer. Analysis of dissociation rates revealed that Xlmf25-E12 dimers had a two-fold lower avidity for this site than did Xlmf1-E12 dimers. Clones containing genomic sequence of Xlmf1 and Xlmf25 have been isolated. Reporter gene constructs containing a lac-z gene driven by Xlmf1 regulatory sequences were analyzed by embryo injections and transfections into cultured muscle cells. Elements within $-$200 bp of the transcription start site can promote high levels of muscle specific expression. Embryo injections show that 3500 bp of upstream sequence is sufficient to drive somite specific expression. EMSAs and DNAse I footprint analysis has shown the discrete interaction of factors with several cis-elements within 200 bp of the transcription start site. Mutation of several of these elements shows a positive requirement for two CCAAT boxes and two E boxes. It is evident from the work performed with this promoter that Xlmf1 is tightly regulated during muscle cell differentiation. This is not surprising given the fact that its gene product is crucial to the determination of cell fate choices. ^

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Small non-protein-coding RNA (ncRNA) molecules have been recognized recently as major contributors to regulatory networks in controlling gene expression in a highly efficient manner. While the list of validated ncRNAs that regulate crucial cellular processes grows steadily, not a single ncRNA has been identified that directly interacts and regulates the ribosome during protein biosynthesis (with the notable exceptions of 7SL RNA and tmRNA). All of the recently discovered regulatory ncRNAs that act on translation (e.g. microRNAs, siRNAs or antisense RNAs) target the mRNA rather than the ribosome. This is unexpected, given the central position the ribosome plays during gene expression. Furthermore it is strongly assumed that the primordial translation system in the ‘RNA world’ most likely received direct regulatory input from ncRNA-like cofactors. The fundamental question that we would like to ask is: Does the ‘RNA world still communicate’ with the ribosome? To address this question, we have analyzed the small ncRNA interactomes of ribosomes of prokaryotic (H. volcanii, S. aureus) and unicellular eukaryotic model organisms. Deep-sequencing and subsequent bioinformatic analyses revealed thousands of putative ribosome-associated ncRNAs. For a subset of these ncRNA candidates we have gathered experimental evidence that they are expressed in a stress-dependent manner and indeed directly target the ribosome. In the archaeon H. volcanii a tRNA-derived fragment was identified to target the small ribosomal subunit upon alkaline stress in vitro and in vivo. As a consequence of ribosome binding, this tRNA-fragment reduces protein synthesis by interfering with the peptidyl transferase activity. Our data reveal the ribosome as a novel target for small regulatory ncRNAs in all domains of life. Ribosome-bound ncRNAs are capable of fine tuning translation and might represent a so far largely unexplored class of regulatory sRNAs.

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Small non-protein-coding RNA (ncRNA) molecules have been recognized recently as major contributors to regulatory networks in controlling gene expression in a highly efficient manner. While the list of validated ncRNAs that regulate crucial cellular processes grows steadily, not a single ncRNA has been identified that directly interacts and regulates the ribosome during protein biosynthesis (with the notable exceptions of 7SL RNA and tmRNA). All of the recently discovered regulatory ncRNAs that act on translation (e.g. microRNAs, siRNAs or antisense RNAs) target the mRNA rather than the ribosome. This is unexpected, given the central position the ribosome plays during gene expression. Furthermore it is strongly assumed that the primordial translation system in the ‘RNA world’ most likely received direct regulatory input from ncRNA-like cofactors. The fundamental question that we would like to ask is: Does the ‘RNA world still communicate’ with the ribosome? To address this question, we have analyzed the small ncRNA interactomes of ribosomes of organisms from all three domains of life. Deep-sequencing and subsequent bioinformatic analyses revealed thousands of putative ribosome-associated ncRNAs.1,2 For a subset of these ncRNA candidates we have gathered experimental evidence that they are expressed in a stress-dependent manner and indeed directly target the ribosome. We show that some of these ribosome-bound small ncRNAs are capable of fine tuning protein synthesis in vitro and in vivo. Our data therefore reveal the ribosome as a novel target for small regulatory ncRNAs in all domains of life and suggest the existence of a so far largely unexplored mechanism of translation regulation.