954 resultados para Genomic data


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A eficiência econômica da bovinocultura leiteira está relacionada à utilização de animais que apresentem, concomitantemente, bom desempenho quanto à produção, reprodução, saúde e longevidade. Nisto, o índice de seleção configura-se como ferramenta importante ao aumento da lucratividade nesse sistema, visto que permite a seleção de reprodutores para várias características simultaneamente, considerando a relação entre elas bem como a relevância econômica das mesmas. Com a recente disponibilidade de dados genômicos tornou-se ainda possível expandir a abrangência e acurácia dos índices de seleção por meio do aumento do número e qualidade das informações consideradas. Nesse contexto, dois estudos foram desenvolvidos. No primeiro, o objetivo foi estimar parâmetros genéticos e valores genéticos (VG) para características relacionadas à produção e qualidade do leite incluindo-se a informação genômica na avaliação genética. Foram utilizadas medidas de idade ao primeiro parto (IPP), produção de leite (PROD), teor de gordura (GOR), proteína (PROT), lactose, caseína, escore de células somáticas (ECS) e perfil de ácidos graxos de 4.218 vacas bem como os genótipos de 755 vacas para 57.368 polimorfismos de nucleotídeo único (SNP). Os componentes de variância e VG foram obtidos por meio de um modelo misto animal, incluindo-se os efeitos de grupos de contemporâneas, ordem de lactação, dias em lactação e os efeitos aditivo genético, ambiente permanente e residual. Duas abordagens foram desenvolvidas: uma tradicional, na qual a matriz de relacionamentos é baseada no pedigree; e uma genômica, na qual esta matriz é construída combinando-se a informação de pedigree e dos SNP. As herdabilidades variaram de 0,07 a 0,39. As correlações genéticas entre PROD e os componentes do leite variaram entre -0,45 e -0,13 enquanto correlações altas e positivas foram estimadas entre GOR e os ácidos graxos. O uso da abordagem genômica não alterou as estimativas de parâmetros genéticos; contudo, houve aumento entre 1,5% e 6,8% na acurácia dos VG, à exceção de IPP, para a qual houve uma redução de 1,9%. No segundo estudo, o objetivo foi incorporar a informação genômica no desenvolvimento de índices econômicos de seleção. Neste, os VG para PROD, GOR, PROT, teor de ácidos graxos insaturados (INSAT), ECS e vida produtiva foram combinados em índices de seleção ponderados por valores econômicos estimados sob três cenários de pagamento: exclusivamente por volume de leite (PAG1); por volume e por componentes do leite (PAG2); por volume e componentes do leite incluindo INSAT (PAG3). Esses VG foram preditos a partir de fenótipos de 4.293 vacas e genótipos de 755 animais em um modelo multi-característica sob as abordagens tradicional e genômica. O uso da informação genômica influenciou os componentes de variância, VG e a resposta à seleção. Entretanto, as correlações de ranking entre as abordagens foram altas nos três cenários, com valores entre 0,91 e 0,99. Diferenças foram principalmente observadas entre PAG1 e os demais cenários, com correlações entre 0,67 e 0,88. A importância relativa das características e o perfil dos melhores animais foram sensíveis ao cenário de remuneração considerado. Assim, verificou-se como essencial a consideração dos valores econômicos das características na avaliação genética e decisões de seleção.

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Thesis (Ph.D.)--University of Washington, 2016-06

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The reconstructed cellular metabolic network of Mus musculus, based on annotated genomic data, pathway databases, and currently available biochemical and physiological information, is presented. Although incomplete, it represents the first attempt to collect and characterize the metabolic network of a mammalian cell on the basis of genomic data. The reaction network is generic in nature and attempts to capture the carbon, energy, and nitrogen metabolism of the cell. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, including transport reactions between the compartments and the extracellular medium. The reaction list consists of 872 internal metabolites involved in a total of 1220 reactions, whereof 473 relate to known open reading frames. Initial in silico analysis of the reconstructed model is presented.

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The regulation of osteoclast differentiation in the bone microenvironment is critical for normal bone remodeling, as well as for various human bone diseases. Over the last decade, our knowledge of how osteoclast differentiation occurs has progressed rapidly. We highlight some of the major advances in understanding how cell signaling and transcription are integrated to direct the differentiation of this cell type. These studies used genetic, molecular, and biochemical approaches. Additionally, we summarize data obtained from studies of osteoclast differentiation that used the functional genomic approach of global gene profiling applied to osteoclast differentiation. This genomic data confirms results from studies using the classical experimental approaches and also may suggest new modes by which osteoclast differentiation and function can be modulated. Two conclusions that emerge are that osteoclast differentiation depends on a combination of fairly ubiquitously expressed transcription factors rather than unique osteoclast factors, and that the overlay of cell signaling pathways on this set of transcription factors provides a powerful mechanism to fine tune the differentiation program in response to the local bone microenvironment.

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Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

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Peroxisomes are small subcellular compartments that utilize proteins manufactured in the cytoplasm. Proteins use one of two peroxisomal import pathways. This paper presents a simple evolutionary search for a motif that describes the signal used by one of the two pathways: PTS2. The evolved motif has a discriminative accuracy exceeding previously manually curated motifs and can be used to screen genomic data for putative peroxisomal proteins.

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The ABL family of non-receptor tyrosine kinases, ABL1 (also known as c-ABL) and ABL2 (also known as Arg), links diverse extracellular stimuli to signaling pathways that control cell growth, survival, adhesion, migration and invasion. ABL tyrosine kinases play an oncogenic role in human leukemias. However, the role of ABL kinases in solid tumors including breast cancer progression and metastasis is just emerging.

To evaluate whether ABL family kinases are involved in breast cancer development and metastasis, we first analyzed genomic data from large-scale screen of breast cancer patients. We found that ABL kinases are up-regulated in invasive breast cancer patients and high expression of ABL kinases correlates with poor prognosis and early metastasis. Using xenograft mouse models combined with genetic and pharmacological approaches, we demonstrated that ABL kinases are required for regulating breast cancer progression and metastasis to the bone. Using next generation sequencing and bioinformatics analysis, we uncovered a critical role for ABL kinases in promoting multiple oncogenic pathways including TAZ and STAT5 signaling networks and the epithelial to mesenchymal transition (EMT). These findings revealed a role for ABL kinases in regulating breast cancer tumorigenesis and bone metastasis and provide a rationale for targeting breast tumors with ABL-specific inhibitors.

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Expression Quantitative Trait Loci (eQTL) analysis allows for the identification of genetic variation associated with variation in gene expression. It is often unclear however, which of the associated variants are causal, and by what mechanism. Integrating functional genomic data with eQTL data can provide insight into the impact of natural variation in the population, and the nature of the transcriptional machinery itself. In this thesis, I integrate functional genomic data with eQTL data derived from both 5’ CAGE and 3’ TagXseq expression assays, in developing embryos. I first use both datasets to analyse the transcription landscape in embryonic D., melanogaster, and then carry out an analysis of sequence motifs associated with transcription factor binding sites, promoters, and 3’ polyadenylation sites. Finally, I integrate functional genomic data, including these novel sequence motifs, to shed light on the mechanisms of gene expression variation in D.,melanogaster. I am able to demonstrate that some variants effecting gene regulation in Drosophila are found within haplotypes which buffer their effects.

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Schistosomiasis is a neglected tropical disease that affects more than 200 million people worldwide. The main disease-causing agents, Schistosoma japonicum, S. mansoni and S. haematobium, are blood flukes that have complex life cycles involving a snail intermediate host. In Asia, S. japonicum causes hepatointestinal disease (schistosomiasis japonica) and is challenging to control due to a broad distribution of its snail hosts and range of animal reservoir hosts. In China, extensive efforts have been underway to control this parasite, but genetic variability in S. japonicum populations could represent an obstacle to eliminating schistosomiasis japonica. Although a draft genome sequence is available for S. japonicum, there has been no previous study of molecular variation in this parasite on a genome-wide scale. In this study, we conducted the first deep genomic exploration of seven S. japonicum populations from mainland China, constructed phylogenies using mitochondrial and nuclear genomic data sets, and established considerable variation between some of the populations in genes inferred to be linked to key cellular processes and/or pathogen-host interactions. Based on the findings from this study, we propose that verifying intraspecific conservation in vaccine or drug target candidates is an important first step toward developing effective vaccines and chemotherapies against schistosomiasis.

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FMRFamide-like peptide (FLP) signalling systems are core to nematode neuromuscular function. Novel drug discovery efforts associated with nematode FLP/FLP receptor biology are advanced through the accumulation of basic biological data that can reveal subtle complexities within the neuropeptidergic system. This study reports the characterisation of FMRFamide-like peptide encoding gene-11 (flp-11) and FMRFamide-like peptide encoding gene-32 (flp-32), two distinct flp genes which encode the analogous peptide, AMRN(A/S)LVRFamide, in multiple nematode species - the only known example of this phenomenon within the FLPergic system of nematodes. Using bioinformatics, in situ hybridisation, immunocytochemistry and behavioural assays we show that: (i) flp-11 and -32 are distinct flp genes expressed individually or in tandem across multiple nematode species, where they encode a highly similar peptide; (ii) flp-11 does not appear to be the most widely expressed flp in Caenorhabditis elegans; (iii) in species expressing both flp-11 and flp-32, flp-11 displays a conserved, restricted expression pattern across nematode clades and lifestyles; (iv) in species expressing both flp-11 and flp-32, flp-32 expression is more widespread and less conserved than flp-11; (v) in species expressing only flp-11, the flp-11 expression profile is more similar to the flp-32 profile observed in species expressing both; and (vi) FLP-11 peptides inhibit motor function in multiple nematode species. The biological significance and evolutionary origin of flp-11 and -32 peptide duplication remains unclear despite attempts to identify a common ancestor; this may become clearer as the availability of genomic data improves. This work provides insight into the complexity of the neuropeptidergic system in nematodes, and begins to examine how nematodes may compensate for structural neuronal simplicity. From a parasite control standpoint this work underscores the importance of basic biological data, and has wider implications for the utility of C. elegans as a model for parasite neurobiology.

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Oogenesis is a prerequisite for embryogenesis in Metazoa. During both biological processes important decisions must be made to form the embryo and hence ensure the next generation: (1) Maternal gene products (mRNAs, proteins and nutrients) must be supplied to the embryo. (2) Polarity must be established and axes must be specified. While incorporation of maternal gene products occurs during oogenesis, the time point of polarity establishment and axis specification varies among species, as it is accomplished either prior, during, or after fertilisation. But not only the time point when these events take place varies among species but also the underlying mechanisms by which they are triggered. For the nematode model Caenorhabditis elegans the underlying pathways and gene regulatory networks (GRNs) are well understood. It is known that there the sperm entry point initiates a primary polarity in the 1-celled egg and with it the establishment of the anteroposterior axis. However, studies of other nematodes demonstrated that polarity establishment can be independent of sperm entry (Goldstein et al., 1998; Lahl et al., 2006) and that cleavage patterns, symmetry formation and cell specification also differ from C. elegans. In contrast to the studied Chromadorea (more derived nematodes including C. elegans), embryos of some marine Enoplea (more basal representatives) even show no discernible early polarity and blastomeres can adopt variable cell fates (Voronov and Panchin 1998). The underlying pathways controlling the obviously variant embryonic processes in non-Caenorhabditis nematodes are essentially unknown. In this thesis I addressed this issue by performing a detailed unbiased comparative transcriptome analysis based on microarrays and RNA sequencing of selected developmental stages in a variety of nematodes from different phylogenetic branches with C. elegans as a reference system and a nematomorph as an outgroup representative. In addition, I made use of available genomic data to determine the presence or absence of genes for which no expression had been detected. In particular, I focussed on components of selected pathways or GRNs which are known to play essential roles during C. elegans development and/or other invertebrate or vertebrate model systems. Oogenesis must be regulated differently in non-Caenorhabditis nematodes, as crucial controlling components of Wnt and sex determination signaling are absent in these species. In this respect, I identified female-specific expression of potential polarity associated genes during gonad development and oogenesis in the Enoplean nematode Romanomermis culicivorax. I could show that known downstream components of the polarity complexes PAR-3/-6/PKC-3 and PAR-1/-2 are absent in non-Caenorhabditis species. Even PAR-2 as part of the polarity complex does not exist in these nematodes. Instead, transcriptomes of nematodes (including C. elegans), show expression of other polarity-associated complexes such as the Lgl (Lethal giant larvae) complex. This result could pose an alternative route for nematodes and nematomorphs to initiate polarity during early embryogenesis. I could show that crucial pathways of axis specification, such as Wnt and BMP are very different in C. elegans compared to other nematodes. In the former, Wnt signaling, for instance, is mediated by four paralogous beta-catenins, while other Chromadorea have fewer and Enoplea only one beta-catenin. The transcriptomes of R. culicivorax and the nematomorph show that regulators of BMP (e.g. Chordin), are specifically expressed during early embryogenesis only in Enoplea and the close outgroup of nematomorphs. In conclusion, my results demonstrate that the molecular machinery controlling oogenesis and embryogenesis in nematodes is unexpectedly variable and C. elegans cannot be taken as a general model for nematode development. Under this perspective, Enoplean nematodes show more similarities with outgroups than with C. elegans. It appears that certain pathway components were lost or gained during evolution and others adopted new functions. Based on my findings I can conjecture, which pathway components may be ancestral and which were newly acquired in the course of nematode evolution.

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We present a nonparametric Bayesian method for disease subtype discovery in multi-dimensional cancer data. Our method can simultaneously analyse a wide range of data types, allowing for both agreement and disagreement between their underlying clustering structure. It includes feature selection and infers the most likely number of disease subtypes, given the data. We apply the method to 277 glioblastoma samples from The Cancer Genome Atlas, for which there are gene expression, copy number variation, methylation and microRNA data. We identify 8 distinct consensus subtypes and study their prognostic value for death, new tumour events, progression and recurrence. The consensus subtypes are prognostic of tumour recurrence (log-rank p-value of $3.6 \times 10^{-4}$ after correction for multiple hypothesis tests). This is driven principally by the methylation data (log-rank p-value of $2.0 \times 10^{-3}$) but the effect is strengthened by the other 3 data types, demonstrating the value of integrating multiple data types. Of particular note is a subtype of 47 patients characterised by very low levels of methylation. This subtype has very low rates of tumour recurrence and no new events in 10 years of follow up. We also identify a small gene expression subtype of 6 patients that shows particularly poor survival outcomes. Additionally, we note a consensus subtype that showly a highly distinctive data signature and suggest that it is therefore a biologically distinct subtype of glioblastoma. The code is available from https://sites.google.com/site/multipledatafusion/

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Clare, A. (2005) Integration of genomic and phenotypic data. In Data Analysis and Visualization in Genomics and Proteomics, Eds. Francisco Azuaje and Joaquin Dopazo, Wiley, London. ISBN: 0-470-09439-7

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Background: Affymetrix GeneChip arrays are widely used for transcriptomic studies in a diverse range of species. Each gene is represented on a GeneChip array by a probe- set, consisting of up to 16 probe-pairs. Signal intensities across probe- pairs within a probe-set vary in part due to different physical hybridisation characteristics of individual probes with their target labelled transcripts. We have previously developed a technique to study the transcriptomes of heterologous species based on hybridising genomic DNA (gDNA) to a GeneChip array designed for a different species, and subsequently using only those probes with good homology. Results: Here we have investigated the effects of hybridising homologous species gDNA to study the transcriptomes of species for which the arrays have been designed. Genomic DNA from Arabidopsis thaliana and rice (Oryza sativa) were hybridised to the Affymetrix Arabidopsis ATH1 and Rice Genome GeneChip arrays respectively. Probe selection based on gDNA hybridisation intensity increased the number of genes identified as significantly differentially expressed in two published studies of Arabidopsis development, and optimised the analysis of technical replicates obtained from pooled samples of RNA from rice. Conclusion: This mixed physical and bioinformatics approach can be used to optimise estimates of gene expression when using GeneChip arrays.

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BACKGROUND: Recurrent airway obstruction (RAO) is a severe chronic respiratory disease affecting horses worldwide, though mostly in the Northern hemisphere. Environmental as well as genetic factors strongly influence the course and prognosis of the disease. Research has been focused on characterization of immunologic factors contributing to inflammatory responses, on genetic linkage analysis, and, more recently, on proteomic analysis of airway secretions from affected horses. The goal of this study was to investigate the interactions between eight candidate genes previously identified in a genetic linkage study and proteins expressed in bronchoalveolar lavage fluid (BALF) collected from healthy and RAO-affected horses. The analysis was carried out with Ingenuity Pathway Analysis(R) bioinformatics software. RESULTS: The gene with the greatest number of indirect interactions with the set of proteins identified is Interleukin 4 Receptor (IL-4R), whose protein has also been detected in BALF. Interleukin 21 receptor and chemokine (C-C motif) ligand 24 also showed a large number of interactions with the group of detected proteins. Protein products of other genes like that of SOCS5, revealed direct interactions with the IL-4R protein. The interacting proteins NOD2, RPS6KA5 and FOXP3 found in several pathways are reported regulators of the NFkappaB pathway. CONCLUSIONS: The pathways generated with IL-4R highlight possible important intracellular signaling cascades implicating, for instance, NFkappaB. Furthermore, the proposed interaction between SOCS5 and IL-4R could explain how different genes can lead to identical clinical RAO phenotypes, as observed in two Swiss Warmblood half sibling families because these proteins interact upstream of an important cascade where they may act as a functional unit.