106 resultados para Transcriptomics
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Le système hématopoïétique est un tissu en constant renouvellement et les cellules souches hématopoïétiques (CSHs) sont indispensables pour soutenir la production des cellules matures du sang. Deux fonctions définissent les CSHs; la propriété d’auto-renouvellement, soit la capacité de préserver l’identité cellulaire suivant une division, et la multipotence, le potentiel de différenciation permettant de générer toutes les lignées hématopoïétiques. Chez l’adulte, la majorité des CSHs sont quiescentes et l’altération de cet état corrèle avec une diminution du potentiel de reconstitution des CSHs, suggérant que la quiescence protège les fonctions des CSHs. La quiescence est un état réversible et dynamique et les réseaux génétiques le contrôlant restent peu connus. Un nombre croissant d’évidences suggère que si à l’état d’homéostasie il y a une certaine redondance entre les gènes impliqués dans ces réseaux de contrôle, leurs rôles spécifiques sont révélés en situation de stress. La famille des bHLHs (basic helix-loop-helix) inclue différentes classes des protéines dont ceux qui sont tissu-spécifiques comme SCL, et les protéines E, comme E12/E47 et HEB. Certains bHLHs sont proposés êtres important pour la fonction des cellules souches, mais cela ne fait pas l’unanimité, car selon le contexte cellulaire, il y a redondance entre ces facteurs. La question reste donc entière, y a-t-il un rôle redondant entre les bHLHs d’une même classe pour la fonction à long-terme des CSHs? Les travaux présentés dans cette thèse visaient dans un premier temps à explorer le lien encore mal compris entre la quiescence et la fonction des CSHs en mesurant leurs facultés suite à un stress prolifératif intense et dans un deuxième temps, investiguer l’importance et la spécificité de trois gènes pour la fonction des CSHs adultes, soit Scl/Tal1, E2a/Tcf3 et Heb/Tcf12. Pour répondre à ces questions, une approche cellulaire (stress prolifératif) a été combinée avec une approche génétique (invalidation génique). Plus précisément, la résistance des CSHs au stress prolifératif a été étudiée en utilisant deux tests fonctionnels quantitatifs optimisés, soit un traitement basé sur le 5-fluorouracil, une drogue de chimiothérapie, et la transplantation sérielle en nombre limite. Dans la mesure où la fonction d’un réseau génique ne peut être révélée que par une perturbation intrinsèque, trois modèles de souris, i.e. Scl+/-, E2a+/- et Heb+/- ont été utilisés. Ceci a permis de révéler que l’adaptation des CSHs au stress prolifératif et le retour à l’équilibre est strictement contrôlé par les niveaux de Scl, lesquels règlent le métabolisme cellulaire des CSHs en maintenant l’expression de gènes ribosomaux à un niveau basal. D’autre part, bien que les composantes du réseau puissent paraître redondants à l’équilibre, mes travaux montrent qu’en situation de stress prolifératif, les niveaux de Heb restreignent la prolifération excessive des CSHs en induisant la sénescence et que cette fonction ne peut pas être compensée par E2a. En conclusion, les résultats présentés dans cette thèse montrent que les CSHs peuvent tolérer un stress prolifératif intense ainsi que des dommages à l’ADN non-réparés, tout en maintenant leur capacité de reconstituer l’hématopoïèse à long-terme. Cela implique cependant que leur métabolisme revienne au niveau de base, soit celui trouvé à l’état d’homéostasie. Par contre, avec l’augmentation du nombre de division cellulaire les CSHs atteignent éventuellement une limite d’expansion et entrent en sénescence.
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Amb la finalitat de garantir la seguretat dels consumidors i del medi ambient, a la UE els aliments modificats genèticament (MG) estan sotmesos a un rigorós procés d'autorització que inclou: caracterització molecular del transgèn i anàlisis comparatives a nivell nutricional i agronòmic. L'ús de tècniques de profiling per avaluar la possible existència d'efectes no esperats derivats de la inserció i/o expressió del transgèn s'ha proposat com a una eina complementària per l'avaluació de la seguretat alimentària. L'objectiu de la present tesis és avaluar la variabilitat associada a la inserció i expressió de transgens en plantes, utilitzant com a exemple el blat de moro MON810. Es pretén complementar les aproximacions ja existents basades en l'estudi de paràmetres concrets mitjançant les tècniques de profiling. Des del punt de vista transcriptòmic i proteòmic, les varietats de blat de moro MON810 semblen ser substancialment equivalents a les seves varietats comparables no-MG. En conseqüència, és possible la producció de plantes MG amb el mínim d'efectes no esperats.
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Background: Hexaploid wheat is one of the most important cereal crops for human nutrition. Molecular understanding of the biology of the developing grain will assist the improvement of yield and quality traits for different environments. High quality transcriptomics is a powerful method to increase this understanding. Results: The transcriptome of developing caryopses from hexaploid wheat ( Triticum aestivum, cv. Hereward) was determined using Affymetrix wheat GeneChip (R) oligonucleotide arrays which have probes for 55,052 transcripts. Of these, 14,550 showed significant differential regulation in the period between 6 and 42 days after anthesis ( daa). Large changes in transcript abundance were observed which were categorised into distinct phases of differentiation ( 6 - 10 daa), grain fill ( 12 - 21 daa) and desiccation/maturation ( 28 - 42 daa) and were associated with specific tissues and processes. A similar experiment on developing caryopses grown with dry and/or hot environmental treatments was also analysed, using the profiles established in the first experiment to show that most environmental treatment effects on transcription were due to acceleration of development, but that a few transcripts were specifically affected. Transcript abundance profiles in both experiments for nine selected known and putative wheat transcription factors were independently confirmed by real time RT-PCR. These expression profiles confirm or extend our knowledge of the roles of the known transcription factors and suggest roles for the unknown ones. Conclusion: This transcriptome data will provide a valuable resource for molecular studies on wheat grain. It has been demonstrated how it can be used to distinguish general developmental shifts from specific effects of treatments on gene expression and to diagnose the probable tissue specificity and role of transcription factors.
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A novel methodology is described in which transcriptomics is combined with the measurement of bread-making quality and other agronomic traits for wheat genotypes grown in different environments (wet and cool or hot and dry conditions) to identify transcripts associated with these traits. Seven doubled haploid lines from the Spark x Rialto mapping population were selected to be matched for development and known alleles affecting quality. These were grown in polytunnels with different environments applied 14 days post-anthesis, and the whole experiment was repeated over 2 years. Transcriptomics using the wheat Affymetrix chip was carried out on whole caryopsis samples at two stages during grain filling. Transcript abundance was correlated with the traits for approximately 400 transcripts. About 30 of these were selected as being of most interest, and markers were derived from them and mapped using the population. Expression was identified as being under cis control for 11 of these and under trans control for 18. These transcripts are candidates for involvement in the biological processes which underlie genotypic variation in these traits.
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There is a strong desire to exploit transcriptomics data from model species for the genetic improvement of non-model crops. Here, we use gene expression profiles from the commercial model Pinus taeda to identify candidate genes implicated in juvenile-mature wood transition in the non-model relative, P. sylvestris. Re-analysis of 'public domain' SAGE data from xylem tissues of P. taeda revealed 283 mature-abundant and 396 juvenile-abundant tags (P < 0.01), of which 70 and 137, respectively matched to genes with known function. Based on sequence similarity, we then isolated 16 putative homologues of genes that in P. taeda exhibited widest divergence in expression between juvenile and mature samples. Candidate expression levels in P. sylvestris were almost invariably differential between juvenile and mature woody tissue samples among two cohorts of five trees collected from the same seed source and selected for genetic uniformity by genetic distance analysis. However, the direction of differential expression was not always consistent with that described in the original P. taeda SAGE data. Correlation was observed between gene expression and juvenile-mature wood anatomical characteristics by OPLS analysis. Four candidates (alpha-tubulin, porin MIP1, lipid transfer protein and aquaporin like protein) apparently had greatest influence on the wood traits measured. Speculative function of these genes in relation to juvenile-mature wood transition is briefly explored. Thus, we demonstrate the feasibility of exploiting SAGE data from a model species to identify consistently differentially expressed candidates in a related non-model species.
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Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.
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The transcriptome of an organism is its set of gene transcripts (mRNAs) at a defined spatial and temporal locus. Because gene expression is affected markedly by environmental and developmental perturbations, it is widely assumed that transcriptome divergence among taxa represents adaptive phenotypic selection. This assumption has been challenged by neutral theories which propose that stochastic processes drive transcriptome evolution. To test for evidence of neutral transcriptome evolution in plants, we quantified 18 494 gene transcripts in nonsenescent leaves of 14 taxa of Brassicaceae using robust cross-species transcriptomics which includes a two-step physical and in silico-based normalization procedure based on DNA similarity among taxa. Transcriptome divergence correlates positively with evolutionary distance between taxa and with variation in gene expression among samples. Results are similar for pseudogenes and chloroplast genes evolving at different rates. Remarkably, variation in transcript abundance among root-cell samples correlates positively with transcriptome divergence among root tissues and among taxa. Because neutral processes affect transcriptome evolution in plants, many differences in gene expression among or within taxa may be nonfunctional, reflecting ancestral plasticity and founder effects. Appropriate null models are required when comparing transcriptomes in space and time.
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Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2 of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log(2) units (6 of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions: This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells.
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Affymetrix GeneChip (R) arrays are used widely to study transcriptional changes in response to developmental and environmental stimuli. GeneChip (R) arrays comprise multiple 25-mer oligonucleotide probes per gene and retain certain advantages over direct sequencing. For plants, there are several public GeneChip (R) arrays whose probes are localised primarily in 39 exons. Plant whole-transcript (WT) GeneChip (R) arrays are not yet publicly available, although WT resolution is needed to study complex crop genomes such as Brassica, which are typified by segmental duplications containing paralogous genes and/or allopolyploidy. Available sequence data were sampled from the Brassica A and C genomes, and 142,997 gene models identified. The assembled gene models were then used to establish a comprehensive public WT exon array for transcriptomics studies. The Affymetrix GeneChip (R) Brassica Exon 1.0 ST Array is a 5 mu M feature size array, containing 2.4 million 25-base oligonucleotide probes representing 135,201 gene models, with 15 probes per gene distributed among exons. Discrimination of the gene models was based on an E-value cut-off of 1E(-5), with <= 98 sequence identity. The 135 k Brassica Exon Array was validated by quantifying transcriptome differences between leaf and root tissue from a reference Brassica rapa line (R-o-18), and categorisation by Gene Ontologies (GO) based on gene orthology with Arabidopsis thaliana. Technical validation involved comparison of the exon array with a 60-mer array platform using the same starting RNA samples. The 135 k Brassica Exon Array is a robust platform. All data relating to the array design and probe identities are available in the public domain and are curated within the BrassEnsembl genome viewer at http://www.brassica.info/BrassEnsembl/index.html.
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Background: Podosphaera aphanis, the causal agent of strawberry powdery mildew causes significant economic loss worldwide. Methods: We used the diploid strawberry species Fragaria vesca as a model to study plant pathogen interactions. RNA-seq was employed to generate a transcriptome dataset from two accessions, F. vesca ssp. vesca Hawaii 4 (HW) and F. vesca f. semperflorens Yellow Wonder 5AF7 (YW) at 1 d (1 DAI) and 8 d (8 DAI) after infection. Results: Of the total reads identified about 999 million (92%) mapped to the F. vesca genome. These transcripts were derived from a total of 23,470 and 23,464 genes in HW and YW, respectively from the three time points (control, 1 and 8 DAI). Analysis identified 1,567, 1,846 and 1,145 up-regulated genes between control and 1 DAI, control and 8 DAI, and 1 and 8 DAI, respectively in HW. Similarly, 1,336, 1,619 and 968 genes were up-regulated in YW. Also 646, 1,098 and 624 down-regulated genes were identified in HW, while 571, 754 and 627 genes were down-regulated in YW between all three time points, respectively. Conclusion: Investigation of differentially expressed genes (log2 fold changes �5) between control and 1 DAI in both HW and YW identified a large number of genes related to secondary metabolism, signal transduction; transcriptional regulation and disease resistance were highly expressed. These included flavonoid 3´-monooxygenase, peroxidase 15, glucan endo-1,3-β-glucosidase 2, receptor-like kinases, transcription factors, germin-like proteins, F-box proteins, NB-ARC and NBS-LRR proteins. This is the first application of RNA-seq to any pathogen interaction in strawberry
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A joint transcriptomic and proteomic approach employing two-dimensional electrophoresis, liquid chromatography and mass spectrometry was carried out to identify peptides and proteins expressed by the venom gland of the snake Bothrops insularis, an endemic species of Queimada Grande Island, Brazil. Four protein families were mainly represented in processed spots, namely metalloproteinase, serine proteinase, phospholipase A(2) and lectin. Other represented families were growth factors, the developmental protein G10, a disintegrin and putative novel bradykinin-potentiating peptides. The enzymes were present in several isoforms. Most of the experimental data agreed with predicted values for isoelectric point and M(r) of proteins found in the transcriptome of the venom gland. The results also support the existence of posttranslational modifications and of proteolytic processing of precursor molecules which could lead to diverse multifunctional proteins. This study provides a preliminary reference map for proteins and peptides present in Bothrops insularis whole venom establishing the basis for comparative studies of other venom proteomes which could help the search for new drugs and the improvement of venom therapeutics. Altogether, our data point to the influence of transcriptional and post-translational events on the final venom composition and stress the need for a multivariate approach to snake venomics studies. (c) 2009 Elsevier B.V. All rights reserved.
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As plataformas de sequenciamento de nova geração são uma alternativa poderosa para estudos de genômica estrutural e funcional. Na genômica de plantas, os trabalhos com as novas plataformas têm sido destinados ao sequenciamento de transcritos, ressequenciamento ou sequenciamento de novo de genomas plastidiais. Neste trabalho, são detalhadas as tecnologias das plataformas mais utilizadas atualmente, bem como é revisada a aplicação dessas tecnologias na genômica estrutural e funcional de plantas.
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Background: Uterine Leiomyomas (ULs) are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs). Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs. Methodology: We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC) and gene expression microarrays (SAM). The CONEXIC algorithm was applied to integrate the data. Principal Findings: The integrated analysis identified the top 30 significant genes (P<0.01), which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively) and IGFBP5 (P = 0.0002 and P = 0.006, respectively) were up-regulated in the tumours when compared with the adjacent normal myometrium. Conclusions: The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs. © 2013 Cirilo et al.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)