78 research outputs found
Identitag, a relational database for SAGE tag identification and interspecies comparison of SAGE libraries
BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a method of large-scale gene expression analysis that has the potential to generate the full list of mRNAs present within a cell population at a given time and their frequency. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has to be improved in the analysis of SAGE libraries. Indeed, the existing web sites providing correspondence between tags and transcripts do not concern all species for which numerous EST and cDNA have already been sequenced. RESULTS: This is the reason why we designed and implemented a freely available tool called Identitag for tag identification that can be used in any species for which transcript sequences are available. Identitag is based on a relational database structure in order to allow rapid and easy storage and updating of data and, most importantly, in order to be able to precisely define identification parameters. This structure can be seen like three interconnected modules : the first one stores virtual tags extracted from a given list of transcript sequences, the second stores experimental tags observed in SAGE experiments, and the third allows the annotation of the transcript sequences used for virtual tag extraction. It therefore connects an observed tag to a virtual tag and to the sequence it comes from, and then to its functional annotation when available. Databases made from different species can be connected according to orthology relationship thus allowing the comparison of SAGE libraries between species. We successfully used Identitag to identify tags from our chicken SAGE libraries and for chicken to human SAGE tags interspecies comparison. Identitag sources are freely available on web site. CONCLUSIONS: Identitag is a flexible and powerful tool for tag identification in any single species and for interspecies comparison of SAGE libraries. It opens the way to comparative transcriptomic analysis, an emerging branch of biology
A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome
<p>Abstract</p> <p>Background</p> <p>"Open" transcriptome analysis methods allow to study gene expression without <it>a priori </it>knowledge of the transcript sequences. As of now, SAGE (Serial Analysis of Gene Expression), LongSAGE and MPSS (Massively Parallel Signature Sequencing) are the mostly used methods for "open" transcriptome analysis. Both LongSAGE and MPSS rely on the isolation of 21 pb tag sequences from each transcript. In contrast to LongSAGE, the high throughput sequencing method used in MPSS enables the rapid sequencing of very large libraries containing several millions of tags, allowing deep transcriptome analysis. However, a bias in the complexity of the transcriptome representation obtained by MPSS was recently uncovered.</p> <p>Results</p> <p>In order to make a deep analysis of mouse hypothalamus transcriptome avoiding the limitation introduced by MPSS, we combined LongSAGE with the Solexa sequencing technology and obtained a library of more than 11 millions of tags. We then compared it to a LongSAGE library of mouse hypothalamus sequenced with the Sanger method.</p> <p>Conclusion</p> <p>We found that Solexa sequencing technology combined with LongSAGE is perfectly suited for deep transcriptome analysis. In contrast to MPSS, it gives a complex representation of transcriptome as reliable as a LongSAGE library sequenced by the Sanger method.</p
Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays
Background: Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results: We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions: MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions
Transcription factor MITF and remodeller BRG1 define chromatin organisation at regulatory elements in melanoma cells
Microphthalmia-associated transcription factor (MITF) is the master regulator of the melanocyte lineage. To understand how MITF regulates transcription, we used tandem affinity purification and mass spectrometry to define a comprehensive MITF interactome identifying novel cofactors involved in transcription, DNA replication and repair, and chromatin organisation. We show that MITF interacts with a PBAF chromatin remodelling complex comprising BRG1 and CHD7. BRG1 is essential for melanoma cell proliferation in vitro and for normal melanocyte development in vivo. MITF and SOX10 actively recruit BRG1 to a set of MITF-associated regulatory elements (MAREs) at active enhancers. Combinations of MITF, SOX10, TFAP2A, and YY1 bind between two BRG1-occupied nucleosomes thus defining both a signature of transcription factors essential for the melanocyte lineage and a specific chromatin organisation of the regulatory elements they occupy. BRG1 also regulates the dynamics of MITF genomic occupancy. MITF-BRG1 interplay thus plays an essential role in transcription regulation in melanoma
Peroxisomal defects in microglial cells induce a disease-associated microglial signature
Microglial cells ensure essential roles in brain homeostasis. In pathological condition, microglia adopt a common signature, called disease-associated microglial (DAM) signature, characterized by the loss of homeostatic genes and the induction of disease-associated genes. In X-linked adrenoleukodystrophy (X-ALD), the most common peroxisomal disease, microglial defect has been shown to precede myelin degradation and may actively contribute to the neurodegenerative process. We previously established BV-2 microglial cell models bearing mutations in peroxisomal genes that recapitulate some of the hallmarks of the peroxisomal β-oxidation defects such as very long-chain fatty acid (VLCFA) accumulation. In these cell lines, we used RNA-sequencing and identified large-scale reprogramming for genes involved in lipid metabolism, immune response, cell signaling, lysosome and autophagy, as well as a DAM-like signature. We highlighted cholesterol accumulation in plasma membranes and observed autophagy patterns in the cell mutants. We confirmed the upregulation or downregulation at the protein level for a few selected genes that mostly corroborated our observations and clearly demonstrated increased expression and secretion of DAM proteins in the BV-2 mutant cells. In conclusion, the peroxisomal defects in microglial cells not only impact on VLCFA metabolism but also force microglial cells to adopt a pathological phenotype likely representing a key contributor to the pathogenesis of peroxisomal disorders
Immune response of BV-2 microglial cells is impacted by peroxisomal beta-oxidation
Microglia are crucial for brain homeostasis, and dysfunction of these cells is a key driver in most neurodegenerative diseases, including peroxisomal leukodystrophies. In X-linked adrenoleukodystrophy (X-ALD), a neuroinflammatory disorder, very long-chain fatty acid (VLCFA) accumulation due to impaired degradation within peroxisomes results in microglial defects, but the underlying mechanisms remain unclear. Using CRISPR/Cas9 gene editing of key genes in peroxisomal VLCFA breakdown (Abcd1, Abcd2, and Acox1), we recently established easily accessible microglial BV-2 cell models to study the impact of dysfunctional peroxisomal β-oxidation and revealed a disease-associated microglial-like signature in these cell lines. Transcriptomic analysis suggested consequences on the immune response. To clarify how impaired lipid degradation impacts the immune function of microglia, we here used RNA-sequencing and functional assays related to the immune response to compare wild-type and mutant BV-2 cell lines under basal conditions and upon pro-inflammatory lipopolysaccharide (LPS) activation. A majority of genes encoding proinflammatory cytokines, as well as genes involved in phagocytosis, antigen presentation, and co-stimulation of T lymphocytes, were found differentially overexpressed. The transcriptomic alterations were reflected by altered phagocytic capacity, inflammasome activation, increased release of inflammatory cytokines, including TNF, and upregulated response of T lymphocytes primed by mutant BV-2 cells presenting peptides. Together, the present study shows that peroxisomal β-oxidation defects resulting in lipid alterations, including VLCFA accumulation, directly reprogram the main cellular functions of microglia. The elucidation of this link between lipid metabolism and the immune response of microglia will help to better understand the pathogenesis of peroxisomal leukodystrophies
Extensive Regulation of Diurnal Transcription and Metabolism by Glucocorticoids.
Altered daily patterns of hormone action are suspected to contribute to metabolic disease. It is poorly understood how the adrenal glucocorticoid hormones contribute to the coordination of daily global patterns of transcription and metabolism. Here, we examined diurnal metabolite and transcriptome patterns in a zebrafish glucocorticoid deficiency model by RNA-Seq, NMR spectroscopy and liquid chromatography-based methods. We observed dysregulation of metabolic pathways including glutaminolysis, the citrate and urea cycles and glyoxylate detoxification. Constant, non-rhythmic glucocorticoid treatment rescued many of these changes, with some notable exceptions among the amino acid related pathways. Surprisingly, the non-rhythmic glucocorticoid treatment rescued almost half of the entire dysregulated diurnal transcriptome patterns. A combination of E-box and glucocorticoid response elements is enriched in the rescued genes. This simple enhancer element combination is sufficient to drive rhythmic circadian reporter gene expression under non-rhythmic glucocorticoid exposure, revealing a permissive function for the hormones in glucocorticoid-dependent circadian transcription. Our work highlights metabolic pathways potentially contributing to morbidity in patients with glucocorticoid deficiency, even under glucocorticoid replacement therapy. Moreover, we provide mechanistic insight into the interaction between the circadian clock and glucocorticoids in the transcriptional regulation of metabolism
Étude de l'autorenouvellement cellulaire par des approches de transcriptomique et de trancriptomique comparative
L'autorenouvellement et la différenciation sont essentiels pour le développement et l'homéostasie tissulaire chez l'ensemble des métazoaires et leur dérégulation est à l'origine de cancers. Nous nous sommes intéressés à ces processus en analysant le transcriptome de différentes populations de cellules en état d'autorenouvellement normal ou leucémogène. Pour cela, nous avons principalement utilisé des données issues de la technique SAGE (Serial Analysis of Gene Expression), qui permet d'échantillonner les ARNm en isolant à partir de chacun d'eux un court fragment appelé tag. Une étape clé dans l'analyse de ces données réside dans l'identification des tags, qui permet de retrouver de quels transcrits ils proviennent. Nous avons ainsi conçu et développé Identitag, qui permet l'identification des tags chez toutes les espèces pour lesquelles des données de transcrits sont disponibles. Ceci nous a permis d'analyser l'expression des gènes dans des cellules aviaires en état d'autorenouvellement, induites à se différencier ou présentant un phénotypique leucémique suite à la surexpression d un oncogène, v-erbA. Ces études nous ont permis de mettre en évidence des gènes potentiellement impliqués dans l'autorenouvellement normal et leucémogène. Pour étendre notre étude à d'autres espèces, nous avons conçu et développé une méthode permettant de réaliser des comparaisons interspécifiques de transcriptomes à partir de données SAGE. En comparant plus de 400 librairies SAGE humaines et murines publiques, nous avons observé une corrélation entre les profils d'expression de gènes tissu-spécifiques au sein de ces espèces, mais également des gènes ayant un profil d'expression espèce-spécifiqueSelf-renewal and differentiation are necessary for the development and maintenance of tissue homeostasis in all metazoan species and the deregulation of these processes can lead to the development of cancer. We studied the molecular mechanisms controlling these processes by analyzing the transcriptome of different normal and leukemic self-renewing cell populations. For this, we have mainly worked on data generated by the Serial Analysis of Gene Expression (SAGE) method, which allows to quantify mRNA present in a cell population. It is based on the isolation of short tag sequences from each transcript. An essential step in SAGE data analysis is tag identification, that is the unambiguous assignment of each tag to the transcript from which it was derived. Therefore, we developed a new tool called Identitag, that can be used for tag identification in any species for which transcript sequences are available. We used Identitag to compare gene expression in chicken self-renewing cells or in their progeny after the induction of differentiation. We then analyzed the consequences of transformation of the same cell type by the v-erbA oncogene. These studies allowed us to identify genes which can be important for self-renewal in normal and leukemic cells. In order to extend our analysis to other species, we designed a method which allows to compare transcriptomes between species, based on SAGE data. By using this method, we compared more than 400 publicly available human and mouse SAGE libraries. Despite the correlated patterns of tissue specific gene expression in different species we observed, we identified genes that showed species specific patterns of expressionLYON1-BU.Sciences (692662101) / SudocSudocFranceF
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