CD8+ T Cells from Human Neonates Are Biased toward an Innate Immune Response

To better understand why human neonates show a poor response to intracellular pathogens, we compared gene expression and histone modification profiles of neonatal naive CD8+ T cells with that of their adult counterparts. We found that neonatal lymphocytes have a distinct epigenomic landscape associated with a lower expression of genes involved in T cell receptor (TCR) signaling and cytotoxicity and a higher expression of genes involved in the cell cycle and innate immunity. Functional studies corroborated that neonatal CD8+ T cells are less cytotoxic, transcribe antimicrobial peptides, and produce reactive oxygen species. Altogether, our results show that neonatal CD8+ T cells have a specific genetic program biased toward the innate immune response. These findings will contribute to better diagnosis and management of the neonatal immune response.This project was specifically supported by a joint EcosNord-Anuies-SEP-Con-acyt project (M11S01). Work in the M.A.S. laboratory is supported by grantsfrom Consejo Nacional de Ciencia y Tecnologı ́a(CONACYT; CB-2011-01168182) and Programa de Mejoramiento del Profesorado (PROMEPSI-UAEM/13/342). Work in the S.S. laboratory is supported by recurrent fundingfrom the Inserm and Aix-Marseille University and by specific grants from theEuropean Union’s FP7 Program (agreement 282510-BLUEPRINT), the Associ-ation pour la Recherche contre le Cancer (ARC) (project SFI20111203756), andthe Aix-Marseille initiative d’excelence (A*MIDEX) project ANR-11-IDEX-0001-02. We thank Centro Estatal de la Transfusio ́n Sanguı ́nea in Cuernavaca for thedonation of leukocyte concentrates and the mothers and babies of HospitalGeneral Parres in Cuernavaca for the donation of cord blood. This study makesuse of data generated by the Blueprint and Roadmap consortia. A full list of theinvestigators who contributed to the generation of the data is availablefromwww.blueprint-epigenome.euandhttp://www.roadmapepigenomics.org/. Funding for the Blueprint project was provided by the European Union’sSeventh Framework Program (FP7/2007-2013) under grant agreement282510 – BLUEPRINT. The Roadmap consortium is financed by the NIH. Weare grateful to Professor C.I. Pogson for critical reading of the manuscript.S

TranscriptomeBrowser: A Powerful and Flexible Toolbox to Explore Productively the Transcriptional Landscape of the Gene Expression Omnibus Database

International audienceAs public microarray repositories are constantly growing, we are facing the challenge of designing strategies to provide productive access to the available data.\ We used a modified version of the Markov clustering algorithm to systematically extract clusters of co-regulated genes from hundreds of microarray datasets stored in the Gene Expression Omnibus database (n = 1,484). This approach led to the definition of 18,250 transcriptional signatures (TS) that were tested for functional enrichment using the DAVID knowledgebase. Over-representation of functional terms was found in a large proportion of these TS (84%). We developed a JAVA application, TBrowser that comes with an open plug-in architecture and whose interface implements a highly sophisticated search engine supporting several Boolean operators (http://tagc.univ-mrs.fr/tbrowser/). User can search and analyze TS containing a list of identifiers (gene symbols or AffyIDs) or associated with a set of functional terms.\ As proof of principle, TBrowser was used to define breast cancer cell specific genes and to detect chromosomal abnormalities in tumors. Finally, taking advantage of our large collection of transcriptional signatures, we constructed a comprehensive map that summarizes gene-gene co-regulations observed through all the experiments performed on HGU133A Affymetrix platform. We provide evidences that this map can extend our knowledge of cellular signaling pathways

Olfactory Stem Cells, a New Cellular Model for Studying Molecular Mechanisms Underlying Familial Dysautonomia

International audienceBackground: Familial dysautonomia (FD) is a hereditary neuropathy caused by mutations in the IKBKAP gene, the most common of which results in variable tissue-specific mRNA splicing with skipping of exon 20. Defective splicing is especially severe in nervous tissue, leading to incomplete development and progressive degeneration of sensory and autonomic neurons. The specificity of neuron loss in FD is poorly understood due to the lack of an appropriate model system. To better understand and modelize the molecular mechanisms of IKBKAP mRNA splicing, we collected human olfactory ecto-mesenchymal stem cells (hOE-MSC) from FD patients. hOE-MSCs have a pluripotent ability to differentiate into various cell lineages, including neurons and glial cells.Methodology/Principal Findings: We confirmed IKBKAP mRNA alternative splicing in FD hOE-MSCs and identified 2 novel spliced isoforms also present in control cells. We observed a significant lower expression of both IKBKAP transcript and IKAP/hELP1 protein in FD cells resulting from the degradation of the transcript isoform skipping exon 20. We localized IKAP/hELP1 in different cell compartments, including the nucleus, which supports multiple roles for that protein. We also investigated cellular pathways altered in FD, at the genome-wide level, and confirmed that cell migration and cytoskeleton reorganization were among the processes altered in FD. Indeed, FD hOE-MSCs exhibit impaired migration compared to control cells. Moreover, we showed that kinetin improved exon 20 inclusion and restores a normal level of IKAP/hELP1 in FD hOE-MSCs. Furthermore, we were able to modify the IKBKAP splicing ratio in FD hOE-MSCs, increasing or reducing the WT (exon 20 inclusion):MU (exon 20 skipping) ratio respectively, either by producing free-floating spheres, or by inducing cells into neural differentiation.Conclusions/Significance: hOE-MSCs isolated from FD patients represent a new approach for modeling FD to better understand genetic expression and possible therapeutic approaches. This model could also be applied to other neurological genetic diseases

Développement d'outils et méthodes bioinformatiques pour l'étude de l'expression des gènes et de leur régulation. : application aux pathologies

Understanding the mechanisms that control gene expression is a major challenge for medical research. This requires using a large set of pangenomic approaches such as those using DNA microarrays and high-throughput sequencing that generate an ever growing mass of digital data. During my thesis, I have developed several computer-based tools to facilitate their processing and analysis. I have created a R library (AgiND) that controls the quality of Agilent DNA microarray data and allows their statistical normalization. The growing number of experiences stored in Gene Expression Omnibus has motivated the development of the TBrowser project. An original method, DBF-MCL, was created to extract annotated transcriptional signatures by integrating various sources of information. Stored in a database, these signatures are accessible using a Java interface, a SOAP web service and a R/Bioconductor library (RTools4TB). Finally, a pipeline dedicated to the ChIP-seq analyses has been implemented. All these tools were used to study various diseases in collaborations.La compréhension des mécanismes qui contrôlent l'expression des gènes est un enjeu majeur pour la recherche médicale. Elle nécessite un ensemble d'approches pangénomiques telles que les puces à ADN et plus récemment le séquençage à très haut débit qui génèrent une masse toujours plus grande de données numériques à traiter. Au cours de ma thèse, j'ai développé plusieurs outils informatiques innovants pour faciliter leur exploitation. Ainsi, j'ai créé une librairie R (AgiND) qui vérifie la qualité des données de puces à ADN Agilent et permet de les normaliser. Le nombre croissant d'expériences stockées dans Gene Expression Omnibus a motivé la mise en place du projet TBrowser. Une méthode originale DBF-MCL a été créée pour extraire des signatures transcriptionnelles annotées par l'intégration de diverses sources d'information. Stockées dans une base de données, elles sont accessibles à travers une interface Java, un service web SOAP et une librairie R/Bioconductor (RTools4TB). Enfin, un pipeline d'analyse dédié au ChIP-seq a été implémenté. Tous ces outils ont servi pour l'étude de diverses maladies dans le cadre de collaborations

Développement d'outils et méthodes bioinformatiques pour l'étude de l'expression des gènes et de leur régulation. : application aux pathologies

Understanding the mechanisms that control gene expression is a major challenge for medical research. This requires using a large set of pangenomic approaches such as those using DNA microarrays and high-throughput sequencing that generate an ever growing mass of digital data. During my thesis, I have developed several computer-based tools to facilitate their processing and analysis. I have created a R library (AgiND) that controls the quality of Agilent DNA microarray data and allows their statistical normalization. The growing number of experiences stored in Gene Expression Omnibus has motivated the development of the TBrowser project. An original method, DBF-MCL, was created to extract annotated transcriptional signatures by integrating various sources of information. Stored in a database, these signatures are accessible using a Java interface, a SOAP web service and a R/Bioconductor library (RTools4TB). Finally, a pipeline dedicated to the ChIP-seq analyses has been implemented. All these tools were used to study various diseases in collaborations.La compréhension des mécanismes qui contrôlent l'expression des gènes est un enjeu majeur pour la recherche médicale. Elle nécessite un ensemble d'approches pangénomiques telles que les puces à ADN et plus récemment le séquençage à très haut débit qui génèrent une masse toujours plus grande de données numériques à traiter. Au cours de ma thèse, j'ai développé plusieurs outils informatiques innovants pour faciliter leur exploitation. Ainsi, j'ai créé une librairie R (AgiND) qui vérifie la qualité des données de puces à ADN Agilent et permet de les normaliser. Le nombre croissant d'expériences stockées dans Gene Expression Omnibus a motivé la mise en place du projet TBrowser. Une méthode originale DBF-MCL a été créée pour extraire des signatures transcriptionnelles annotées par l'intégration de diverses sources d'information. Stockées dans une base de données, elles sont accessibles à travers une interface Java, un service web SOAP et une librairie R/Bioconductor (RTools4TB). Enfin, un pipeline d'analyse dédié au ChIP-seq a été implémenté. Tous ces outils ont servi pour l'étude de diverses maladies dans le cadre de collaborations

ReMap 2022: a database of Human, Mouse, Drosophila and Arabidopsis regulatory regions from an integrative analysis of DNA-binding sequencing experiments

International audienceReMap (https://remap.univ-amu.fr) aims to provide manually curated, high-quality catalogs of regulatory regions resulting from a large-scale integrative analysis of DNA-binding experiments in Human, Mouse, Fly and Arabidopsis thaliana for hundreds of transcription factors and regulators. In this 2022 update, we have uniformly processed >11 000 DNA-binding sequencing datasets from public sources across four species. The updated Human regulatory atlas includes 8103 datasets covering a total of 1210 transcriptional regulators (TRs) with a catalog of 182 million (M) peaks, while the updated Arabidopsis atlas reaches 4.8M peaks, 423 TRs across 694 datasets. Also, this ReMap release is enriched by two new regulatory catalogs for Mus musculus and Drosophila melanogaster. First, the Mouse regulatory catalog consists of 123M peaks across 648 TRs as a result of the integration and validation of 5503 ChIP-seq datasets. Second, the Drosophila melanogaster catalog contains 16.6M peaks across 550 TRs from the integration of 1205 datasets. The four regulatory catalogs are browsable through track hubs at UCSC, Ensembl and NCBI genome browsers. Finally, ReMap 2022 comes with a new Cis Regulatory Module identification method, improved quality controls, faster search results, and better user experience with an interactive tour and video tutorials on browsing and filtering ReMap catalogs

TranscriptomeBrowser 3.0 : introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

International audienceBACKGROUND: Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. RESULTS: We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed InteractomeBrowser, a graph-based knowledge browser that comes as a plug-in for TranscriptomeBrowser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information and is a productive avenue in generating new hypotheses. The second objective of InteractomeBrowser is to fill the gap between interaction databases and dynamic modeling. It is thus compatible with the network analysis software Cytoscape and with the Gene Interaction Network simulation software (GINsim). We provide examples underlying the benefits of this visualization tool for large gene set analysis related to thymocyte differentiation. CONCLUSIONS: The InteractomeBrowser plugin is a powerful tool to get quick access to a knowledge database that includes both predicted and validated molecular interactions. InteractomeBrowser is available through the TranscriptomeBrowser framework and can be found at : http://tagc.univ-mrs.fr/tbrowser/. Our database is updated on a regular basis

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information and is a productive avenue in generating new hypotheses. The second objective of InteractomeBrowser is to fill the gap between interaction databases and dynamic modeling. It is thus compatible with the network analysis software Cytoscape and with the Gene Interaction Network simulation software (GINsim). We provide examples underlying the benefits of this visualization tool for large gene set analysis related to thymocyte differentiation. Conclusions The InteractomeBrowser plugin is a powerful tool to get quick access to a knowledge database that includes both predicted and validated molecular interactions. InteractomeBrowser is available through the TranscriptomeBrowser framework and can be found at: http://tagc.univ-mrs.fr/tbrowser/. Our database is updated on a regular basis.</p

Genome-wide analysis of familial dysautonomia and kinetin target genes with patient olfactory ecto-mesenchymal stem cells.

International audienceFamilial dysautonomia (FD) is a rare inherited neurodegenerative disorder. The most common mutation is a c.2204+6T>C transition in the 5' splice site (5'ss) of IKBKAP intron 20, which causes a tissue-specific skipping of exon 20, resulting in lower synthesis of IKAP/hELP1 protein. To better understand the specificity of neuron loss in FD, we modeled the molecular mechanisms of IKBKAP mRNA splicing by studying human olfactory ecto-mesenchymal stem cells (hOE-MSCs) derived from FD patient nasal biopsies. We explored how the modulation of IKBKAP mRNA alternative splicing impacts the transcriptome at the genome-wide level. We found that the FD transcriptional signature was highly associated with biological functions related to the development of the nervous system. In addition, we identified target genes of kinetin, a plant cytokinin that corrects IKBKAP mRNA splicing and increases the expression of IKAP/hELP1. We identified this compound as a putative regulator of splicing factors and added new evidence for a sequence-specific correction of splicing. In conclusion, hOE-MSCs isolated from FD patients represent a promising avenue for modeling the altered genetic expression of FD, demonstrating a methodology that can be applied to a host of other genetic disorders to test the therapeutic potential of candidate molecules

ReMap 2020: a database of regulatory regions from an integrative analysis of Human and Arabidopsis DNA-binding sequencing experiments

International audienceReMap (http://remap.univ-amu.fr) aims to provide the largest catalogs of high-quality regulatory regions resulting from a large-scale integrative analysis of hundreds of transcription factors and regulators from DNA-binding experiments in Human and Arabidopsis (Arabidopsis thaliana). In this 2020 update of ReMap we have collected, analyzed and retained after quality control 2764 new human ChIP-seq and 208 ChIP-exo datasets available from public sources. The updated human atlas totalize 5798 datasets covering a total of 1135 transcriptional regulators (TRs) with a catalog of 165 million (M) peaks. This ReMap update comes with two unique Arabidopsis regulatory catalogs. First, a catalog of 372 Arabidopsis TRs across 2.6M peaks as a result of the integration of 509 ChIP-seq and DAP-seq datasets. Second, a catalog of 33 hi-stone modifications and variants across 4.5M peaks from the integration of 286 ChIP-seq datasets. All catalogs are made available through track hubs at Ensembl and UCSC Genome Browsers. Additionally, this update comes with a new web framework providing an interactive user-interface, including improved search features. Finally, full programmatically access to the underlying data is available using a RESTful API together with a new R Shiny interface for a TRs binding enrichment analysis tool