Community-Level Responses to Iron Availability in Open Ocean Plankton Ecosystems

Predicting responses of plankton to variations in essential nutrients is hampered by limited in situ measurements, a poor understanding of community composition, and the lack of reference gene catalogs for key taxa. Iron is a key driver of plankton dynamics and, therefore, of global biogeochemical cycles and climate. To assess the impact of iron availability on plankton communities, we explored the comprehensive bio-oceanographic and bio-omics data sets from Tara Oceans in the context of the iron products from two state-of-the-art global scale biogeochemical models. We obtained novel information about adaptation and acclimation toward iron in a range of phytoplankton, including picocyanobacteria and diatoms, and identified whole subcommunities covarying with iron. Many of the observed global patterns were recapitulated in the Marquesas archipelago, where frequent plankton blooms are believed to be caused by natural iron fertilization, although they are not captured in large-scale biogeochemical models. This work provides a proof of concept that integrative analyses, spanning from genes to ecosystems and viruses to zooplankton, can disentangle the complexity of plankton communities and can lead to more accurate formulations of resource bioavailability in biogeochemical models, thus improving our understanding of plankton resilience in a changing environment

Analysis and integration of genomic data for the study of transcription and regulation networks in the hematopoietic system

Un des défis fondamentaux de la biologie moderne est une meilleure compréhension des mécanismes de régulation de l'expression des gènes, dont dépendent notamment le fonctionnement et la différentiation des cellules. En outre, leurs dérèglements peuvent être à l'origine de pathologies comme par exemple les cancers. Les technologies haut-débit de l'ère post-génomique permettent la production massive de données concernant notamment l'expression des gènes, les sites de fixation des facteurs de transcription et l'état de la chromatine. Ces données sont une mine d'informations pour l'étude des mécanismes de régulation. Cependant, la quantité et l'hétérogénéité de ces données soulèvent de nombreuses problématiques bioinformatiques liées à l'accès, la visualisation, l'analyse et l'intégration de celles-ci.Cette thèse aborde un certain nombre de ces aspects, à travers plusieurs projets :- la caractérisation bioinformatique de transcrits anti-sens produits par des promoteurs bidirectionnels durant le développement thymocytaire- le développement et l'intégration d'un compendium d'interactions géniques de natures diverses (interactions physiques, régulations, etc), ainsi qu'un outil de visualisation de graphes adapté - l'étude d'un système de transdifférentiation de lymphocytes pre-B en macrophages par induction de CEBPa, et la construction d'un modèle de régulation, grâce à l'analyse intégrée de données de puces à ADN, de ChIP-seq et de séquenceOne of the fundamental challenges of modern biology is to better understand the mechanisms regulating gene expression, on which the functioning and differentiation of cells depend. In particular, disorders in these mechanisms may be the cause of diseases such as cancer. High throughput technologies of the post-genomic era allow mass production of data including gene expression, binding sites of transcription factors and chromatin state. These data a wealth of information for the study of regulatory mechanisms. However, the amount and heterogeneity of these data raise many bioinformatics issues related to access, visualization, analysis and integration of these.This thesis addresses a number of these aspects, through several projects:- bioinformatics characterization of antisense transcripts produced by bidirectional promoters during thymocyte development,- development and integration of a compendium of gene interactions of various kinds (physical interactions, regulations, etc.), and a graph visualization tool,- the study of a transdifferentiation system of pre-B lymphocytes into macrophages by induction of CEBPa, and the construction of a regulation model, thanks to the integrated analysis of DNA microarrays, ChIP-seq and sequence data.This work provides an illustration of some of the bioinformatics issues related to the exploitation of these data and methodologies to efficiently extract biological information, particularly to answer questions regarding the mechanisms of transcription and its regulation in the hematopoietic system

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

Sperm mRNAs and microRNAs as candidate markers for the impact of toxicants on human spermatogenesis: an application to tobacco smoking

International audienceSpermatozoa contain a complex population of RNAs including messenger RNAs (mRNAs) and small RNAs such as microRNAs (miRNA). It has been reported that these RNAs can be used to understand the mechanisms by which toxicological exposure affects spermatogenesis. The aim of our study was to compare mRNA and miRNA profiles in spermatozoa from eight smokers and eight non-smokers, and search for potential relationships between mRNA and miRNA variation. All men were selected based on their answers to a standard toxic exposure questionnaire, and sperm parameters. Using mRNA and miRNA microarrays, we showed that mRNAs from 15 genes were differentially represented between smokers and non-smokers (p \textless 0.01): five had higher levels and 10 lower levels in the smokers. For the microRNAs, 23 were differentially represented: 16 were higher and seven lower in the smokers (0.004 \textless= p \textless 0.01). Quantitative RT-PCR confirmed the lower levels in smokers compared to non-smokers for hsa-miR-296-5p, hsa-miR-3940, and hsa-miR-520d-3p. Moreover, we observed an inverse relationship between the levels of microRNAs and six potential target mRNAs (B3GAT3, HNRNPL, OASL, ODZ3, CNGB1, and PKD2). Our results indicate that alterations in the level of a small number of microRNAs in response to smoking may contribute to changes in mRNA expression in smokers. We conclude that large-scale analysis of spermatozoa RNAs can be used to help understand the mechanisms by which human spermatogenesis responds to toxic substances including those in tobacco smoke

C/EBPα Activates Pre-existing and De Novo Macrophage Enhancers during Induced Pre-B Cell Transdifferentiation and Myelopoiesis

Summary Transcription-factor-induced somatic cell conversions are highly relevant for both basic and clinical research yet their mechanism is not fully understood and it is unclear whether they reflect normal differentiation processes. Here we show that during pre-B-cell-to-macrophage transdifferentiation, C/EBPα binds to two types of myeloid enhancers in B cells: pre-existing enhancers that are bound by PU.1, providing a platform for incoming C/EBPα; and de novo enhancers that are targeted by C/EBPα, acting as a pioneer factor for subsequent binding by PU.1. The order of factor binding dictates the upregulation kinetics of nearby genes. Pre-existing enhancers are broadly active throughout the hematopoietic lineage tree, including B cells. In contrast, de novo enhancers are silent in most cell types except in myeloid cells where they become activated by C/EBP factors. Our data suggest that C/EBPα recapitulates physiological developmental processes by short-circuiting two macrophage enhancer pathways in pre-B cells

C/EBPalpha activates pre-existing and de novo macrophage enhancers during induced pre-B cell transdifferentiation and myelopoiesis

Transcription-factor-induced somatic cell conversions are highly relevant for both basic and clinical research yet their mechanism is not fully understood and it is unclear whether they reflect normal differentiation processes. Here we show that during pre-B-cell-to-macrophage transdifferentiation, C/EBPα binds to two types of myeloid enhancers in B cells: pre-existing enhancers that are bound by PU.1, providing a platform for incoming C/EBPα; and de novo enhancers that are targeted by C/EBPα, acting as a pioneer factor for subsequent binding by PU.1. The order of factor binding dictates the upregulation kinetics of nearby genes. Pre-existing enhancers are broadly active throughout the hematopoietic lineage tree, including B cells. In contrast, de novo enhancers are silent in most cell types except in myeloid cells where they become activated by C/EBP factors. Our data suggest that C/EBPα recapitulates physiological developmental processes by short-circuiting two macrophage enhancer pathways in pre-B cells.This work was supported by the Ministerio de Educacion y Ciencia, SAF.2012- 37167, AGAUR 2009 SGR768, EU-FP7 project BLUEPRINT (282510), and Fundacio la Marato TV3. C.B. was funded by a program grant (LLR 7001) from Leukemia Lymphoma Research UK

Divergent transcription is associated with promoters of transcriptional regulators.

International audienceBACKGROUND: Divergent transcription is a wide-spread phenomenon in mammals. For instance, short bidirectional transcripts are a hallmark of active promoters, while longer transcripts can be detected antisense from active genes in conditions where the RNA degradation machinery is inhibited. Moreover, many described long non-coding RNAs (lncRNAs) are transcribed antisense from coding gene promoters. However, the general significance of divergent lncRNA/mRNA gene pair transcription is still poorly understood. Here, we used strand-specific RNA-seq with high sequencing depth to thoroughly identify antisense transcripts from coding gene promoters in primary mouse tissues. RESULTS: We found that a substantial fraction of coding-gene promoters sustain divergent transcription of long non-coding RNA (lncRNA)/mRNA gene pairs. Strikingly, upstream antisense transcription is significantly associated with genes related to transcriptional regulation and development. Their promoters share several characteristics with those of transcriptional developmental genes, including very large CpG islands, high degree of conservation and epigenetic regulation in ES cells. In-depth analysis revealed a unique GC skew profile at these promoter regions, while the associated coding genes were found to have large first exons, two genomic features that might enforce bidirectional transcription. Finally, genes associated with antisense transcription harbor specific H3K79me2 epigenetic marking and RNA polymerase II enrichment profiles linked to an intensified rate of early transcriptional elongation. CONCLUSIONS: We concluded that promoters of a class of transcription regulators are characterized by a specialized transcriptional control mechanism, which is directly coupled to relaxed bidirectional transcription

Ocean plankton. Structure and function of the global ocean microbiome

Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.status: publishe

Structure and function of the global ocean microbiome

International audienceMicrobes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems