Phylogenetic Affiliation of SSU rRNA Genes Generated by Massively Parallel Sequencing: New Insights into the Freshwater Protist Diversity

International audienceRecent advances in next-generation sequencing (NGS) technologies spur progress in determining the microbial diversity in various ecosystems by highlighting, for example, the rare biosphere. Currently, high-throughput pyrotag sequencing of PCR-amplified SSU rRNA gene regions is mainly used to characterize bacterial and archaeal communities, and rarely to characterize protist communities. In addition, although taxonomic assessment through phylogeny is considered as the most robust approach, similarity and probabilistic approaches remain the most commonly used for taxonomic affiliation. In a first part of this work, a tree-based method was compared with different approaches of taxonomic affiliation (BLAST and RDP) of 18S rRNA gene sequences and was shown to be the most accurate for near full-length sequences and for 400 bp amplicons, with the exception of amplicons covering the V5-V6 region. Secondly, the applicability of this method was tested by running a full scale test using an original pyrosequencing dataset of 18S rRNA genes of small lacustrine protists (0.2-5 mm) from eight freshwater ecosystems. Our results revealed that i) fewer than 5% of the operational taxonomic units (OTUs) identified through clustering and phylogenetic affiliation had been previously detected in lakes, based on comparison to sequence in public databases; ii) the sequencing depth provided by the NGS coupled with a phylogenetic approach allowed to shed light on clades of freshwater protists rarely or never detected with classical molecular ecology approaches; and iii) phylogenetic methods are more robust in describing the structuring of under-studied or highly divergent populations. More precisely, new putative clades belonging to Mamiellophyceae, Foraminifera, Dictyochophyceae and Euglenida were detected. Beyond the study of protists, these results illustrate that the tree-based approach for NGS based diversity characterization allows an in-depth description of microbial communities including taxonomic profiling, community structuring and the description of clades of any microorganisms (protists, Bacteria and Archaea)

Positional cloning of a candidate gene for resistance to the sunflower downy mildew, Plasmopara halstedii race 300.

International audienceThe resistance of sunflower to Plasmopara halstedii is conferred by major resistance genes denoted Pl. Previous genetic studies indicated that the majority of these genes are clustered on linkage groups 8 and 13. The Pl6 locus is one of the main clusters to have been identified, and confers resistance to several P. halstedii races. In this study, a map-based cloning strategy was implemented using a large segregating F2 population to establish a fine physical map of this cluster. A marker derived from a bacterial artificial chromosome (BAC) clone was found to be very tightly linked to the gene conferring resistance to race 300, and the corresponding BAC clone was sequenced and annotated. It contains several putative genes including three toll-interleukin receptor-nucleotide binding site-leucine rich repeats (TIR-NBS-LRR) genes. However, only one TIR-NBS-LRR appeared to be expressed, and thus constitutes a candidate gene for resistance to P. halstedii race 300

Temporal Dynamics of Active Prokaryotic Nitrifiers and Archaeal Communities from River to Sea

International audienceTo test if different niches for potential nitrifiers exist in estuarine systems, we assessed by pyrosequencing the diversity of archaeal gene transcript markers for taxonomy (16S ribosomal RNA (rRNA)) during an entire year along a salinity gradient in surface waters of the Charente estuary (Atlantic coast, France). We further investigated the potential for estuarine prokaryotes to oxidize ammonia and hydrolyze urea by quantifying thaumarchaeal amoA and ureC and bacterial amoA transcripts. Our results showed a succession of different nitrifiers from river to sea with bacterial amoA transcripts dominating in the freshwater station while archaeal transcripts were predominant in the marine station. The 16S rRNA sequence analysis revealed that Thaumarchaeota marine group I (MGI) were the most abundant overall but other archaeal groups like Methanosaeta were also potentially active in winter (December–March) and Euryarchaeota marine group II (MGII) were dominant in seawater in summer (April–August). Each station also contained different Thaumarchaeota MGI phylogenetic clusters, and the clusters' microdiversity was associated to specific environmental conditions suggesting the presence of ecotypes adapted to distinct ecological niches. The amoA and ureC transcript dynamics further indicated that some of the Thaumarchaeota MGI sub-clusters were involved in ammonia oxidation through the hy-drolysis of urea. Our findings show that ammonia-oxidizing Archaea and Bacteria were adapted to contrasted conditions and that the Thaumarchaeota MGI diversity probably corresponds to distinct metabolisms or life strategies

Portage de ePANAM sur la grille de calcul

Portage de ePANAM sur la grille de calcu

Représentation des connaissances en cartographie comparée des génomes (le modèle de GeMCore)

La cartographie comparée nous permet d'étendre nos connaissances sur les génomes, en particulier des génomes d'organismes "modèles" vers les génomes d'espèces d'intérêt. Elle permet également de comparer des données génomiques sur la base de leur localisation et ainsi d'analyser les mécanismes évolutifs et fonctionnels à l'échelle des génomes. La démarche de la cartographie comparée en termes bioinformatiques est actuellement bridée par une modèlisation et des outils limités. Dans ce contexte, le système GeM (Genomic Mapping) développé au laboratoire constitue une approche nouvelle. GeM s'organise autour de la base de connaissances GeMCore pour la cartographie comparée, qui fait l'objet de cette thèse, associé à des interfaces graphiques dédiées à des domaines particuliers (médecine, agronomie, évolution). Le modèle de connaissance de GeMCore, de type objet-association, permet une description des objets de la cartographie comparée des génomes et de leurs relations. Ceux-ci sont décrits à travers trois classes principales : El'men, Map et Séquence. La modèlisation des positions relatives cartographiques est inspirée de l'algèbre de Allen. Une attention particulère a été portée à la représentation des relations évolutives, avec la distinction des relations d'homologie, d'orthologie et de paralogie. Ce modèle, implémenté avec le système de représentation des connaissances AROM, constitue la base de connaissances GeMCore. Celle-ci gère des données portant sur la nature des marqueurs, leur localisation cartographiques et leurs relations évolutives. Elle offre également un système de requêtes, utilisable par les interfaces de GeM. Les données intègrées dans GeMCore sont issues de la MGD, HUGO, LocusLink et Hovergen. L'apport de la représentation des connaissances au développement d'outils bioinformatiques pour la cartographie comparée des génomes et de manière plus générale pour l'explicitation des concepts de la biologie est discuté.LYON1-BU.Sciences (692662101) / SudocSudocFranceF

Cartographie génomique comparée chez les mammifères

La cartographie comparée est une analyse comparative de l’organisation chromosomique des génomes, qui repose sur l’exploitation de la biodiversité dans le double objectif de comprendre le fonctionnement des structures biologiques et d’en inférer l’évolution. La popularité actuelle de cette approche relève cependant d’une autre démarche, plus technique, qui résulte de la structure très particulière des connaissances actuelles sur les génomes. Le coût expérimental de l’analyse d’un génome restant très élevé, les informations disponibles sont le plus souvent concentrées sur quelques organismes « modèles » (principalement l’homme et la souris chez les mammifères). Déduire des informations sur des organismes d’intérêt, à partir de l’étude d’organismes modèles, est donc une démarche très précieuse, et la cartographie comparée entre dans ce cadre. Il faut également souligner que les comparaisons entre génomes peuvent être plus complexes et profiter des possibilités expérimentales offertes par certaines espèces. Ainsi, bien que l’homme soit l’un des organismes les mieux connus, la cartographie comparée est largement utilisée pour effectuer des allers-retours entre l’information génomique humaine et celle d’autres organismes dans lesquels l’observation, voire l’expérimentation génétique, est plus accessible

Comparison of 16S rRNA and protein-coding genes as molecular markers for assessing microbial diversity (Bacteria and Archaea) in ecosystems.

International audiencePCR amplification of the rRNA gene is the most popular method for assessing microbial diversity. However, this molecular marker is often present in multiple copies in cells presenting, in addition, an intragenomic heterogeneity. In this context, housekeeping genes may be used as taxonomic markers for ecological studies. However, the efficiency of these protein-coding genes compared to 16S rRNA genes has not been tested on environmental data. For this purpose, five protein marker genes for which primer sets are available, were selected (rplB, pyrG, fusA, leuS and rpoB) and compared with 16S rRNA gene results from PCR amplification or metagenomic data from aquatic ecosystems. Analysis of the major groups found in these ecosystems, such as Actinobacteria, Bacteroides, Proteobacteria and Cyanobacteria, showed good agreement between the protein markers and the results given by 16S rRNA genes from metagenomic reads. However, with the markers it was possible to detect minor groups among the microbial assemblages, providing more details compared to 16S rRNA results from PCR amplification. In addition, the use of a set of protein markers made it possible to deduce a mean copy number of rRNA operons. This average estimate is essentially lower than the one estimated in sequenced genomes