28 research outputs found

    TOGGLe, a flexible framework for easily building complex workflows and performing robust large-scale NGS analyses

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    ABSTRACTThe advent of NGS has intensified the need for robust pipelines to perform high-performance automated analyses. The required softwares depend on the sequencing method used to produce raw data (e.g. Whole genome sequencing, Genotyping By Sequencing, RNASeq) as well as the kind of analyses to carry on (GWAS, population structure, differential expression). These tools have to be generic and scalable, and should meet the biologists needs.Here, we present the new version of TOGGLe (Toolbox for Generic NGS Analyses), a simple and highly flexible framework to easily and quickly generate pipelines for large-scale second- and third-generation sequencing analyses, including multi-sample and multi-threading support. TOGGLe is a workflow manager designed to be as effortless as possible to use for biologists, so the focus can remain on the analyses. Pipelines are easily customizable and supported analyses are reproducible and shareable. TOGGLe is designed as a generic, adaptable and fast evolutive solution, and has been tested and used in large-scale projects on various organisms. It is freely available at http://toggle.southgreen.fr/, under the GNU GPLv3/CeCill-C licenses) and can be deployed onto HPC clusters as well as on local machines

    The Conserved Candida albicans CA3427 Gene Product Defines a New Family of Proteins Exhibiting the Generic Periplasmic Binding Protein Structural Fold

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    Nosocomial diseases due to Candida albicans infections are in constant rise in hospitals, where they cause serious complications to already fragile intensive care patients. Antifungal drug resistance is fast becoming a serious issue due to the emergence of strains resistant to currently available antifungal agents. Thus the urgency to identify new potential protein targets, the function and structure of which may guide the development of new antifungal drugs. In this context, we initiated a comparative genomics study in search of promising protein coding genes among the most conserved ones in reference fungal genomes. The CA3427 gene was selected on the basis of its presence among pathogenic fungi contrasting with its absence in the non pathogenic Saccharomyces cerevisiae. We report the crystal 3D-structure of the Candida albicans CA3427 protein at 2.1 Å resolution. The combined analysis of its sequence and structure reveals a structural fold originally associated with periplasmic binding proteins. The CA3427 structure highlights a binding site located between the two protein domains, corresponding to a sequence segment conserved among fungi. Two crystal forms of CA3427 were found, suggesting that the presence or absence of a ligand at the proposed binding site might trigger a “Venus flytrap” motion, coupled to the previously described activity of bacterial periplasmic binding proteins. The conserved binding site defines a new subfamily of periplasmic binding proteins also found in many bacteria of the bacteroidetes division, in a choanoflagellate (a free-living unicellular and colonial flagellate eukaryote) and in a placozoan (the closest multicellular relative of animals). A phylogenetic analysis suggests that this gene family originated in bacteria before its horizontal transfer to an ancestral eukaryote prior to the radiation of fungi. It was then lost by the Saccharomycetales which include Saccharomyces cerevisiae

    South Green bioinformatics platform : Plateforme collaborative de bioinformatique verte héraultaise

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    Drivers and other road users often encounter situations where priority is unclear or ambiguous, but must be resolved, for example, after arriving at an intersection nearly simultaneously. The participants in such scenarios reach agreement by communicating; while instinctive to humans, this is a significant challenge for autonomous vehicles. Currently, the nature of interaction for resolving ambiguous road situations between pedestrians and autonomous vehicles remains mostly in the realm of speculation, for which no direct means for expressing intent and acknowledgment has yet been established. This thesis approaches the challenge by contributing a model and approach for planning that can produce actions that are expressive and encode certain aspects of intent; the result is communicative in that vehicle-pedestrian coordination arises via a negotiation of intent in a prototypical unsignalized intersection crossing scenario. We deliberately construct a prototypical crossing setting with a vehicle and one pedestrian at an unsignalized intersection such that there is substantial ambiguity in crossing order. A decision-theoretic model is then used for capturing this scenario along with its ambiguity as uncertainty arising from non-determinism and partial observability. We solve the problem by first proposing a Markov decision process to express the interaction at the intersection. Next, we focus on the partial-observability and include it in the model to generate a sequence of vehicle actions by solving via a state-of-the-art online solver. We implement the approach on a self-driving Ford Lincoln MKZ platform and examine an experimental setting involving real-time interaction. The experiment shows that the method achieves safe and efficient navigation. We analyze the resulting policy in detail in simulation and examine the coupled behavior of the vehicle and pedestrian, interpreting evidence for implicit communication that emerges as the two resolve ambiguity to achieve safe and efficient navigation

    The venom composition of the parasitic wasp Chelonus inanitus resolved by combined expressed sequence tags analysis and proteomic approach

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    <p>Abstract</p> <p>Background</p> <p>Parasitic wasps constitute one of the largest group of venomous animals. Although some physiological effects of their venoms are well documented, relatively little is known at the molecular level on the protein composition of these secretions. To identify the majority of the venom proteins of the endoparasitoid wasp <it>Chelonus inanitus </it>(Hymenoptera: Braconidae), we have randomly sequenced 2111 expressed sequence tags (ESTs) from a cDNA library of venom gland. In parallel, proteins from pure venom were separated by gel electrophoresis and individually submitted to a nano-LC-MS/MS analysis allowing comparison of peptides and ESTs sequences.</p> <p>Results</p> <p>About 60% of sequenced ESTs encoded proteins whose presence in venom was attested by mass spectrometry. Most of the remaining ESTs corresponded to gene products likely involved in the transcriptional and translational machinery of venom gland cells. In addition, a small number of transcripts were found to encode proteins that share sequence similarity with well-known venom constituents of social hymenopteran species, such as hyaluronidase-like proteins and an Allergen-5 protein.</p> <p>An overall number of 29 venom proteins could be identified through the combination of ESTs sequencing and proteomic analyses. The most highly redundant set of ESTs encoded a protein that shared sequence similarity with a venom protein of unknown function potentially specific of the <it>Chelonus </it>lineage. Venom components specific to <it>C. inanitus </it>included a C-type lectin domain containing protein, a chemosensory protein-like protein, a protein related to yellow-e3 and ten new proteins which shared no significant sequence similarity with known sequences. In addition, several venom proteins potentially able to interact with chitin were also identified including a chitinase, an imaginal disc growth factor-like protein and two putative mucin-like peritrophins.</p> <p>Conclusions</p> <p>The use of the combined approaches has allowed to discriminate between cellular and truly venom proteins. The venom of <it>C. inanitus </it>appears as a mixture of conserved venom components and of potentially lineage-specific proteins. These new molecular data enrich our knowledge on parasitoid venoms and more generally, might contribute to a better understanding of the evolution and functional diversity of venom proteins within Hymenoptera.</p
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