eL-DASionator: an LDAS upload file generator

BACKGROUND: The Distributed Annotation System (DAS) allows merging of DNA sequence annotations from multiple sources and provides a single annotation view. A straightforward way to establish a DAS annotation server is to use the "Lightweight DAS" server (LDAS). Onto this type of server, annotations can be uploaded as flat text files in a defined format. The popular Ensembl ContigView uses the same format for the transient upload and display of user data. RESULTS: In order to easily generate LDAS upload files we developed a software tool that is accessible via a web-interface . Users can submit their DNA sequences of interest. Our program (i) aligns these sequences to the reference sequences of Ensembl, (ii) determines start and end positions of each sequence on the reference sequence, and (iii) generates a formatted annotation file. This file can be used to load any LDAS annotation server or it can be uploaded to the Ensembl ContigView. CONCLUSION: The eL-DASionator is an on-line tool that is intended for life-science researchers with little bioinformatics background. It conveniently generates LDAS upload files, and makes it possible to generate annotations in a standard format that permits comfortable sharing of this data

InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid

International audiencePlant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users

A new molecular breast cancer subclass defined from a large scale real-time quantitative RT-PCR study

BACKGROUND: Current histo-pathological prognostic factors are not very helpful in predicting the clinical outcome of breast cancer due to the disease's heterogeneity. Molecular profiling using a large panel of genes could help to classify breast tumours and to define signatures which are predictive of their clinical behaviour. METHODS: To this aim, quantitative RT-PCR amplification was used to study the RNA expression levels of 47 genes in 199 primary breast tumours and 6 normal breast tissues. Genes were selected on the basis of their potential implication in hormonal sensitivity of breast tumours. Normalized RT-PCR data were analysed in an unsupervised manner by pairwise hierarchical clustering, and the statistical relevance of the defined subclasses was assessed by Chi2 analysis. The robustness of the selected subgroups was evaluated by classifying an external and independent set of tumours using these Chi2-defined molecular signatures. RESULTS: Hierarchical clustering of gene expression data allowed us to define a series of tumour subgroups that were either reminiscent of previously reported classifications, or represented putative new subtypes. The Chi2 analysis of these subgroups allowed us to define specific molecular signatures for some of them whose reliability was further demonstrated by using the validation data set. A new breast cancer subclass, called subgroup 7, that we defined in that way, was particularly interesting as it gathered tumours with specific bioclinical features including a low rate of recurrence during a 5 year follow-up. CONCLUSION: The analysis of the expression of 47 genes in 199 primary breast tumours allowed classifying them into a series of molecular subgroups. The subgroup 7, which has been highlighted by our study, was remarkable as it gathered tumours with specific bioclinical features including a low rate of recurrence. Although this finding should be confirmed by using a larger tumour cohort, it suggests that gene expression profiling using a minimal set of genes may allow the discovery of new subclasses of breast cancer that are characterized by specific molecular signatures and exhibit specific bioclinical features

Carnosine:can understanding its actions on energy metabolism and protein homeostasis inform its therapeutic potential?

The dipeptide carnosine (β-alanyl-L-histidine) has contrasting but beneficial effects on cellular activity. It delays cellular senescence and rejuvenates cultured senescent mammalian cells. However, it also inhibits the growth of cultured tumour cells. Based on studies in several organisms, we speculate that carnosine exerts these apparently opposing actions by affecting energy metabolism and/or protein homeostasis (proteostasis). Specific effects on energy metabolism include the dipeptide's influence on cellular ATP concentrations. Carnosine's ability to reduce the formation of altered proteins (typically adducts of methylglyoxal) and enhance proteolysis of aberrant polypeptides is indicative of its influence on proteostasis. Furthermore these dual actions might provide a rationale for the use of carnosine in the treatment or prevention of diverse age-related conditions where energy metabolism or proteostasis are compromised. These include cancer, Alzheimer's disease, Parkinson's disease and the complications of type-2 diabetes (nephropathy, cataracts, stroke and pain), which might all benefit from knowledge of carnosine's mode of action on human cells. © 2013 Hipkiss et al.; licensee Chemistry Central Ltd

Du phénotypage au Big Data

Avec l’émergence des nouvelles technologies d’acquisition de données, les solutions actuelles de stockage et d’interrogation vont très vite atteindre leurs limites. Les Catis (centres automatisés de traitement de l’information) Sicpa (systèmes d’informations et calcul pour le phénotypage animal) et Codex (connaissances et données expérimentales) s’intéressent donc aux différentes technologies autour du Big Data

Insecticide resistance through mutations in cholinesterases or carboxylesterases : data mining in the ESTHER database

Resistance of arthropods to organophosphates and carbamates used as insecticides is mainly due to mutations in genes encoding carboxylesterase or acetylcholinesterase members of the alpha/beta-hydrolase fold superfamily of proteins. Mutations that have been described at the molecular level concern 24 species, 31 genes and 32 identical positions in the aligned aminoacid sequences. Seven of these positions are found in more than four species and can be considered as hot spots for mutations. Mutations in one single gene also result in cross resistance to pyrethroids. These figures along with all pieces of information related to these mutations can be recovered from the ESTHER database, dedicated to the alpha/beta-hydrolase fold superfamily (http://bioweb.ensam.inra.fr/esther), through built-in or custom made queries. A sequence alignment of enzymes involved in resistance with highlighted mutated amino acid residues is provided. Selecting one amino acid residue leads to all information about mutations analyzed at this position. Links to the related literature are also available

ESTHER, the database of the α/β-hydrolase fold superfamily of proteins

The α/β-hydrolase fold is characterized by a β-sheet core of five to eight strands connected by α-helices to form a α/β/α sandwich. In most of the family members the β-strands are parallels, but some show an inversion in the order of the first strands, resulting in antiparallel orientation. The members of the superfamily diverged from a common ancestor into a number of hydrolytic enzymes with a wide range of substrate specificities, together with other proteins with no recognized catalytic activity. In the enzymes the catalytic triad residues are presented on loops, of which one, the nucleophile elbow, is the most conserved feature of the fold. Of the other proteins, which all lack from one to all of the catalytic residues, some may simply be ‘inactive’ enzymes while others are known to be involved in surface recognition functions. The ESTHER database (http://bioweb.ensam.inra.fr/esther) gathers and annotates all the published information related to gene and protein sequences of this superfamily, as well as biochemical, pharmacological and structural data, and connects them so as to provide the bases for studying structure–function relationships within the family. The most recent developments of the database, which include a section on human diseases related to members of the family, are described

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