Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System.

Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.

PHENOPSIS DB: an information system for Arabidopsis thaliana phenotypic data in an environmental context.

BACKGROUND: Renewed interest in plant×environment interactions has risen in the post-genomic era. In this context, high-throughput phenotyping platforms have been developed to create reproducible environmental scenarios in which the phenotypic responses of multiple genotypes can be analysed in a reproducible way. These platforms benefit hugely from the development of suitable databases for storage, sharing and analysis of the large amount of data collected. In the model plant Arabidopsis thaliana, most databases available to the scientific community contain data related to genetic and molecular biology and are characterised by an inadequacy in the description of plant developmental stages and experimental metadata such as environmental conditions. Our goal was to develop a comprehensive information system for sharing of the data collected in PHENOPSIS, an automated platform for Arabidopsis thaliana phenotyping, with the scientific community. DESCRIPTION: PHENOPSIS DB is a publicly available (URL: http://bioweb.supagro.inra.fr/phenopsis/) information system developed for storage, browsing and sharing of online data generated by the PHENOPSIS platform and offline data collected by experimenters and experimental metadata. It provides modules coupled to a Web interface for (i) the visualisation of environmental data of an experiment, (ii) the visualisation and statistical analysis of phenotypic data, and (iii) the analysis of Arabidopsis thaliana plant images. CONCLUSIONS: Firstly, data stored in the PHENOPSIS DB are of interest to the Arabidopsis thaliana community, particularly in allowing phenotypic meta-analyses directly linked to environmental conditions on which publications are still scarce. Secondly, data or image analysis modules can be downloaded from the Web interface for direct usage or as the basis for modifications according to new requirements. Finally, the structure of PHENOPSIS DB provides a useful template for the development of other similar databases related to genotype×environment interactions.

Genomic markers for ovarian cancer at chromosomes 1, 8 and 17 revealed by array CGH analysis.

AIMS AND BACKGROUND: The literature data show that the most frequently affected chromosomes in ovarian carcinogenesis are 1, 8 and 17. In the present study we aimed to define more precisely at a high resolution the genomic imbalances of these chromosomes in ovarian cancer and to determine genomic markers separating tumors of different histological types and stages. METHODS: Array comparative genomic hybridization (CGH) with a resolution of approximately 0.8 Mb was applied in 28 primary ovarian tumors. We identified regions of highly frequent gains or losses (affecting more than 40% of ovarian cancers) and determined sites showing alterations of elevated amplitude (amplifications or homozygous deletions). Doing this we also identified at least two adjacent changed clones. RESULTS: We determined anomalies strongly associated with the disease such as deletions at 8p21-23, 17p12-13, 1p35-36 or amplifications at 1q23, 17q12, 17q23.2, 8q13.2, 8q24. We defined more precisely the gains in 17q12-q24, finding as strong candidates for ovarian tumorigenesis the genes LASP1 (17q12), TGF11 (17q21.32), MUL (17q23.2), TBX2 (17q23.2), AXIN2 (17q24.3) and GRB2 (17q25.1). Of particular note was gain of 8q13.2, which occurred at a high frequency in ovarian cancer, especially in serous and late-stage tumors. We found that gains of 1q32-1q43, 8p11-p12, 8q11.23, 8q13.2, and 8q24.21-8q24.22 and losses of 1p36.21, 8p23.1-8p21.1 and 8q21.2 were associated with serous histology, whereas losses of 1q23 and 1q32-43 and gains of 17q11.2-12 and 17q25 were associated with mucinous histology. Gains of 1q23, 8q24, 17q23.2, 17q24.2 and losses of 1p35-36, 8p, 17p, and 17q were specific for late-stage ovarian cancers. CONCLUSIONS: Our study has identified potential genomic markers of interest on chromosomes 1, 8 and 17 in ovarian cancer. Tumors showed a wide variety in the patterns of alteration, suggesting that alternative mechanisms of genomic instability may play a role in this tumor type.

Identification of potential pharmacological targets by analysis of the comprehensive G protein-coupled receptor repertoire in the four cardiac chambers.

Cardiac function is regulated by many hormones and neurotransmitters that exert their physiological effects through the activation of G protein-coupled receptors (GPCRs). Identification of new GPCRs that might display a specific pattern of expression within the heart and differentially regulate specific cardiac functions represents an important issue for the development of new drugs. Indeed, highly targeted receptors represent only a small percentage of known GPCRs. Here, we quantified the expression of 395 endoGPCRs (all GPCRs excluding taste and odorant receptors) in male mouse right and left atria and ventricles by using high-throughput real-time reverse-transcriptase polymerase chain reaction (RT-PCR) and focused on the 135 most highly expressed transcripts. No cardiac functional data are available for almost half of these receptors; therefore, linking GPCR expression patterns to cardiac function has allowed us to provide new insights into the possible function of some of these receptors. Indeed, ventricles and atria are both contractile; however, the latter, and especially the right atrium, are central to the generation and regulation of cardiac rhythm. Accordingly, the right atrium exhibited the most specific signature, whereas the majority of GPCRs found in ventricles were evenly expressed in both the right and left chambers. RT-PCR data were confirmed at the protein level for six selected transcripts. Furthermore, we provide new data showing that, as suggested by our repertoire, the metabotropic glutamate receptor 1b is expressed and is functional in ventricular cardiac myocytes. This is the first report describing GPCRs in the four cardiac chambers and may assist in the identification of therapeutic targets.

A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer.

PURPOSE: The identification of a molecular signature predicting the relapse of tamoxifen-treated primary breast cancers should help the therapeutic management of estrogen receptor-positive cancers. EXPERIMENTAL DESIGN: A series of 132 primary tumors from patients who received adjuvant tamoxifen were analyzed for expression profiles at the whole-genome level by 70-mer oligonucleotide microarrays. A supervised analysis was done to identify an expression signature. RESULTS: We defined a 36-gene signature that correctly classified 78% of patients with relapse and 80% of relapse-free patients (79% accuracy). Using 23 independent tumors, we confirmed the accuracy of the signature (78%) whose relevance was further shown by using published microarray data from 60 tamoxifen-treated patients (63% accuracy). Univariate analysis using the validation set of 83 tumors showed that the 36-gene classifier is more efficient in predicting disease-free survival than the traditional histopathologic prognostic factors and is as effective as the Nottingham Prognostic Index or the "Adjuvant!" software. Multivariate analysis showed that the molecular signature is the only independent prognostic factor. A comparison with several already published signatures demonstrated that the 36-gene signature is among the best to classify tumors from both training and validation sets. Kaplan-Meier analyses emphasized its prognostic power both on the whole cohort of patients and on a subgroup with an intermediate risk of recurrence as defined by the St. Gallen criteria. CONCLUSION: This study identifies a molecular signature specifying a subgroup of patients who do not gain benefits from tamoxifen treatment. These patients may therefore be eligible for alternative endocrine therapies and/or chemotherapy.

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.

SPODOBASE: an EST database for the lepidopteran crop pest Spodoptera.

BACKGROUND: The Lepidoptera Spodoptera frugiperda is a pest which causes widespread economic damage on a variety of crop plants. It is also well known through its famous Sf9 cell line which is used for numerous heterologous protein productions. Species of the Spodoptera genus are used as model for pesticide resistance and to study virus host interactions. A genomic approach is now a critical step for further new developments in biology and pathology of these insects, and the results of ESTs sequencing efforts need to be structured into databases providing an integrated set of tools and informations. DESCRIPTION: The ESTs from five independent cDNA libraries, prepared from three different S. frugiperda tissues (hemocytes, midgut and fat body) and from the Sf9 cell line, are deposited in the database. These tissues were chosen because of their importance in biological processes such as immune response, development and plant/insect interaction. So far, the SPODOBASE contains 29,325 ESTs, which are cleaned and clustered into non-redundant sets (2294 clusters and 6103 singletons). The SPODOBASE is constructed in such a way that other ESTs from S. frugiperda or other species may be added. User can retrieve information using text searches, pre-formatted queries, query assistant or blast searches. Annotation is provided against NCBI, UNIPROT or Bombyx mori ESTs databases, and with GO-Slim vocabulary. CONCLUSION: The SPODOBASE database provides integrated access to expressed sequence tags (EST) from the lepidopteran insect Spodoptera frugiperda. It is a publicly available structured database with insect pest sequences which will allow identification of a number of genes and comprehensive cloning of gene families of interest for scientific community. SPODOBASE is available from URL: http://bioweb.ensam.inra.fr/spodobase.

The MethDB DAS server: adding an epigenetic information layer to the human genome.

The DNA methylation database MethDB (www.methdb.net) was developed in order to standardize and collect the dispersed data about this epigenetic phenomenon in a common resource. In the first version of MethDB, data was gathered by annotators and the database could only be queried. In a second step, we added an on-line data submission system that is open to the public. Here we present the DAS annotation server of MethDB that allows integration of MethDB into the network of biological databases via the Distributed Annotation System (DAS) and the representation of DNA methylation data as an epigenetic information layer to the human genome. In order to validate our system and to incorporate the data of the first large scale methylation analysis of the human genome, we assembled the 31312 sequences of the human CpG island tagging project into 13786 CpG islands and imported them into MethDB. The database contains now 19905 methylation content data and 5382 methylation patterns or profiles for 48 species, 1511 individuals, 198 tissues and cell lines and 79 phenotypes.

New friendly tools for users of ESTHER, the database of the alpha/beta-hydrolase fold superfamily of proteins.

The structural alpha/beta-hydrolase fold is characterized by a beta-sheet core of five to eight strands connected by alpha-helices to form a alpha/beta/alpha sandwich. The superfamily members, exemplified by the cholinesterases, diverged from a common ancestor into a number of hydrolytic enzymes displaying a wide range of substrate specificities, along with proteins with no recognized hydrolytic 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 have been shown to be involved in heterologous surface recognition functions. The ESTHER (for esterases, alpha/beta-hydrolase enzymes and relatives) database (http://bioweb.ensam.inra.fr.esther) gathers and annotates all the published pieces of information (gene and protein sequences; biochemical, pharmacological, and structural data) related to the superfamily, and connects them together to provide the bases for studying structure-function relationships within the superfamily. The most recent developments of the database are presented.

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 http://atgc.lirmm.fr/eldasionator.html. 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.

ESTHER, the database of the alpha/beta-hydrolase fold superfamily of proteins.

The alpha/beta-hydrolase fold is characterized by a beta-sheet core of five to eight strands connected by alpha-helices to form a alpha/beta/alpha sandwich. In most of the family members the beta-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.

Negative regulation of transcription by the type II arginine methyltransferase PRMT5.

We have identified previously a repressor element in the transcription start site region of the cyclin E1 promoter that periodically associates with an atypical, high molecular weight E2F complex, termed CERC. Purification of native CERC reveals the presence of the type II arginine methyltransferase PRMT5, which can mono- or symetrically dimethylate arginine residues in proteins. Chromatin immunoprecipitations (ChIPs) show that PRMT5 is associated specifically with the transcription start site region of the cyclin E1 promoter. ChIP analyses also show that this correlates with the presence on the same promoter region of arginine-methylated proteins including histone H4, an in vitro substrate of PRMT5. Consistent with its presence within the repressor complex, forced expression of PRMT5 negatively affects cyclin E1 promoter activity and cellular proliferation, effects that require its methyltransferase activity. These data provide the first direct experimental evidence that a type II arginine methylase is involved in the control of transcription and proliferation.