Very fast identification of RNA motifs in genomic DNA. Application to tRNA search in the yeast genome.

A common strategy characterises the various methods independently defined to identify almost unambiguously different types of RNA molecules in DNA fragments. So far, the good quality of detection of RNA motif has been the prior motivation and effectively delayed the optimisation of programs. As an illustration of possible improvements, a modified version of tRNAscan is described. The previous algorithm was altered to run 500 times faster and to lower both rates of false positives and false negatives. The newly sequenced genome of Saccharomyces cerevisiae is scanned both ways in less than three minutes and results match annotations found in databanks with three exceptions, two of which being arguably not real tRNAs.

Automatic identification of group I intron cores in genomic DNA sequences.

Automatic identification of the ribozyme core of group I catalytic introns in genomic sequences is shown to be feasible in spite of the scarcity of strictly conserved features in the sequence and secondary structure of group I introns. An algorithm is described that successfully identified 132 out of the 143 currently reported group I cores with a false positive rate of only 10(-6) per nucleotide. The recognition process consists in generating and rating large sets of potential local solutions which are gradually combined into more complex structures until an entire core (six to seven pairings, six connecting segments, three terminal loops) has been assembled. The extent to which successful recognition may be prevented by sequencing errors is assessed. Also discussed are (1) possible relationships between scores allocated by the program and ability to self-splice in vitro and (2) the potential for objectively assessing the degree of relatedness to group I of structures claimed to resemble group I introns.

Animal board invited review: advances in proteomics for animal and food sciences.

Animal production and health (APH) is an important sector in the world economy, representing a large proportion of the budget of all member states in the European Union and in other continents. APH is a highly competitive sector with a strong emphasis on innovation and, albeit with country to country variations, on scientific research. Proteomics (the study of all proteins present in a given tissue or fluid - i.e. the proteome) has an enormous potential when applied to APH. Nevertheless, for a variety of reasons and in contrast to disciplines such as plant sciences or human biomedicine, such potential is only now being tapped. To counter such limited usage, 6 years ago we created a consortium dedicated to the applications of Proteomics to APH, specifically in the form of a Cooperation in Science and Technology (COST) Action, termed FA1002--Proteomics in Farm Animals: www.cost-faproteomics.org. In 4 years, the consortium quickly enlarged to a total of 31 countries in Europe, as well as Israel, Argentina, Australia and New Zealand. This article has a triple purpose. First, we aim to provide clear examples on the applications and benefits of the use of proteomics in all aspects related to APH. Second, we provide insights and possibilities on the new trends and objectives for APH proteomics applications and technologies for the years to come. Finally, we provide an overview and balance of the major activities and accomplishments of the COST Action on Farm Animal Proteomics. These include activities such as the organization of seminars, workshops and major scientific conferences, organization of summer schools, financing Short-Term Scientific Missions (STSMs) and the generation of scientific literature. Overall, the Action has attained all of the proposed objectives and has made considerable difference by putting proteomics on the global map for animal and veterinary researchers in general and by contributing significantly to reduce the East-West and North-South gaps existing in the European farm animal research. Future activities of significance in the field of scientific research, involving members of the action, as well as others, will likely be established in the future.

Codon usage and gene function are related in sequences of Arabidopsis thaliana.

In this paper, the relationship between codon usage and the physiological pattern of expression of a gene is investigated while considering a dataset of 815 nuclear genes of Arabidopsis thaliana. Factorial Correspondence Analysis, a commonly used multivariate statistical approach in codon usage analysis, was used in order to analyse codon usage bias gene by gene. The analysis reveals a single major trend in codon usage among genes in Arabidopsis. At one end of the trend lie genes with a highly G/C biased codon usage. This group contains mainly photosynthetic and housekeeping genes which are known to encode the most abundant proteins of the vegetal cell. At the other extreme lie genes with a weaker A/T-biased codon usage. This group contain genes with various functions which exhibits most of the time a strong tissue-specific pattern of expression in relation, for example, to stress conditions. These observations were confirmed by the detailed analysis of codon usage in the multigene family of tubulins and appear to be general in plant species, even as distant from Arabidopsis thaliana as a monocotyledonous plant such as maize.

Exon prediction in eucaryotic genomes.

Two independent computer systems, NetPlantGene and AMELIE, dedicated to the identification of splice sites in plant and human genomes, respectively, are introduced here. Both methods were designed in relation to experimental work; they rely on automatically generated rules involving the nucleotide content of sequences regardless of the coding properties of exons. The specificity of plant sequences as considered in NetPlantGene is shown to enhance the quality of detection as opposed to general methods such as GRAIL. A scanning model of the acceptor site recognition is being simulated by AMELIE leading to a relatively accurate selection process of sites.

Functional specifications of an integrated proteomics information management and analysis platform.

Detecting proteins in human blood holds the promise of a revolution in cancer diagnosis. Also, the ability to perform laboratory operations on small scales using miniaturized (lab-on-a-chip) devices has many benefits. Designing and fabricating such systems is extremely challenging, but physicists and engineers are beginning to construct such highly integrated and compact labs on chips with exciting functionality. This paper focuses on the presentation of the requirements of the information technology layer in such an integrated platform been developed in the LOCCANDIA project. LOCCANDIA is a Specific Targeted Research project (STREP) funded under the 6th Framework program of the EC. Its ultimate objective is to develop an innovative nano-technology based (lab-on-a-chip) platform for the medical-proeomics field. The paper presents the main engineering aspects, challenges and architecture for creating an Integrated Clinico-Proteomic Environment. The environment will be used to monitor and document the analysis and discovery chain and to allow the physician to interpret the digital spectrogram data delivered by the mass spectrometer, for diagnostic purposes.

A Multi-Agent System for Exon Prediction in Human Sequences.

Given the problem of identifying exons in new genomic DNA, the sketch of a resolution process was drawn using sequence data and models of site/signal recognition. A multi-agent architecture is used to validate these models and test hypotheses on the chronology of events involved in gene splicing. Information is channelled through a hierarchy of agents. Each type of agent is the result of a successful step in the resolution process. The system does not rely on the compositional bias of coding sequences which is a key feature of current computer methods.

A multi-agent system simulating human splice site recognition.

The present paper describes a method detecting splice sites automatically on the basis of sequence data and models of site/signal recognition supported by experimental evidences. The method is designed to simulate splicing and while doing so, track prediction failures, missing information and possibly test correcting hypotheses. Correlations between nucleotides in the splice site regions and the various elements of the acceptor region are evaluated and combined to assess compensating interactions between elements of the splicing machinery. A scanning model of the acceptor region and a model of interaction between the splicing complexes (exon definition model) are also incorporated in the detection process. Subsets of sites presenting deficiencies of several splice site elements could be identified. Further examination of these sites helps to determine lacking elements and refine models.

Global analysis of genomic texts: the distribution of AGCT tetranucleotides in the Escherichia coli and Bacillus subtilis genomes predicts translational frameshifting and ribosomal hopping in several genes.

Present availability of the genomic text of bacteria allows assignment of biological known functions to many genes (typically, half of the genome's gene content). It is now time to try and predict new unexpected functions, using inductive procedures that allow correlating the content of the genomic text to possible biological functions. We show here that analysis of the genomes of Escherichia coli and Bacillus subtilis for the distribution of AGCT motifs predicts that genes exist for which the mRNA molecule can be translated as several different proteins synthesized after ribosomal frameshifting or hopping. Among these genes we found that several coded for the same function in E. coli and B. subtilis. We analyzed in depth the situation of the infB gene (experimentally known to specify synthesis of several proteins differing in their translation starts), the aceF/pdhC gene, the eno gene, and the rplI gene. In addition, genes specific to E. coli were also studied: ompA, ompFand tolA (predicting epigenetic variation that could help escape infection by phages or colicins).

Strategy for protein isoform identification from expressed sequence tags and its application to peptide mass fingerprinting.

Expressed Sequence Tags (ESTs) are an invaluable resource for protein identification and characterisation in proteomics. They allow proteins to be identified in the absence of genome sequence data. When EST sequences are used for protein identification, they are usually first processed into contigs to reduce redundancy and generate longer sequences from the overlapping ESTs. However, the process of generating contigs may accidentally group biologically meaningful isoforms together. Here we report means of discovering isoforms in EST sequences and how to use this information in the framework of protein identification and characterisation with peptide mass fingerprinting. We illustrate our strategies with examples from the dbEST database as well as protein isoforms from two-dimensional polyacrylamide gels.

Shaping biological knowledge: applications in proteomics.

The central dogma of molecular biology has provided a meaningful principle for data integration in the field of genomics. In this context, integration reflects the known transitions from a chromosome to a protein sequence: transcription, intron splicing, exon assembly and translation. There is no such clear principle for integrating proteomics data, since the laws governing protein folding and interactivity are not quite understood. In our effort to bring together independent pieces of information relative to proteins in a biologically meaningful way, we assess the bias of bioinformatics resources and consequent approximations in the framework of small-scale studies. We analyse proteomics data while following both a data-driven (focus on proteins smaller than 10 kDa) and a hypothesis-driven (focus on whole bacterial proteomes) approach. These applications are potentially the source of specialized complements to classical biological ontologies.