Biomedical subjects

Guy Perrière

Publications and source records attributed to Guy Perrière.

10 recordsLinked to original sources

PubMed2003

The source of laterally transferred genes in bacterial genomes.

BACKGROUND: Laterally transferred genes have often been identified on the basis of compositional features that distinguish them from ancestral genes in the genome. These genes are usually A+T-rich, arguing either that there is a bias towards acquiring genes from donor organisms having low G+C contents or that genes acquired from organisms of similar genomic base compositions go undetected in these analyses. RESULTS: By examining the genome contents of closely related, fully sequenced bacteria, we uncovered genes confined to a single genome and examined the sequence features of these acquired genes. The analysis shows that few transfer events are overlooked by compositional analyses. Most observed lateral gene transfers do not correspond to free exchange of regular genes among bacterial genomes, but more probably represent the constituents of phages or other selfish elements. CONCLUSIONS: Although bacteria tend to acquire large amounts of DNA, the origin of these genes remains obscure. We have shown that contrary to what is often supposed, their composition cannot be explained by a previous genomic context. In contrast, these genes fit the description of recently described genes in lambdoid phages, named 'morons'. Therefore, results from genome content and compositional approaches to detect lateral transfers should not be cited as evidence for genetic exchange between distantly related bacteria.

Arginine↗

PubMed2003

Integrated databanks access and sequence/structure analysis services at the PBIL.

The World Wide Web server of the PBIL (Pôle Bioinformatique Lyonnais) provides on-line access to sequence databanks and to many tools of nucleic acid and protein sequence analyses. This server allows to query nucleotide sequence banks in the EMBL and GenBank formats and protein sequence banks in the SWISS-PROT and PIR formats. The query engine on which our data bank access is based is the ACNUC system. It allows the possibility to build complex queries to access functional zones of biological interest and to retrieve large sequence sets. Of special interest are the unique features provided by this system to query the data banks of gene families developed at the PBIL. The server also provides access to a wide range of sequence analysis methods: similarity search programs, multiple alignments, protein structure prediction and multivariate statistics. An originality of this server is the integration of these two aspects: sequence retrieval and sequence analysis. Indeed, thanks to the introduction of re-usable lists, it is possible to perform treatments on large sets of data. The PBIL server can be reached at: http://pbil.univ-lyon1.fr.

Databases, Genetic↗

PubMed2003

G+C3 structuring along the genome: a common feature in prokaryotes.

The heterogeneity of gene nucleotide content in prokaryotic genomes is commonly interpreted as the result of three main phenomena: (1) genes undergo different selection pressures both during and after translation (affecting codon and amino acid choice); (2) genes undergo different mutational pressure whether they are on the leading or lagging strand; and (3) genes may have different phylogenetic origins as a result of lateral transfers. However, this view neglects the necessity of organizing genetic information on a chromosome that needs to be replicated and folded, which may add constraints to single gene evolution. As a consequence, genes are potentially subjected to different mutation and selection pressures, depending on their position in the genome. In this paper, we analyze the structuring of different codon usage measures along completely sequenced bacterial genomes. We show that most of them are highly structured, suggesting that genes have different base content, depending on their location on the chromosome. A peculiar pattern of genome structure, with a tendency toward an A+T-enrichment near the replication terminus, is found in most bacterial phyla and may reflect common chromosome constraints. Several species may have lost this pattern, probably because of genome rearrangements or integration of foreign DNA. We show that in several species, this enrichment is associated with an increase of evolutionary rate and we discuss the evolutionary implications of these results. We argue that structural constraints acting on the circular chromosome are not negligible and that this natural structuring of bacterial genomes may be a cause of overestimation in lateral gene transfer predictions using codon composition indices.

Base Composition↗

PubMed2003

RTKdb: database of Receptor Tyrosine Kinase.

Receptor Tyrosine Kinases (RTK) are transmembrane receptors specifically found in metazoans. They represent an excellent model for studying evolution of cellular processes in metazoans because they encompass large families of modular proteins and belong to a major family of contingency generating molecules in eukaryotic cells: the protein kinases. Because tyrosine kinases have been under close scrutiny for many years in various species, they are associated with a wealth of information, mainly in mammals. Presently, most categories of RTK were identified in mammals, but in a near future other model species will be sequenced, and will bring us RTKs from other metazoan clades. Thus, collecting RTK sequences would provide a good starting point as a new model for comparative and evolutionary studies applying to multigene families. In this context, we are developing the Receptor Tyrosine Kinase database (RTKdb), which is the only database on tyrosine kinase receptors presently available. In this database, protein sequences from eight model metazoan species are organized under the format previously used for the HOVERGEN, HOBACGEN and NUREBASE systems. RTKdb can be accessed through the PBIL (Pôle Bioinformatique Lyonnais) World Wide Web server at http://pbil.univ-lyon1.fr/RTKdb/, or through the FamFetch graphical user interface available at the same address.

Animals↗

PubMed2003

Use of correspondence discriminant analysis to predict the subcellular location of bacterial proteins.

Correspondence discriminant analysis (CDA) is a multivariate statistical method derived from discriminant analysis which can be used on contingency tables. We have used CDA to separate Gram negative bacteria proteins according to their subcellular location. The high resolution of the discrimination obtained makes this method a good tool to predict subcellular location when this information is not known. The main advantage of this technique is its simplicity. Indeed, by computing two linear formulae on amino acid composition, it is possible to classify a protein into one of the three classes of subcellular location we have defined. The CDA itself can be computed with the ADE-4 software package that can be downloaded, as well as the data set used in this study, from the Pôle Bio-Informatique Lyonnais (PBIL) server at http://pbil.univ-lyon1.fr.

Bacterial Proteins↗

PubMed2002

Use and misuse of correspondence analysis in codon usage studies.

Correspondence analysis has frequently been used for codon usage studies but this method is often misused. Because amino acid composition exerts constraints on codon usage, it is common to use tables containing relative codon frequencies (or ratios of frequencies) instead of simple codon counts to get rid of these amino acid biases. The problem is that some important properties of correspondence analysis, such as rows weighting, are lost in the process. Moreover, the use of relative measures sometimes introduces other biases and often diminishes the quantity of information to analyse, occasionally resulting in interpretation errors. For instance, in the case of an organism such as Borrelia burgdorferi, the use of relative measures led to the conclusion that there was no translational selection, while analyses based on codon counts show that there is a possibility of a selective effect at that level. In this paper, we expose these problems and we propose alternative strategies to correspondence analysis for studying codon usage biases when amino acid composition effects must be removed.

Bacillus subtilis↗

PubMed2002

NUREBASE: database of nuclear hormone receptors.

Nuclear hormone receptors are an abundant class of ligand activated transcriptional regulators, found in varying numbers in all animals. Based on our experience of managing the official nomenclature of nuclear receptors, we have developed NUREBASE, a database containing protein and DNA sequences, reviewed protein alignments and phylogenies, taxonomy and annotations for all nuclear receptors. The reviewed NUREBASE is completed by NUREBASE_DAILY, automatically updated every 24 h. Both databases are organized under a client/server architecture, with a client written in Java which runs on any platform. This client, named FamFetch, integrates a graphical interface allowing selection of families, and manipulation of phylogenies and alignments. NUREBASE sequence data is also accessible through a World Wide Web server, allowing complex queries. All information on accessing and installing NUREBASE may be found at http://www.ens-lyon.fr/LBMC/laudet/nurebase.html.

Amino Acid Sequence↗

PubMed2002

Between-group analysis of microarray data.

MOTIVATION: Most supervised classification methods are limited by the requirement for more cases than variables. In microarray data the number of variables (genes) far exceeds the number of cases (arrays), and thus filtering and pre-selection of genes is required. We describe the application of Between Group Analysis (BGA) to the analysis of microarray data. A feature of BGA is that it can be used when the number of variables (genes) exceeds the number of cases (arrays). BGA is based on carrying out an ordination of groups of samples, using a standard method such as Correspondence Analysis (COA), rather than an ordination of the individual microarray samples. As such, it can be viewed as a method of carrying out COA with grouped data. RESULTS: We illustrate the power of the method using two cancer data sets. In both cases, we can quickly and accurately classify test samples from any number of specified a priori groups and identify the genes which characterize these groups. We obtained very high rates of correct classification, as determined by jack-knife or validation experiments with training and test sets. The results are comparable to those from other methods in terms of accuracy but the power and flexibility of BGA make it an especially attractive method for the analysis of microarray cancer data.

Algorithms↗

PubMed2002

A mathematical method for determining genome divergence and species delineation using AFLP.

The delineation of bacterial species is presently achieved using direct DNA-DNA relatedness studies of whole genomes. It would be helpful to obtain the same genomically based delineation by indirect methods, provided that descriptions of individual genome composition of bacterial genomes are obtained and included in species descriptions. The amplified fragment length polymorphism (AFLP) technique could provide the necessary data if the nucleotides involved in restriction and amplification are fundamental to the description of genomic divergences. Firstly, in order to verify that AFLP analysis permits a realistic exploration of bacterial genome composition, the strong correspondence between predicted and experimental AFLP data was demonstrated using Agrobacterium strain C58 as a model system. Secondly, a method is proposed for determining current genome mispairing and evolutionary genome divergences between pairs of bacteria, based on arbitrary sampling of genomes by using AFLP. The measure of current genome mispairing was validated by comparison with DNA-DNA relatedness data, which itself correlates with base mispairing. The evolutionary genome divergence is the estimated rate of nucleotide substitution that has occurred since the strains diverged from a common ancestor. Current genome mispairing and evolutionary genome divergence were used to compare members of Agrobacterium, used as a model of closely related genomic species. A strong and highly significant correlation was found between calculated genome mispairing and DNA-DNA relatedness values within genomic species. The canonical 70% DNA-DNA hybridization value used to delineate genomic species was found to correspond to a range of current genome mispairing of 13-13.6%. These limits correspond to 0.097 and 0.104 nucleotide substitutions per site, respectively. In addition, experimental data showed that the large Ti and cryptic plasmids of Agrobacterium had little effect on the estimation of genome divergence. Evolutionary genome divergence was used for phylogenetic inferences. Data showed that members of the same genomic species clustered consistently, as supported by bootstrap resampling. On the basis of these results, it is proposed that the genomic delineation of bacterial species could be based, in future, on phylogenetic groups supported by bootstraps and genome descriptions of individual strains, obtained by AFLP analysis, recorded in accessible databases; this approach might eventually replace DNA-DNA hybridization studies.

Biological Evolution↗

PubMed2002

A phylogenomic approach to bacterial phylogeny: evidence of a core of genes sharing a common history.

It has been claimed that complete genome sequences would clarify phylogenetic relationships between organisms, but up to now, no satisfying approach has been proposed to use efficiently these data. For instance, if the coding of presence or absence of genes in complete genomes gives interesting results, it does not take into account the phylogenetic information contained in sequences and ignores hidden paralogies by using a BLAST reciprocal best hit definition of orthology. In addition, concatenation of sequences of different genes as well as building of consensus trees only consider the few genes that are shared among all organisms. Here we present an attempt to use a supertree method to build the phylogenetic tree of 45 organisms, with special focus on bacterial phylogeny. This led us to perform a phylogenetic study of congruence of tree topologies, which allows the identification of a core of genes supporting similar species phylogeny. We then used this core of genes to infer a tree. This phylogeny presents several differences with the rRNA phylogeny, notably for the position of hyperthermophilic bacteria.

Computational Biology↗