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One of the fundamental techniques of biology is sequence alignment, namely transforming one sequence into another with minimal change. Sequence alignment is essential for evolutionary studies and is a source of information for the analysis of the physico-chemical mechanisms which are at the heart of protein activity. Biologists almost exclusively use methods based on a very simple model, although they are aware that this can be quite removed from reality. In fact, the more complex models involve so many variables that they cannot be calculated in practice. This paper presents a method to estimate the quality of the approximation made using simple models, giving a measure of the deviation from reality. It is exclusively based on the analysis of pairwise alignments, without resorting to multiple alignments, and therefore without requiring the construction of trees and the problems associated with it. The paper also describes an approach that allows building trees and clusters from sequences without strongly relying on the choice of a dissimilarity measure. It illustrates the interest and effectiveness of the point of view promoted by Alex: assume as little as possible and try to gather information from the data, before turning to explicit modeling if necessary., L'une des techniques fondamentales de la biologie est l'alignement de séquences, c'est-à-dire la transformation d'une séquence en une autre avec un minimum de changement. L'alignement de séquences est essentiel pour les études évolutives et constitue une source d'information pour l'analyse des mécanismes physico-chimiques qui sont au cœur de l'activité des protéines. Les biologistes utilisent presque exclusivement des méthodes basées sur un modèle très simple, même s'ils sont conscients que cela peut être assez éloigné de la réalité. En fait, les modèles les plus complexes impliquent tellement de variables qu'elles ne peuvent pas être calculées en pratique. Cet article présente une méthode pour estimer la qualité de l'approximation faite à l'aide de modèles simples, donnant une mesure de l'écart par rapport à la réalité. Elle repose exclusivement sur l'analyse d'alignements par paires, sans recourir à des alignements multiples, et donc sans nécessiter la construction d'arbres et les problèmes qui y sont associés. L'article décrit également une approche qui permet de construire des arbres et des clusters à partir de séquences sans dépendre fortement du choix d'une mesure de dissimilarité. Elle illustre l'intérêt et l'efficacité du point de vue promu par Alex : supposer le moins possible et essayer de recueillir des informations à partir des données, avant de se tourner si nécessaire vers une modélisation explicite.

Summer mortality of the Pacific oyster Crassostrea gigas is the result of a complex interaction between oysters, their environment, and pathogens. Heredity appears to be a major factor determining the sensitivity of oysters to summer mortality, allowing resistant (R) and susceptible (S) lines to be produced. We conducted genome-wide expression profiling of R and S gonads during the 3-month period preceding a summer mortality event, using a cDNA microarray that we designed. ANOVA analysis revealed that 34 genes were differentially expressed between R and S lines on four dates preceding the mortality event. Annotation of some of these genes highlights reproduction and its allocation and antioxidant defenses as the main pathways that operate differentially between R and S lines. This transcriptional analysis provides new indications to define markers for quantitative trait loci searches and functional studies and evaluate the potential role of each gene in the resistance to summer mortality.

In this note, it is shown that by applying ranking procedures to data that allow, for any three objects a1; a2; b in a collection X of objects of interest, to make consistent decisions about which of the two objects a1 or a2 is more similar to b, a family of cluster systems A (k) (k = 0; 1;:::) can be constructed that start with the associated Apresjan Hierarchy and keep growing until, for k = #X 1, the full set P (X) of all subsets of X is reached. Various ideas regarding canonical modications of the similarity values so that these cluster systems contain as many clusters as possible for small values of k (and in particular for k := 0) and/or are rooted at a specic element in X, possible applications, e.g. concerning (i) the comparison of distinct dissimilarity data dened on the same set X or (ii) diversity optimization, and new tasks arising in ranking statistics are also discussed.

Web geometry is devoted to the study of families of foliations which are in general position. We restrict ourselves to the local situation, in the neighborhood of the origin in C2, with d > 1 complex analytic foliations of curves in general position. We are interested in the geometry of such configurations, that is, properties of planar d-webs which are invariant with respect to analytic local isomorphisms of C2. The initiators of the subject are W. Blaschke, G. Thomsen and G. Bol

A $d$-web ${\Cal W}(d)$ is given by $d$ complex analytic foliations of codimension $n$ in $({\sumbbb C}^N,0)$ such that the leaves are in general position. We are interested in the geometry of such configurations. A complex $({\Cal A}^{\bullet},\delta)$ of ${\sumbbb C}$-vector spaces is defined in which ${\Cal A}^0$ corresponds to functions and ${\Cal A}^p$ to $p$-forms of the web ${\Cal W}(d)$ for $1\leq p\leq n$. If $N=kn$ with $k\geq 2$, it is proved that $r_p:=\dim_{\,\sumbbb C}{\Cal A}^p$ is a finite analytic invariant of ${\Cal W}(d)$ with an optimal upper bound $\pi_{p}(d,k,n)$ for $0\leq p\leq n$. These bounds generalize the Castelnuovo’s ones for genus of curves in ${\sumbbb P}^{k}$ with degree $d$. Some characterization of the the space $H^0(V_n,\omega^p_{V_n})$ of abelian differentials to an algebraic variety $V_n$ in ${\sumbbb P}^{n+k-1}$ of pure dimension $n$ with degree $d$ is given. Moreover, using duality and Abel’s theorem, we investigate how for suitable $V_n$ the natural complex $\bigr(H^0(V_n,\omega^{\bullet}_{V_n}),d\,\bigr)$ and the abelian relation complex $({\Cal A}^{\bullet},\delta)$ of the linear web associated to $V_n$ in $({\sumbbb C}^{kn},0)$ are related.

An analytic \(d\)-web \(\mathcal{W}(d)\) in a neighborhood of \(0\in {\mathbb C}^2\) with \(d\ge 4\) and maximum rank \(\pi _d:={1\over 2}(d-1)(d-2)\) gives rise to an analytic map \({\mathfrak u}:({\mathbb C}^2,0)\longrightarrow \check{\mathbb P}^{\,\pi _d-1}\) through an abelian basis. Classic and new properties of the resulting projective surface, smooth but transcendental in general, are presented. Modeled on the previous \(\mathfrak u\), special maps \(f:({\mathbb C}^2,0)\longrightarrow \check{\mathbb P}^{\,\pi _d-1}\) induce Bompiani webs \(\mathcal{W}_f(d)\) through their \((d-4)\)-principal curves that we define. It is proved in particular that those Bompiani webs \(\mathcal{W}_f(d)\) of maximum rank are characterized only by a vanishing curvature.

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, ompF and tolA (predicting epigenetic variation that could help escape infection by phages or colicins).

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.

Resume Un d-tissu W(d,2,n) est defini par d feuilletages analytiques complexes de codimension n de ( C 2n, 0) dont les feuilles sont en position generale. On s'interesse a la geometrie de telles configurations. S. S. Chem et P. A. Griffiths ont donne une borne optimale du principal invariant de W(d, 2, n) que l'on appelle le n-rang. Toute hypersurface algebrique reduite Vn de P n+1 dont le degre est d determine, generiquement dans la grassmannienne G(1, P n+1) des droites de P n+1, un d-tisssu L Vn(d, 2, n). Grâce au theoreme d'Abel, le n-rang de L Vn (d, 2, n) est maximal et egal au genre arithmetique de Vn. On caracterise pour d ≥ n + 3 ≥ 5 les d-tissus W(d, 2, n) dont le n-rang est maximal : ils sont algebriques (i.e. a un isomorphisme local pres et avec les notations precedentes, on a W(d, 2, n) = L Vn(d, 2, n)).

A computer-assisted analysis was made of 24 complete nucleotide sequences selected from the vertebrate retroviruses to represent the ten viral groups. The conclusions of this analysis extend and strengthen the previously made hypothesis on the Moloney murine leukemia virus: The evolution of the nucleotide sequence appears to have occurred mainly through at least three overlapping levels of duplication: (1) The distributions of overrepresented (3-6)-mers are consistent with the universal rule of a trend toward TG/CT excess and with the persistence of a certain degree of symmetry between the two strands of DNA. This suggests one or several original tandemly repeated sequences and some inverted duplications. (2) The existence of two general core consensuses at the level of these (3-6)-mers supports the hypothesis of a common evolutionary origin of vertebrate retroviruses. Consensuses more specific to certain sequences are compatible with phylogenetic trees established independently. The consensuses could correspond to intermediary evolutionary stages. (3) Most of the (3-6)-mers with a significantly higher than average frequency appear to be internally repeated (with monomeric or oligomeric internal iterations) and seem to be at least partly the cause of the bias observed by other researchers at the level of retroviral nucleotide composition. They suggest a third evolutionary stage by slippage-like stepwise local duplications.

A d-web in (\(\mathbb{C}^n \),0) is given by d complex analytic foliations of codimension one in (\(\mathbb{C}^n \),0) which are in general position. A d-web \(\mathcal{L}(d)\) in (\(\mathbb{C}^n \),0) is linear if all the leaves are (pieces of) hyperplanes in \(\mathbb{C}^n \) and \(\mathcal{L}(d)\) is algebraic if it is associated, by duality, to a nondegenerate algebraic curve Г in \(\mathbb{P}^n \) of degree d. We characterize linear webs in (\(\mathbb{C}^n \),0). We give explicit conditions under which a linear d-web in (\(\mathbb{C}^n \),0) is algebraic and we obtain equations for \(\Gamma \subset \mathbb{P}^n \) in this case. Some related problems are discussed and some questions are posed.

Motivation: Compression algorithms can be used to analyse genetic sequences. A compression algorithm tests a given property on the sequence and uses it to encode the sequence: if the property is true, it reveals some structure of the sequence which can be described briefly, this yields a description of the sequence which is shorter than the sequence of nucleotides given in extenso. The more a sequence is compressed by the algorithm, the more significant is the property for that sequence. Results: We present a compression algorithm that tests the presence of a particular type of dosDNA (defined ordered sequence-DNA): approximate tandem repeats of small motifs (i.e. of lengths

International audience; Leukodystrophies (LD) are rare inherited disorders that primarily affect the white matter (WM) of the central nervous system. The large heterogeneity of LD results from the diversity of the genetically determined defects that interfere with glial cells functions. Astrocytes have been identified as the primary target of LD with cystic myelin breakdown including those related to mutations in the ubiquitous translation initiation factor eIF2B. EIF2B is involved in global protein synthesis and its regulation under normal and stress conditions. Little is known about how eIF2B mutations have a major effect on WM. We performed a transcriptomic analysis using fibroblasts of 10 eIF2B-mutated patients with a severe phenotype and 10 age matched patients with other types of LD in comparison to control fibroblasts. ANOVA was used to identify genes that were statistically significantly differentially expressed at basal state and after ER-stress. The pattern of differentially expressed genes between basal state and ER-stress did not differ significantly among each of the three conditions. However, 70 genes were specifically differentially expressed in eIF2B-mutated fibroblasts whatever the stress conditions tested compared to controls, 96% being under-expressed. Most of these genes were involved in mRNA regulation and mitochondrial metabolism. The 13 most representative genes, including genes belonging to the Heterogeneous Nuclear Ribonucleoprotein (HNRNP) family, described as regulators of splicing events and stability of mRNA, were dysregulated during the development of eIF2B-mutated brains. HNRNPH1, F and C mRNA were over-expressed in foetus but under-expressed in children and adult brains. The abnormal regulation of HNRNP expression in the brain of eIF2B-mutated patients was concomitant with splicing dysregulation of the main genes involved in glial maturation such as PLP1 for oligodendrocytes and GFAP in astrocytes. These findings demonstrate a developmental deregulation of splicing events in glial cells that is related to abnormal production of HNRNP, in eIF2B-mutated brains.

A method aimed at classifying protein sequences withoutresorting to pairwise alignment is presented. Called DOCMA(DOt-plot Comparisons by Multivariate Analysis), it is basedon a multivariate analysis of the pairwise dot-plots between allthe sequences in the set. The dot-plots are first simplified byconsidering only the projections of the 'diagonal' segments ofsimilarity onto the axes. From these projections a data matrixis built, in which each column is representative of thecomparisons of one given sequence with all the other ones. Thisdata matrix is then transformed into a distance matrix by achi-squared analysis, from which the coordinates of thesequences in an orthonormal Euclidean space are obtained. Thesequences are finally classified by a dynamic clusteringprocedure followed by a search for strong clusters. Applicationof this method to protein families such as the globins, thecytochromes c and the aminoacyl-tRNA synthetases shows thatit is quite effective in delineating subgroups that contain evendistantly related sequences.IntroductionAs more and more amino acid sequences of proteins becomeavailable, there has been a growing number of studies aimedat establishing the evolutionary relationships between membersof one given set of proteins, or, less ambitiously, at classifyingthe sequences as a function of their similarities. In the first case,the problem is to find the tree(s) in which the lengths of thebranches reflect at best the pairwise distances between thesequences—assuming that these distances are directly relatedto evolutionary times. The search for such a tree is generallyextremely time consuming, even if efficient heuristics are usedto speed up the process. For instance, the determination of themost parsimonious tree for 245 globin sequences (Goodmanet al., 1988) required the use of a Cray-2 supercomputer. In thesecond case, the problem is rather to delineate the groups, orclusters, of the most closely related sequences. The informationthus gained can be used, for instance, as a guideline forperforming a multiple alignment of the sequences, i.e. thosethat are most alike will be aligned first (e.g. Corpet, 1988; Fengand Doolittle, 1987; Taylor, 1988), or to select those sequences

The present work describes an attempt to identify reliable criteria which could be used as distance indices between protein sequences. Seven different criteria have been tested: i and ii) the scores of the alignments as given by the BESTFIT and the FASTA programs; iii) the ratio parameter, i.e. the BESTFIT score divided by the length of the aligned peptides; iv and v) the statistical significance (Z-scores) of the scores calculated by BESTFIT and FASTA, as obtained by comparison with shuffled sequences; vi) the Z-scores provided by the program RELATE which performs a segment-by-segment comparison of 2 sequences, and vii) an original distance index calculated by the program DOCMA from all the pairwise dotplots between the sequences. These 7 criteria have been tested against the aminoacid sequences of 39 globins and those of the 20 aminoacyl-tRNA synthetases from E. coli. The distances between the sequences were analyzed by the multivariate analysis techniques. The results show that the distances calculated from the scores of the pairwise alignments are not adequately sensitive. The Z-score from RELATE is not selective enough and too demanding in computer time. Three criteria gave a classification consistent with the known similarities between the sequences in the sets, namely the Z-scores from BESTFIT and FASTA and the multiple dotplot comparison distance index from DOCMA.

International audience

A characteristic profile of the fluctuations of codon usage is observed in bacteriophages and mitochondria. By following the DNA in the direction of transcription, one moves slowly from a region where selective pressure favours codons ending with C to a region where the bias is in favour of codons ending with T; then, abruptly, one again enters a region of codons ending in C. The transcription end point takes place in the area of abrupt change in codon usage. By comparing Drosophila yakuba and mouse mitochondrial genomes, it is possible to show that the strategy of codon usage for a given gene depends on its location along the transcription unit and not on the encoded protein. The choice of codons ending in T or C allows large scale variations of DNA stability which could regulate the speed of propagation of the RNA polymerase.

The information collected in national and international libraries on nucleotide and protein sequences cannot be directly treated for proper handling by existing software. Therefore we evaluated the feasibility of constructing a data base for Escherichia coli using the data present in the banks. The knowhow thus acquired was applied to Bacillus subtilis. Specific examples of the general procedure are given.

Yarrowia lipolytica is one of the yeasts most frequently isolated from the surface of ripened cheeses. In previous work, it has been shown that this yeast is able to convert l -methionine into various volatile sulfur compounds (VSCs) that may contribute to the typical flavors of several cheeses. In the present study, we show that Y. lipolytica does not assimilate lactate in the presence of l -methionine in a cheeselike medium. Nineteen presumptive genes associated with l -methionine catabolism or pyruvate metabolism in Y. lipolytica were transcriptionally studied in relation to l -methionine degradation. The expression levels of the Yl ARO8 (YALI0E20977g), Yl BAT1 (YALI0D01265g), and Yl BAT2 (YALI0F19910g) genes (confirmed by real-time PCR experiments) were found to be strongly up-regulated by l -methionine, and a greater variety and larger amounts of VSCs, such as methanethiol and its autooxidation products (dimethyl disulfide and dimethyl trisulfide), were released in the medium when Y. lipolytica was grown in the presence of a high concentration of l -methionine. In contrast, other genes related to pyruvate metabolism were found to be down-regulated in the presence of l -methionine; two exceptions were the Yl PDB1 (YALI0E27005g) and Yl PDC6 (YALI0D06930g) genes, which encode a pyruvate dehydrogenase and a pyruvate decarboxylase, respectively. Both transcriptional and biochemical results corroborate the view that transamination is the first step of the enzymatic conversion of l -methionine to VSCs in Y. lipolytica and that the Yl ARO8 , Yl BAT1 , and Yl BAT2 genes could play a key role in this process.

Background The processes of gene transcription, translation, as well as the reactions taking place between gene products, are subject to stochastic fluctuations. These stochastic events are being increasingly examined as it emerges that they can be crucial in the cell's survival. In a previous study we had examined the transcription patterns of two bacterial species (Escherichia coli and Bacillus subtilis) to elucidate the nucleoid's organization. The basic idea is that genes that share transcription patterns, must share some sort of spatial relationship, even if they are not close to each other on the chromosome. We had found that picking any gene at random, its transcription will be correlated with genes at well-defined short – as well as long-range distances, leaving the explanation of the latter an open question. In this paper we study the transcription correlations when the only transcription taking place is stochastic, in other words, no active or "deterministic" transcription takes place. To this purpose we use transcription data of Sinorhizobium meliloti. Results Even when only stochastic transcription takes place, the co-expression of genes varies as a function of the distance between genes: we observe again the short-range as well as the regular, long-range correlation patterns. Conclusion We explain these latter with a model based on the physical constraints acting on the DNA, forcing it into a conformation of groups of a few successive large and transcribed loops, which are evenly spaced along the chromosome and separated by small, non-transcribed loops. We discuss the question about the link between shared transcription patterns and physiological relationship and come to the conclusion that when genes are distantly placed along the chromosome, the transcription correlation does not imply a physiological relationship.

DNA microarrays of 86 genes from the yeasts Debaryomyces hansenii , Kluyveromyces marxianus , and Yarrowia lipolytica were developed to determine which genes were expressed in a medium mimicking a cheese-ripening environment. These genes were selected for potential involvement in lactose/lactate catabolism and the biosynthesis of sulfur-flavored compounds. Hybridization conditions to follow specifically the expression of homologous genes belonging to different species were set up. The microarray was first validated on pure cultures of each yeast; no interspecies cross-hybridization was observed. Expression patterns of targeted genes were studied in pure cultures of each yeast, as well as in coculture, and compared to biochemical data. As expected, a high expression of the LAC genes of K. marxianus was observed. This is a yeast that efficiently degrades lactose. Several lactate dehydrogenase-encoding genes were also expressed essentially in D. hansenii and K. marxianus , which are two efficient deacidifying yeasts in cheese ripening. A set of genes possibly involved in l -methionine catabolism was also used on the array. Y. lipolytica , which efficiently assimilates l -methionine, also exhibited a high expression of the Saccharomyces cerevisiae orthologs BAT2 and ARO8 , which are involved in the l -methionine degradation pathway. Our data provide the first evidence that the use of a multispecies microarray could be a powerful tool to investigate targeted metabolism and possible metabolic interactions between species within microbial cocultures.

Background Although the organisation of the bacterial chromosome is an area of active research, little is known yet on that subject. The difficulty lies in the fact that the system is dynamic and difficult to observe directly. The advent of massive hybridisation techniques opens the way to further studies of the chromosomal structure because the genes that are co-expressed, as identified by microarray experiments, probably share some spatial relationship. The use of several independent sets of gene expression data should make it possible to obtain an exhaustive view of the genes co-expression and thus a more accurate image of the structure of the chromosome. Results For both Bacillus subtilis and Escherichia coli the co-expression of genes varies as a function of the distance between the genes along the chromosome. The long-range correlations are surprising: the changes in the level of expression of any gene are correlated (positively or negatively) to the changes in the expression level of other genes located at well-defined long-range distances. This property is true for all the genes, regardless of their localisation on the chromosome. We also found short-range correlations, which suggest that the location of these co-expressed genes corresponds to DNA turns on the nucleoid surface (14–16 genes). Conclusion The long-range correlations do not correspond to the domains so far identified in the nucleoid. We explain our results by a model of the nucleoid solenoid structure based on two types of spirals (short and long). The long spirals are uncoiled expressed DNA while the short ones correspond to coiled unexpressed DNA.

International audience; Microarrays are becoming a ubiquitous tool of research in life sciences. However, the working principles of microarray-based methodologies are often misunderstood or apparently ignored by the researchers who actually perform and interpret experiments. This in turn seems to lead to a common over-expectation regarding the explanatory and/or knowledge-generating power of microarray analyses.In this note we intend to explain basic principles of five (5) major groups of analytical techniques used in studies of microarray data and their interpretation: the principal component analysis (PCA), the independent component analysis (ICA), the t-test, the analysis of variance (ANOVA), and self organizing maps (SOM). We discuss answers to selected practical questions related to the analysis of microarray data. We also take a closer look at the experimental setup and the rules, which have to be observed in order to exploit microarrays efficiently. Finally, we discuss in detail the scope and limitations of microarray-based methods. We emphasize the fact that no amount of statistical analysis can compensate for (or replace) a well thought through experimental setup. We conclude that microarrays are indeed useful tools in life sciences but by no means should they be expected to generate complete answers to complex biological questions. We argue that even well posed questions, formulated within a microarray-specific terminology, cannot be completely answered with the use of microarray analyses alone.

The number of statistical tools used to analyze transcriptome data is continuously increasing and no one, definitive method has so far emerged. There is a need for comparison and a number of different approaches has been taken to evaluate the effectiveness of the different statistical tools available for microarray analyses. In this paper, we describe a simple and efficient protocol to compare the reliability of different statistical tools available for microarray analyses. It exploits the fact that genes within an operon exhibit the same expression patterns. In order to compare the tools, the genes are ranked according to the most relevant criterion for each tool; for each tool we look at the number of different operons represented within the first twenty genes detected. We then look at the size of the interval within which we find the most significant genes belonging to each operon in question. This allows us to define and estimate the sensitivity and accuracy of each statistical tool. We have compared four statistical tools using Bacillus subtilis expression data: the analysis of variance (ANOVA), the principal component analysis (PCA), the independent component analysis (ICA) and the partial least square regression (PLS). Our results show ICA to be the most sensitive and accurate of the tools tested. In this article, we have used the protocol to compare statistical tools applied to the analysis of differential gene expression. However, it can also be applied without modification to compare the statistical tools developed for other types of transcriptome analyses, like the study of gene co-expression.

International audience; We propose and study a new approach for the analysis of families of protein sequences. This method is related to the LogDet distances used in phylogenetic reconstructions; it can be viewed as an attempt to embed these distances into a multidimensional framework. The proposed method starts by associating a Markov matrix to each pairwise alignment deduced from a given multiple alignment. The central objects under consideration here are matrix-valued logarithms L of these Markov matrices, which exist under conditions that are compatible with fairly large divergence between the sequences. These logarithms allow us to compare data from a family of aligned proteins with simple models (in particular, continuous reversible Markov models) and to test the adequacy of such models. If one neglects fluctuations arising from the finite length of sequences, any continuous reversible Markov model with a single rate matrix Q over an arbitrary tree predicts that all the observed matrices L are multiples of Q. Our method exploits this fact, without relying on any tree estimation. We test this prediction on a family of proteins encoded by the mitochondrial genome of 26 multicellular animals, which include vertebrates, arthropods, echinoderms, molluscs, and nematodes. A principal component analysis of the observed matrices L shows that a single rate model can be used as a rough approximation to the data, but that systematic deviations from any such model are unmistakable and related to the evolutionary history of the species under consideration.

Genomic analyses on part of Escherichia coli's chromosome had suggested the existence of a GATC regulated network. This has recently been confirmed through a transcriptome analysis. Two hypotheses about the molecular control mechanism have been proposed-(i) the GATC network regulation is caused by the presence of GATC clusters within the coding sequences; the regulation is the direct consequence of the clusters' hemi-methylation and therefore their elevated melting temperature, (ii) the regulation is caused by the presence of GATCs in the non-coding 500 bp upstream regions of the affected genes; it is the consequence of an interaction with a regulatory protein like Fnr or CAP. An analysis of the transcriptome data has not allowed us to decide between the two hypotheses. We have therefore taken a classic genomic approach, analyzing the statistical distribution of GATC along the chromosome, using a realistic model of the chromosome as theoretical reference. We observe no particular distribution of GATC in the non-coding upstream regions; however, we confirm the presence of GATC clusters within the genes. In order to verify that the particular distribution observed in E. coli is not a statistical artefact, but has a physiological role, we have carried out the same analysis on Salmonella, making the hypothesis that the genes containing a GATC clusters should be largely the same in the two bacteria. This has been indeed observed, showing that the genes containing a GATC cluster are part of a regulation network. The present is a case study, which demonstrates that the analysis of transcriptome data does not always permit to identify the primary cause of a phenomenon observed; on the other hand, a classic genomic approach linked with a comparative study of related genomes may allow this identification.

Background A new variant of Creutzfeldt-Jakob disease was described in the United Kingdom. It is often claimed that it is caused by consumption of food infected with the agent of bovine spongiform encephalopathy. However, this remains open to question because the number of cases of the variant is, at the present time, less than would be expected from a major food-borne source. Discussion The EUROCJD cooperative study presents currently available epidemiological data of Creutzfeldt-Jakob disease and its new variant, for nine European countries plus Australia and Canada. Unexpectedly, for the United Kingdom where all but a few cases of the new variant have been reported, these cases have to be included in the incidence curve of the sporadic forms of the disease in order to obtain the best fit with the median curve from all the countries. This variant could be merely a rare clinical phenotype within the sporadic disease. The published clinical and experimental data which suggest that it is linked with bovine spongiform encephalopathy, lead us to propose that this link could be a common etiological origin other than consumption of bovine infected food. In any case, public health recommendations hold and further investigation is required. Summary The lack of a relative increase of the Creutzfeldt-Jakob-disease mortality rate in the United Kingdom, does not fit well with the new variant being the consequence of consumption of food infected with the agent of bovine spongiform encephalopthy.

In the framework of genome annotation, scientific literature is obviously the major source of biological knowledge. The aim of the work described in this paper is to exploit this source of data for the model plant Arabidopsis thaliana. The first step has consisted in constituting a relevant bibliographic references dataset for plant genomic research. Genes co-citations have then been systematically annotated in this reference dataset, starting from the simple idea that if genes are cited in the same publication, they must probably share some related functional properties. In order to deal with the synonymous gene name problem, a gene name reference list has been constituted starting from A. thaliana SwissProt entries. This list was used to build clusters of co-cited genes by a single linkage procedure such that any gene in a given cluster possesses at least one co-cited partner in the same cluster. Analysis of the clusters demonstrate the biological consistency of this approach, with only very few fortuitous links. As an example, a cluster including genes related to flowering time is more deeply described in the paper. Finally, a graphical representation of each cluster was performed, which provides a convenient way to retrieve the genes (the nodes of the graphs) and the references in which they were co-cited (the edges of the graphs). All the results can be accessed at the URL http://chlora.Igi.infobiogen.fr:1234/bib_arath/.

Summary: GeneANOVA is an ANOVA-based software devoted to the analysis of gene expression data. Availability: GeneANOVA is freely available on request for non-commercial use. Contact: didier@genopole.cnrs.fr

Previous analyses of retroviral nucleotide sequences, suggest a so-called "scrambled duplicative stepwise molecular evolution" (many sectors with successive duplications/deletions of short and longer motifs) that could have stemmed from one or several starter tandemly repeated short sequence(s). In the present report, we tested this hypothesis by focusing on the long terminal repeats (LTRs) (and flanking sequences) of 24 human and 3 simian immunodeficiency viruses. By using a calculation strategy applicable to short sequences, we found consensus overrepresented motifs (often containing CTG or CAG) that were congruent with the previously defined "retroviral signature." We also show many local repetition patterns that are significant when compared with simply shuffled sequences. First- and second-order Markov chain analyses demonstrate that a major portion of the overrepresented oligonucleotides can be predicted from the dinucleotide compositions of the sequences, but by no means can biological mechanisms be deduced from these results: some of the listed local repetitions remain significant against dinucleotide-conserving shuffled sequences; together with previous results, this suggests that interspersed and/or local mononucleotide and oligonucleotide repetitions could have biased the dinucleotide compositions of the sequences. We searched for suggestive evolutionary patterns by scrutinizing a reliable multiple alignment of the 27 sequences. A manually constructed alignment based on homology blocks was in good agreement with the polypeptide alignment in the coding sectors and has been exhaustively assessed by using a multiplied alphabet obtained by the promising mathematical strategy called the N-block presentation (taking into account the environment of each nucleotide in a sequence). Sector by sector, we hypothesize many successive duplication/deletion scenarios that fit our previous evolutionary hypotheses. This suggests an important duplication/deletion role for the reverse transcriptase, particularly in inducing stuttering cryptic simplicity patterns.