Phylogeny.fr: robust phylogenetic analysis for the non-specialist.

Phylogenetic analyses are central to many research areas in biology and typically involve the identification of homologous sequences, their multiple alignment, the phylogenetic reconstruction and the graphical representation of the inferred tree. The Phylogeny.fr platform transparently chains programs to automatically perform these tasks. It is primarily designed for biologists with no experience in phylogeny, but can also meet the needs of specialists; the first ones will find up-to-date tools chained in a phylogeny pipeline to analyze their data in a simple and robust way, while the specialists will be able to easily build and run sophisticated analyses. Phylogeny.fr offers three main modes. The 'One Click' mode targets non-specialists and provides a ready-to-use pipeline chaining programs with recognized accuracy and speed: MUSCLE for multiple alignment, PhyML for tree building, and TreeDyn for tree rendering. All parameters are set up to suit most studies, and users only have to provide their input sequences to obtain a ready-to-print tree. The 'Advanced' mode uses the same pipeline but allows the parameters of each program to be customized by users. The 'A la Carte' mode offers more flexibility and sophistication, as users can build their own pipeline by selecting and setting up the required steps from a large choice of tools to suit their specific needs. Prior to phylogenetic analysis, users can also collect neighbors of a query sequence by running BLAST on general or specialized databases. A guide tree then helps to select neighbor sequences to be used as input for the phylogeny pipeline. Phylogeny.fr is available at: http://www.phylogeny.fr/

Selfish DNA in protein-coding genes of Rickettsia.

Rickettsia conorii, the aetiological agent of Mediterranean spotted fever, is an intracellular bacterium transmitted by ticks. Preliminary analyses of the nearly complete genome sequence of R. conorii have revealed 44 occurrences of a previously undescribed palindromic repeat (150 base pairs long) throughout the genome. Unexpectedly, this repeat was found inserted in-frame within 19 different R. conorii open reading frames likely to encode functional proteins. We found the same repeat in proteins of other Rickettsia species. The finding of a mobile element inserted in many unrelated genes suggests the potential role of selfish DNA in the creation of new protein sequences.

Mechanisms of evolution in Rickettsia conorii and R. prowazekii.

Rickettsia conorii is an obligate intracellular bacterium that causes Mediterranean spotted fever in humans. We determined the 1,268,755-nucleotide complete genome sequence of R. conorii, containing 1374 open reading frames. This genome exhibits 804 of the 834 genes of the previously determined R. prowazekii genome plus 552 supplementary open reading frames and a 10-fold increase in the number of repetitive elements. Despite these differences, the two genomes exhibit a nearly perfect colinearity that allowed the clear identification of different stages of gene alterations with gene remnants and 37 genes split in 105 fragments, of which 59 are transcribed. A 38-kilobase sequence inversion was dated shortly after the divergence of the genus.

Ancient DNA is thirteen years old.

The first successful recovery of ancient DNA, from quagga and human mummies inspired significant enough interest to open an entire field of research. Efforts from many research groups, often in a hunt for the oldest sequences, showed that ancient DNA was a poor substrate for the enzymes used in molecular biology; it is present in tiny amounts, hard to purify, and frequently damaged. These obstacles have been partially overcome by the use of drastic laboratory precautions and by the introduction of polymerase chain reaction and phylogenetic studies. Ancient DNA analysis now finds applications in many research domains.

Rickettsia felis, from culture to genome sequencing.

Rickettsia felis has been recently cultured in XTC2 cells. This allows production of enough bacteria to create a genomic bank and to sequence it. The chromosome of R. felis is longer than that of previously sequenced rickettsiae and it possess 2 plasmids. Microscopically, this bacterium exhibits two forms of pili: one resembles a conjugative pilus and another forms hair-like projections that may play a role in pathogenicity. R. felis also exhibits several copies of ankyrin-repeat genes and tetratricopeptide encoding gene that are specifically linked to pathogenic host-associated bacteria. It also contains toxin-antitoxin system encoding genes that are extremely rare in intracellular bacteria and may be linked to plasmid maintenance.

Recent advances in computational genomics.

In the post-genomic era, the new discipline of functional genomics is now facing the challenge of associating a function (as well as estimating its relevance to industrial applications) to about 100,000 microbial, plant or animal genes of known sequence but unknown function. Besides the design of databases, computational methods are increasingly becoming intimately linked with the various experimental approaches. Consequently, bioinformatics is rapidly evolving into independent fields addressing the specific problems of interpreting i) genomic sequences, ii) protein sequences and 3D-structures, as well as iii) transcriptome and macromolecular interaction data. It is thus increasingly difficult for the biologist to choose the computational approaches that perform best in these various areas. This paper attempts to review the most useful developments of the last 2 years.

Automatic reading of hybridization filter images.

We describe a new technique for the automatic detection and characterization, in terms of location, size and intensity, of positive hybridization spots on hybridization filter images. We will also discuss how this information can be used to reconstruct the spot deposition pattern on the filter and thus identify the spots. The part of the algorithm dedicated to the detection of spots is derived from a technique used in astronomy for the automatic recognition of galaxies on photographic plates. This technique has been modified so that it becomes able to cope with the strongly varying background typical of hybridization filter images. The technique does not require any human intervention.

Detection of eukaryotic promoters using Markov transition matrices.

Eukaryotic promoters are among the most important functional domains yet to be characterized in a satisfactory manner in genomic sequences. Most current detection methods rely on the recognition of individual transcription elements using position-weight matrices (PWM) or consensus sequences. Here, we study a simple promoter detection algorithm based on Markov transition matrices built from sequences upward from proven transcription initiation sites. The performances have been evaluated on the training set and on a test set of promoter-containing sequences. The results on the training set are surprisingly good, given that the algorithm does not incorporate any specific knowledge about promoters. Yet, the program exhibits the pathological behaviour typical of all training set-based methods: a significant decline in performance when confronted with previously unseen sequences. Thus, the Markov algorithm, like the others presently available, does not truly capture the essence of eukaryotic promoters. A detection program based on a Markov model is likely to be blind to categories of promoters without close representatives in the training set.

The statistical significance of nucleotide position-weight matrix matches.

MOTIVATION: To improve the detection of nucleotide sequence signals (e.g. promoter elements) by position-weight matrices (PWM) using the concept of statistically significant matches. RESULTS: The Mksite program was originally developed for analyzing protein sequences. We report NMksite, a new version adapted to the processing of nucleotide sequences. NMksite creates PWM from nucleotide sequence block alignments or occurrence tables using three weight computation schemes. An original feature of NMksite is the numerical computation of the statistical significance of PWM matches. The utility of this concept is demonstrated in the context of the prediction of splice sites and promoter regions.

Self-identification of protein-coding regions in microbial genomes.

A new method for predicting protein-coding regions in microbial genomic DNA sequences is presented. It uses an ab initio iterative Markov modeling procedure to automatically perform the partition of genomic sequences into three subsets shown to correspond to coding, coding on the opposite strand, and noncoding segments. In contrast to current methods, such as GENEMARK [Borodovsky, M. & McIninch, J. D. (1993) Comput. Chem. 17, 123-133], no training set or prior knowledge of the statistical properties of the studied genome are required. This new method tolerates error rates of 1-2% and can process unassembled sequences. It is thus ideal for the analysis of genome survey and/or fragmented sequence data from uncharacterized microorganisms. The method was validated on 10 complete bacterial genomes (from four major phylogenetic lineages). The results show that protein-coding regions can be identified with an accuracy of up to 90% with a totally automated and objective procedure.

The significance of digital gene expression profiles.

Genes differentially expressed in different tissues, during development, or during specific pathologies are of foremost interest to both basic and pharmaceutical research. "Transcript profiles" or "digital Northerns" are generated routinely by partially sequencing thousands of randomly selected clones from relevant cDNA libraries. Differentially expressed genes can then be detected from variations in the counts of their cognate sequence tags. Here we present the first systematic study on the influence of random fluctuations and sampling size on the reliability of this kind of data. We establish a rigorous significance test and demonstrate its use on publicly available transcript profiles. The theory links the threshold of selection of putatively regulated genes (e.g., the number of pharmaceutical leads) to the fraction of false positive clones one is willing to risk. Our results delineate more precisely and extend the limits within which digital Northern data can be used.

Alternate polyadenylation in human mRNAs: a large-scale analysis by EST clustering.

Alternate polyadenylation is an important post-transcriptional regulatory process now open to large-scale analysis by use of cDNA databases. We clustered 164,000 expressed sequence tags (ESTs) into approximately 15,000 groups and aligned each group to a putative mRNA 3' end. By use of stringent criteria to discard artifactual mRNA extremities, clear evidence for alternate polyadenylation was obtained in 189 of the 1000 EST clusters studied. A number of previously unreported polyadenylation sites were identified, together with possible instances of tissue-specific differential polyadenylation. This study demonstrates that, besides quantitative aspects of gene expression, the distribution of alternate mRNA forms can be analyzed through EST sampling.

SAmBA: an interactive software for optimizing the design of biological macromolecules crystallization experiments.

SAmBA is a new software for the design of minimal experimental protocols using the notion of orthogonal arrays of strength 2. The main application of SAmBA is the search of protein crystallization conditions. Given a user input defining the relevant effectors/variables (e.g., pH, temperature, salts) and states (e.g., pH: 5, 6, 7 and 8), this software proposes an optimal set of experiments in which all tested variables and the pairwise interactions between them are symmetrically sampled. No a priori restrictions on the number and range of experimental variables is imposed. SAmBA consists of two complementary programs, SAm and BA, using a simulated annealing approach and a backtracking algorithm, respectively. The software is freely available as C code or as an interactive JAVA applet at http:/(/)igs-server.cnrs-mrs.fr.

Large-scale statistical analyses of rice ESTs reveal correlated patterns of gene expression.

Large, publicly available collections of expressed sequence tags (ESTs) have been generated from Arabidopsis thaliana and rice (Oryza sativa). A potential, but relatively unexplored application of this data is in the study of plant gene expression. Other EST data, mainly from human and mouse, have been successfully used to point out genes exhibiting tissue- or disease-specific expression, as well as for identification of alternative transcripts. In this report, we go a step further in showing that computer analyses of plant EST data can be used to generate evidence of correlated expression patterns of genes across various tissues. Furthermore, tissue types and organs can be classified with respect to one another on the basis of their global gene expression patterns. As in previous studies, expression profiles are first estimated from EST counts. By clustering gene expression profiles or whole cDNA library profiles, we show that genes with similar functions, or cDNA libraries expected to share patterns of gene expression, are grouped together. Promising uses of this technique include functional genomics, in which evidence of correlated expression might complement (or substitute for) those of sequence similarity in the annotation of anonymous genes and identification of surrogate markers. The analysis presented here combines the application of a correlation-based clustering method with a graphical color map allowing intuitive visualization of patterns within a large table of expression measurements.