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/

Annotation of a 95-kb Populus deltoides genomic sequence reveals a disease resistance gene cluster and novel class I and class II transposable elements.

Poplar has become a model system for functional genomics in woody plants. Here, we report the sequencing and annotation of the first large contiguous stretch of genomic sequence (95 kb) of poplar, corresponding to a bacterial artificial chromosome clone mapped 0.6 centiMorgan from the Melampsora larici-populina resistance locus. The annotation revealed 15 putative genetic objects, of which five were classified as hypothetical genes that were similar only with expressed sequence tags from poplar. Ten putative objects showed similarity with known genes, of which one was similar to a kinase. Three other objects corresponded to the toll/interleukin-1 receptor/nucleotide-binding site/leucine-rich repeat class of plant disease resistance genes, of which two were predicted to encode an amino terminal nuclear localization signal. Four objects were homologous to the Ty1/ copia family of class I transposable elements, one of which was designated Retropop and interrupted one of the disease resistance genes. Two other objects constituted a novel Spm-like class II transposable element, which we designated Magali.

A higher-order background model improves the detection of promoter regulatory elements by Gibbs sampling.

MOTIVATION: Transcriptome analysis allows detection and clustering of genes that are coexpressed under various biological circumstances. Under the assumption that coregulated genes share cis-acting regulatory elements, it is important to investigate the upstream sequences controlling the transcription of these genes. To improve the robustness of the Gibbs sampling algorithm to noisy data sets we propose an extension of this algorithm for motif finding with a higher-order background model. RESULTS: Simulated data and real biological data sets with well-described regulatory elements are used to test the influence of the different background models on the performance of the motif detection algorithm. We show that the use of a higher-order model considerably enhances the performance of our motif finding algorithm in the presence of noisy data. For Arabidopsis thaliana, a reliable background model based on a set of carefully selected intergenic sequences was constructed. AVAILABILITY: Our implementation of the Gibbs sampler called the Motif Sampler can be used through a web interface: http://www.esat.kuleuven.ac.be/~thijs/Work/MotifSampler.html. CONTACT: gert.thijs@esat.kuleuven.ac.be; yves.moreau@esat.kuleuven.ac.be