Dietary shifts have consequences for the repertoire of allergens produced by the European house dust mite.

Products manufactured from mass-cultured house dust mites, currently commercialized for the diagnosis and immunotherapy of allergy, are heterogeneous in terms of allergen composition and thus present concerns to regulatory authorities. The most abundant species, Dermatophagoides pteronyssinus (Trouessart) (Astigmata: Pyroglyphidae), produces 19 allergenic proteins. Many of these are putatively involved in mite digestive physiology and metabolism. This study aimed to evaluate the effects of mite-rearing media on allergen production. Mites were adapted to feed on culture media supplemented with proteins, lipids, carbohydrates or beard shavings, and collected to quantify major allergens (Der p 1 and 2) by immunodetection, transcription of allergen genes by real-time quantitative polymerase chain reaction, and allergen-related enzymatic activities. All culture media significantly affected the content of major allergens. Modification of macronutrients in the diet produced minor effects on the transcription of allergen genes, but significantly altered mite allergen-related activities. The most remarkable impacts were detected in mites feeding on beard shavings and were reflected in reductions in the content of major allergens, alterations in the transcription of nine allergen genes, and changes in eight allergen-related activities. These results demonstrate the importance of culture media to the quality and consistency of mite extracts used for pharmaceuticals, and highlight the need to further elucidate allergen production by mites in the laboratory and in domestic environments.

Overview of tomato (Solanum lycopersicum) candidate pathogen recognition genes reveals important Solanum R locus dynamics.

To investigate the genome-wide spatial arrangement of R loci, a complete catalogue of tomato (Solanum lycopersicum) and potato (Solanum tuberosum) nucleotide-binding site (NBS) NBS, receptor-like protein (RLP) and receptor-like kinase (RLK) gene repertories was generated. Candidate pathogen recognition genes were characterized with respect to structural diversity, phylogenetic relationships and chromosomal distribution. NBS genes frequently occur in clusters of related gene copies that also include RLP or RLK genes. This scenario is compatible with the existence of selective pressures optimizing coordinated transcription. A number of duplication events associated with lineage-specific evolution were discovered. These findings suggest that different evolutionary mechanisms shaped pathogen recognition gene cluster architecture to expand and to modulate the defence repertoire. Analysis of pathogen recognition gene clusters associated with documented resistance function allowed the identification of adaptive divergence events and the reconstruction of the evolution history of these loci. Differences in candidate pathogen recognition gene number and organization were found between tomato and potato. Most candidate pathogen recognition gene orthologues were distributed at less than perfectly matching positions, suggesting an ongoing lineage-specific rearrangement. Indeed, a local expansion of Toll/Interleukin-1 receptor (TIR)-NBS-leucine-rich repeat (LRR) (TNL) genes in the potato genome was evident. Taken together, these findings have implications for improved understanding of the mechanisms of molecular adaptive selection at Solanum R loci.

The genome of black cottonwood, Populus trichocarpa (Torr. & Gray).

We report the draft genome of the black cottonwood tree, Populus trichocarpa. Integration of shotgun sequence assembly with genetic mapping enabled chromosome-scale reconstruction of the genome. More than 45,000 putative protein-coding genes were identified. Analysis of the assembled genome revealed a whole-genome duplication event; about 8000 pairs of duplicated genes from that event survived in the Populus genome. A second, older duplication event is indistinguishably coincident with the divergence of the Populus and Arabidopsis lineages. Nucleotide substitution, tandem gene duplication, and gross chromosomal rearrangement appear to proceed substantially more slowly in Populus than in Arabidopsis. Populus has more protein-coding genes than Arabidopsis, ranging on average from 1.4 to 1.6 putative Populus homologs for each Arabidopsis gene. However, the relative frequency of protein domains in the two genomes is similar. Overrepresented exceptions in Populus include genes associated with lignocellulosic wall biosynthesis, meristem development, disease resistance, and metabolite transport.

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.

Quantitative cDNA-AFLP analysis for genome-wide expression studies.

An improved cDNA-AFLP method for genome-wide expression analysis has been developed. We demonstrate that this method is an efficient tool for quantitative transcript profiling and a valid alternative to microarrays. Unique transcript tags, generated from reverse-transcribed messenger RNA by restriction enzymes, were screened through a series of selective PCR amplifications. Based on in silico analysis, an enzyme combination was chosen that ensures that at least 60% of all the mRNAs were represented by an informative sequence tag. The sensitivity and specificity of the method allows one to detect poorly expressed genes and distinguish between homologous sequences. Accurate gene expression profiles were determined by quantitative analysis of band intensities, and subtle differences in transcriptional activity were revealed. A detailed screen for cell cycle-modulated genes in tobacco demonstrates the usefulness of the technology for genome-wide expression analysis.

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

Identification of novel cyclin-dependent kinases interacting with the CKS1 protein of Arabidopsis.

The SUC1/CKS1 proteins interact with cyclin-dependent kinases (CDKs) and play an essential, but yet not entirely resolved, role in the regulation of the cell cycle. With the Arabidopsis thaliana CKS1At protein as bait in a two-hybrid screen, two novel Arabidopsis CDKs, Arath;CDKB1;2 and Arath;CDKB2;1, were isolated. A closely related homologue of Arath;CDKB2;1 was discovered in the databases and was nominated Arath;CDKB2;2. Transcript analysis of the five known Arath;CDKA and Arath;CDKB genes revealed that they all had the highest expression in flowers and cell suspensions. Differences in the expression patterns in roots, leaves and stems suggest unique roles for each CDK.

Characterization of two distinct DP-related genes from Arabidopsis thaliana.

E2F/DP complexes play a pivotal role in the regulation of the G1/S transition in animals. Recently, plant E2F homologs have been cloned, but DP-related sequences have not been identified so far. Here we report that Arabidopsis thaliana contains at least two different DP-related genes, AtDPa and AtDPb. They exhibit an overall domain organization similar to that of their animal counterparts, although phylogenetic analysis demonstrated that they form a separate subgroup. AtDPs efficiently heterodimerize in vitro with the Arabidopsis E2F-related proteins, AtE2Fa and AtE2Fb through their dimerization domains. AtDPa and AtE2Fa are predominantly produced in actively dividing cells with highest transcript levels in early S phase cells.

Gene prediction and gene classes in Arabidopsis thaliana.

Gene prediction methods for eukaryotic genomes still are not fully satisfying. One way to improve gene prediction accuracy, proven to be relevant for prokaryotes, is to consider more than one model of genes. Thus, we used our classification of Arabidopsis thaliana genes in two classes (CU(1) and CU(2)), previously delineated according to statistical features, in the GeneMark gene identification program. For each gene class, as well as for the two classes combined, a Markov model was developed (respectively, GM-CU(1), GM-CU(2) and GM-all) and then used on a test set of 168 genes to compare their respective efficiency. We concluded from this analysis that GM-CU(1) is more sensitive than GM-CU(2) which seems to be more specific to a gene type. Besides, GM-all does not give better results than GM-CU(1) and combining results from GM-CU(1) and GM-CU(2) greatly improve prediction efficiency in comparison with predictions made with GM-all only. Thus, this work confirms the necessity to consider more than one gene model for gene prediction in eukaryotic genomes, and to look for gene classes in order to build these models.

Genome annotation: which tools do we have for it?

Genome data have to be converted into knowledge to be useful to biologists. Many valuable computational tools have already been developed to help annotation of plant genome sequences, and these may be improved further, for example by identification of more gene regulatory elements. The lack of a standard computer-assisted annotation platform for eukaryotic genomes remains major bottle-neck.

Evidence for an ancient chromosomal duplication in Arabidopsis thaliana by sequencing and analyzing a 400-kb contig at the APETALA2 locus on chromosome 4.

As part of the European Scientists Sequencing Arabidopsis program, a contiguous region (396607 bp) located on chromosome 4 around the APETALA2 gene was sequenced. Analysis of the sequence and comparison to public databases predicts 103 genes in this area, which represents a gene density of one gene per 3.85 kb. Almost half of the genes show no significant homology to known database entries. In addition, the first 45 kb of the contig, which covers 11 genes, is similar to a region on chromosome 2, as far as coding sequences are concerned. This observation indicates that ancient duplications of large pieces of DNA have occurred in Arabidopsis.

PlantCARE, a plant cis-acting regulatory element database.

PlantCARE is a database of plant cis- acting regulatory elements, enhancers and repressors. Besides the transcription motifs found on a sequence, it also offers a link to the EMBL entry that contains the full gene sequence as well as a description of the conditions in which a motif becomes functional. The information on these sites is given by matrices, consensus and individual site sequences on particular genes, depending on the available information. PlantCARE is a relational database available via the web at the URL: http://sphinx.rug.ac.be:8080/PlantCARE/

Evaluation of gene prediction software using a genomic data set: application to Arabidopsis thaliana sequences.

MOTIVATION: The annotation of the Arabidopsis thaliana genome remains a problem in terms of time and quality. To improve the annotation process, we want to choose the most appropriate tools to use inside a computer-assisted annotation platform. We therefore need evaluation of prediction programs with Arabidopsis sequences containing multiple genes. RESULTS: We have developed AraSet, a data set of contigs of validated genes, enabling the evaluation of multi-gene models for the Arabidopsis genome. Besides conventional metrics to evaluate gene prediction at the site and the exon levels, new measures were introduced for the prediction at the protein sequence level as well as for the evaluation of gene models. This evaluation method is of general interest and could apply to any new gene prediction software and to any eukaryotic genome. The GeneMark.hmm program appears to be the most accurate software at all three levels for the Arabidopsis genomic sequences. Gene modeling could be further improved by combination of prediction software. AVAILABILITY: The AraSet sequence set, the Perl programs and complementary results and notes are available at http://sphinx.rug.ac.be:8080/biocomp/napav/. CONTACT: Pierre.Rouze@gengenp.rug.ac.be.