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Hans-Werner Mewes

Publications and source records attributed to Hans-Werner Mewes.

8 recordsLinked to original sources

Molecular evolution of eukaryotic genomes: hemiascomycetous yeast spliceosomal introns.

As part of the exploratory sequencing program Génolevures, visual scrutinisation and bioinformatic tools were used to detect spliceosomal introns in seven hemiascomycetous yeast species. A total of 153 putative novel introns were identified. Introns are rare in yeast nuclear genes (<5% have an intron), mainly located at the 5' end of ORFs, and not highly conserved in sequence. They all share a clear non-random vocabulary: conserved splice sites and conserved nucleotide contexts around splice sites. Homologues of metazoan snRNAs and putative homologues of SR splicing factors were identified, confirming that the spliceosomal machinery is highly conserved in eukaryotes. Several introns' features were tested as possible markers for phylogenetic analysis. We found that intron sizes vary widely within each genome, and according to the phylogenetic position of the yeast species. The evolutionary origin of spliceosomal introns was examined by analysing the degree of conservation of intron positions in homologous yeast genes. Most introns appeared to exist in the last common ancestor of present day yeast species, and then to have been differentially lost during speciation. However, in some cases, it is difficult to exclude a possible sliding event affecting a pre-existing intron or a gain of a novel intron. Taken together, our results indicate that the origin of spliceosomal introns is complex within a given genome, and that present day introns may have resulted from a dynamic flux between intron conservation, intron loss and intron gain during the evolution of hemiascomycetous yeasts.

Amino Acid Sequence↗

The PEDANT genome database.

The PEDANT genome database (http://pedant.gsf.de) provides exhaustive automatic analysis of genomic sequences by a large variety of established bioinformatics tools through a comprehensive Web-based user interface. One hundred and seventy seven completely sequenced and unfinished genomes have been processed so far, including large eukaryotic genomes (mouse, human) published recently. In this contribution, we describe the current status of the PEDANT database and novel analytical features added to the PEDANT server in 2002. Those include: (i) integration with the BioRS data retrieval system which allows fast text queries, (ii) pre-computed sequence clusters in each complete genome, (iii) a comprehensive set of tools for genome comparison, including genome comparison tables and protein function prediction based on genomic context, and (iv) computation and visualization of protein-protein interaction (PPI) networks based on experimental data. The availability of functional and structural predictions for 650 000 genomic proteins in well organized form makes PEDANT a useful resource for both functional and structural genomics.

Animals↗

Sputnik: a database platform for comparative plant genomics.

Two million plant ESTs, from 20 different plant species, and totalling more than one 1000 Mbp of DNA sequence, represents a formidable transcriptomic resource. Sputnik uses the potential of this sequence resource to fill some of the information gap in the un-sequenced plant genomes and to serve as the foundation for in silicio comparative plant genomics. The complexity of the individual EST collections has been reduced using optimised EST clustering techniques. Annotation of cluster sequences is performed by exploiting and transferring information from the comprehensive knowledgebase already produced for the completed model plant genome (Arabidopsis thaliana) and by performing additional state of-the-art sequence analyses relevant to today's plant biologist. Functional predictions, comparative analyses and associative annotations for 500 000 plant EST derived peptides make Sputnik (http://mips.gsf.de/proj/sputnik/) a valid platform for contemporary plant genomics.

Databases, Nucleic Acid↗

The Protein Information Resource: an integrated public resource of functional annotation of proteins.

The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases).

Amino Acid Sequence↗

How can we deliver the large plant genomes? Strategies and perspectives.

The first sequenced plant genome, from the small mustard plant Arabidopsis thaliana, was published at the end of 2000. The sequencing of the rice genome is well under way. The sizes of plant genomes vary by a factor of up to 1000, and many important crop plants have genomes that are several times larger than the human genome. To gain insight into the gene toolbox of plant species, numerous large-scale EST sequencing projects have been launched successfully, and analysis procedures are constantly being refined to add maximum value to the sequence data. In addition, an alternative approach to exclude repetitive noncoding DNA and to enrich sequence libraries for gene-containing genomic regions has been developed. This strategy has the potential to deliver information about both genes and regulatory regions outside the transcribed regions.

Arabidopsis↗

Exon discovery by genomic sequence alignment.

MOTIVATION: During evolution, functional regions in genomic sequences tend to be more highly conserved than randomly mutating 'junk DNA' so local sequence similarity often indicates biological functionality. This fact can be used to identify functional elements in large eukaryotic DNA sequences by cross-species sequence comparison. In recent years, several gene-prediction methods have been proposed that work by comparing anonymous genomic sequences, for example from human and mouse. The main advantage of these methods is that they are based on simple and generally applicable measures of (local) sequence similarity; unlike standard gene-finding approaches they do not depend on species-specific training data or on the presence of cognate genes in data bases. As all comparative sequence-analysis methods, the new comparative gene-finding approaches critically rely on the quality of the underlying sequence alignments. RESULTS: Herein, we describe a new implementation of the sequence-alignment program DIALIGN that has been developed for alignment of large genomic sequences. We compare our method to the alignment programs PipMaker, WABA and BLAST and we show that local similarities identified by these programs are highly correlated to protein-coding regions. In our test runs, PipMaker was the most sensitive method while DIALIGN was most specific. AVAILABILITY: The program is downloadable from the DIALIGN home page at http://bibiserv.techfak.uni-bielefeld.de/dialign/.

Animals↗

SNAPper: gene order predicts gene function.

UNLABELLED: SNAPper is a network service for predicting gene function based on the conservation of gene order. AVAILABILITY: The SNAPper server is available at http://pedant.gsf.de/snapper. SNAPper-based functional predictions will soon be offered as part of the PEDANT genome analysis server http://pedant.gsf.de.

Algorithms↗

Online genomics facilities in the new millennium.

The review begins by providing a brief typology of biological databases on the Internet, illustrated by examples of the most influential resources of each kind. We then take an insider look at one typical on-line genomic resource -- the yeast genome database hosted at the Munich Information Center for Protein Sequences (MIPS) -- and explain how and why it has evolved from a basic sequence repository to a multidomain knowledge base. The role of community efforts in curating and annotating genome data is discussed. The crucial role of data integration and interoperability in developing next-generation genomic facilities is underscored.

Animals↗