G-InforBIO: integrated system for microbial genomics

BACKGROUND: Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs. RESULTS: The G-InforBIO system is a novel tool for genome data management and sequence analysis. The system can import genome data encoded as eXtensible Markup Language documents as formatted text documents, including annotations and sequences, from DNA Data Bank of Japan and GenBank encoded as flat files. The genome database is constructed automatically after importing, and the database can be exported as documents formatted with eXtensible Markup Language or tab-deliminated text. Users can retrieve data from the database by keyword searches, edit annotation data of genes, and process data with G-InforBIO. In addition, information in the G-InforBIO database can be analyzed seamlessly with nine different software programs, including programs for clustering and homology analyses. CONCLUSION: The G-InforBIO system simplifies genome analyses by integrating several available software programs to allow efficient handling and manipulation of genome data. G-InforBIO is freely available from the download site

Specialized microbial databases for inductive exploration of microbial genome sequences

BACKGROUND: The enormous amount of genome sequence data asks for user-oriented databases to manage sequences and annotations. Queries must include search tools permitting function identification through exploration of related objects. METHODS: The GenoList package for collecting and mining microbial genome databases has been rewritten using MySQL as the database management system. Functions that were not available in MySQL, such as nested subquery, have been implemented. RESULTS: Inductive reasoning in the study of genomes starts from "islands of knowledge", centered around genes with some known background. With this concept of "neighborhood" in mind, a modified version of the GenoList structure has been used for organizing sequence data from prokaryotic genomes of particular interest in China. GenoChore , a set of 17 specialized end-user-oriented microbial databases (including one instance of Microsporidia, Encephalitozoon cuniculi, a member of Eukarya) has been made publicly available. These databases allow the user to browse genome sequence and annotation data using standard queries. In addition they provide a weekly update of searches against the world-wide protein sequences data libraries, allowing one to monitor annotation updates on genes of interest. Finally, they allow users to search for patterns in DNA or protein sequences, taking into account a clustering of genes into formal operons, as well as providing extra facilities to query sequences using predefined sequence patterns. CONCLUSION: This growing set of specialized microbial databases organize data created by the first Chinese bacterial genome programs (ThermaList, Thermoanaerobacter tencongensis, LeptoList, with two different genomes of Leptospira interrogans and SepiList, Staphylococcus epidermidis) associated to related organisms for comparison

The Eukaryotic Promoter Database: expansion of EPDnew and new promoter analysis tools

We present an update of EPDNew (http://epd.vital-it.ch), a recently introduced new part of the Eukaryotic Promoter Database (EPD) which has been described in more detail in a previous NAR Database Issue. EPD is an old database of experimentally characterized eukaryotic POL II promoters, which are conceptually defined as transcription initiation sites or regions. EPDnew is a collection of automatically compiled, organism-specific promoter lists complementing the old corpus of manually compiled promoter entries of EPD. This new part is exclusively derived from next generation sequencing data from high-throughput promoter mapping experiments. We report on the recent growth of EPDnew, its extension to additional model organisms and its improved integration with other bioinformatics resources developed by our group, in particular the Signal Search Analysis and ChIP-Seq web server

Assembly and Automated Annotation of the \u3ci\u3eClostridium scatologenes\u3c/i\u3e Genome

Clostridium scatologenes is an anaerobic bacterium that demonstrates some unusual metabolic traits such as the production of 3-methyl indole. The availability of genome level sequencing has lent itself to the exploration and elucidation of unique metabolic pathways in other organisms such as Clostridium botulinum. The Clostridium scatologenes genome, with an estimated length 4.2 million bp, was sequenced by the Applied Biosystems Solid method and the Roche 454 pyrosequencing method. The resulting DNA sequences were combined and assembled into 8267 contigs with an average length of 1250 bp with the Newbler Assembler program. Comparision of published subunits of csd gene and assembled contigs identified that one contig contained all three subunits. In addition a gene with similarity to clostridium carboxidivorans butyrate kinase was found lined next to csd gene. An alignment of the contig and csdgene sequences identified three deletions in the contig within the 4066 bases of the alignment. This implies that there is about 0.07% error rate in the sequencing itself requiring more finishing. Even without finishing the genome assembly into single contig, contigs were annotated in RAST pipeline predicting 2521 protein encoding genes (PEGs). The PEGs were classified by their metabolic function and compared to classified PEGs found in the closely related clostridium species, Clostridium carboxidivorans and Clostridium. ljungdahlii, which have similarly sized genomes. According to the RAST analysis, Clostridium scatologenes had 35% subsystem coverage of all known metabolic processes with its 2521 PEGs. This compares to 41% for Clostridium carboxidivorans with 4174 PEGs (29) and 42% for Clostridium ljungdahlii with 4184 PEGs (30), indicating that Clostridium scatologenesmay still have more genes to be identified. Comparison of the percent genes found in the metabolic subsystems was similar except in motility and chemotaxis. The contigs, on which the csd gene and tryptophan metabolizing genes lay, were examined to see if additional genes might support these metabolic pathways. Butyrate kinase was associated with the csd genes but no other associations were found for the two tryptophan metabolizing genes. The tryptophan biosynthesis operon genes were all found on one contig (contig 6771) and were syntenic with other bacterial species

EPD and EPDnew, high-quality promoter resources in the next-generation sequencing era

The Eukaryotic Promoter Database (EPD), available online at http://epd.vital-it.ch, is a collection of experimentally defined eukaryotic POL II promoters which has been maintained for more than 25 years. A promoter is represented by a single position in the genome, typically the major transcription start site (TSS). EPD primarily serves biologists interested in analysing the motif content, chromatin structure or DNA methylation status of co-regulated promoter subsets. Initially, promoter evidence came from TSS mapping experiments targeted at single genes and published in journal articles. Today, the TSS positions provided by EPD are inferred from next-generation sequencing data distributed in electronic form. Traditionally, EPD has been a high-quality database with low coverage. The focus of recent efforts has been to reach complete gene coverage for important model organisms. To this end, we introduced a new section called EPDnew, which is automatically assembled from multiple, carefully selected input datasets. As another novelty, we started to use chromatin signatures in addition to mRNA 5′tags to locate promoters of weekly expressed genes. Regarding user interfaces, we introduced a new promoter viewer which enables users to explore promoter-defining experimental evidence in a UCSC genome browser windo