Transposition event detection of transposable element (TE) in the genome using short reads from the next-generation sequence (NGS) was difficult, because the nucleotide sequence of TE itself is repetitive, making it difficult to identify locations of its insertions by alignment programs for NGS. We have developed a program with a new algorithm to detect the transpositions from NGS data.

Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the metabolism of glycans as well as how this impaired metabolism affects various biological functions and human health. In this way, GGDonto will be useful in fields related to glycoscience, including cell biology, biotechnology, and biomedical, and pharmaceutical research.

SummaryThe Integrated Life Science Database Project of Japan funded a group of glycoscientists to carry out a project to integrate glycoscience databases using Semantic Web technologies. As a continuation of the previous project period, the Japan Consortium for Glycobiology and Glycotechnology Database (JCGGDB) developed several glycoscience-related databases. The GlycoProtDB database is among those being integrated, providing an important resource to understand protein glycosylation. Another database being integrated is GlycoEpitope, a comprehensive database of carbohydrate epitopes and antibodies. In the current project period, we started the development of GlyTouCan, the international glycan structure repository providing unique accession numbers to all glycan structures. Although such databases are sufficiently important in and of themselves, their integration with other—omics data such as the protein information in UniProt will be crucial to bring glycosciences to the forefront of life sciences. However, to integrate such disparate sets of data among different fields in a way such that future maintenance costs are minimal, standardized ontologies and formats must be established. Our latest project has attempted to define the minimal standards that are necessary to enable this integration. The technical challenges to integrate all these databases and the technologies to overcome these challenges will be described